diff --git a/docs/docusaurus/package.json b/docs/docusaurus/package.json index 293bdc052bd24..2183be1a360cc 100644 --- a/docs/docusaurus/package.json +++ b/docs/docusaurus/package.json @@ -18,9 +18,10 @@ "dependencies": { "@algolia/client-search": "^4.20.0", "@docsearch/react": "3", - "@docusaurus/core": "^3.5.2", - "@docusaurus/preset-classic": "^3.5.2", - "@docusaurus/theme-search-algolia": "^3.5.2", + "@docusaurus/core": "^3.1.1", + "@docusaurus/plugin-client-redirects": "^3.1.1", + "@docusaurus/preset-classic": "^3.1.1", + "@docusaurus/theme-search-algolia": "^3.1.1", "@mdx-js/react": "^3.0.0", "clsx": "^2.0.0", "fs-extra": "^11.1.1", @@ -29,8 +30,8 @@ "react-dom": "^18.2.0" }, "devDependencies": { - "@docusaurus/module-type-aliases": "^3.5.2", - "@docusaurus/types": "^3.5.2" + "@docusaurus/module-type-aliases": "^3.1.1", + "@docusaurus/types": "^3.1.1" }, "browserslist": { "production": [ diff --git a/docs/docusaurus/sidebars.json b/docs/docusaurus/sidebars.json index d805189a17cd9..ca62261af0844 100644 --- a/docs/docusaurus/sidebars.json +++ b/docs/docusaurus/sidebars.json @@ -112,56 +112,13 @@ "type": "category", "label": "Table Design", "link": { - "type": "doc", - "id": "table_design/catalog_db_tbl" + "type": "generated-index" }, "items": [ - "table_design/StarRocks_table_design", - { - "type": "category", - "label": "Table types", - "link": { - "type": "doc", - "id": "table_design/table_types/table_types" - }, - "items": [ - "table_design/table_types/table_capabilities", - "table_design/table_types/primary_key_table", - "table_design/table_types/duplicate_key_table", - "table_design/table_types/aggregate_table", - "table_design/table_types/unique_key_table" - ] - }, { - "type": "category", - "label": "Data distribution", - "link": { - "type": "doc", - "id": "table_design/Data_distribution" - }, - "items": [ - "table_design/expression_partitioning", - "table_design/list_partitioning", - "table_design/dynamic_partitioning", - "table_design/Temporary_partition", - "table_design/feature-support-data-distribution" - ] - }, - { - "type": "category", - "label": "Indexes", - "link": { - "type": "doc", - "id": "table_design/indexes/indexes_overview" - }, - "items": [ - "table_design/indexes/Prefix_index_sort_key", - "table_design/indexes/Bitmap_index", - "table_design/indexes/Bloomfilter_index" - ] - }, - "table_design/data_compression", - "table_design/hybrid_table" + "type": "autogenerated", + "dirName": "table_design" + } ] }, { diff --git a/docs/docusaurus/yarn.lock b/docs/docusaurus/yarn.lock index 4a791ad20fd36..12c18daad2849 100644 --- a/docs/docusaurus/yarn.lock +++ b/docs/docusaurus/yarn.lock @@ -146,15 +146,7 @@ "@jridgewell/gen-mapping" "^0.3.0" "@jridgewell/trace-mapping" "^0.3.9" -"@babel/code-frame@^7.0.0", "@babel/code-frame@^7.16.0", "@babel/code-frame@^7.22.13", "@babel/code-frame@^7.8.3": - version "7.22.13" - resolved "https://registry.yarnpkg.com/@babel/code-frame/-/code-frame-7.22.13.tgz#e3c1c099402598483b7a8c46a721d1038803755e" - integrity sha512-XktuhWlJ5g+3TJXc5upd9Ks1HutSArik6jf2eAjYFyIOf4ej3RN+184cZbzDvbPnuTJIUhPKKJE3cIsYTiAT3w== - dependencies: - "@babel/highlight" "^7.22.13" - chalk "^2.4.2" - -"@babel/code-frame@^7.23.5": +"@babel/code-frame@^7.0.0", "@babel/code-frame@^7.16.0", "@babel/code-frame@^7.22.13", "@babel/code-frame@^7.23.5", "@babel/code-frame@^7.8.3": version "7.23.5" resolved "https://registry.yarnpkg.com/@babel/code-frame/-/code-frame-7.23.5.tgz#9009b69a8c602293476ad598ff53e4562e15c244" integrity sha512-CgH3s1a96LipHCmSUmYFPwY7MNx8C3avkq7i4Wl3cfa662ldtUe4VM1TPXX70pfmrlWTb6jLqTYrZyT2ZTJBgA== @@ -162,101 +154,42 @@ "@babel/highlight" "^7.23.4" chalk "^2.4.2" -"@babel/code-frame@^7.24.7": - 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infima "0.2.0-alpha.44" + infima "0.2.0-alpha.43" lodash "^4.17.21" nprogress "^0.2.0" postcss "^8.4.26" @@ -2426,15 +1538,18 @@ tslib "^2.6.0" utility-types "^3.10.0" -"@docusaurus/theme-common@3.5.2": - version "3.5.2" - resolved "https://registry.yarnpkg.com/@docusaurus/theme-common/-/theme-common-3.5.2.tgz#b507ab869a1fba0be9c3c9d74f2f3d74c3ac78b2" - integrity sha512-QXqlm9S6x9Ibwjs7I2yEDgsCocp708DrCrgHgKwg2n2AY0YQ6IjU0gAK35lHRLOvAoJUfCKpQAwUykB0R7+Eew== - dependencies: - "@docusaurus/mdx-loader" "3.5.2" - "@docusaurus/module-type-aliases" "3.5.2" - "@docusaurus/utils" "3.5.2" - "@docusaurus/utils-common" "3.5.2" +"@docusaurus/theme-common@3.1.1": + version "3.1.1" + resolved "https://registry.yarnpkg.com/@docusaurus/theme-common/-/theme-common-3.1.1.tgz#5a16893928b8379c9e83aef01d753e7e142459e2" + integrity sha512-38urZfeMhN70YaXkwIGXmcUcv2CEYK/2l4b05GkJPrbEbgpsIZM3Xc+Js2ehBGGZmfZq8GjjQ5RNQYG+MYzCYg== + dependencies: + "@docusaurus/mdx-loader" "3.1.1" + "@docusaurus/module-type-aliases" "3.1.1" + "@docusaurus/plugin-content-blog" "3.1.1" + "@docusaurus/plugin-content-docs" "3.1.1" + "@docusaurus/plugin-content-pages" "3.1.1" + "@docusaurus/utils" "3.1.1" + "@docusaurus/utils-common" "3.1.1" "@types/history" "^4.7.11" "@types/react" "*" "@types/react-router-config" "*" @@ -2444,19 +1559,19 @@ tslib "^2.6.0" utility-types "^3.10.0" -"@docusaurus/theme-search-algolia@3.5.2", "@docusaurus/theme-search-algolia@^3.5.2": - 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prompts "^2.4.2" resolve-pathname "^3.0.0" shelljs "^0.8.5" tslib "^2.6.0" url-loader "^4.1.1" - utility-types "^3.10.0" webpack "^5.88.1" "@hapi/hoek@^9.0.0": @@ -2576,15 +1685,6 @@ "@jridgewell/sourcemap-codec" "^1.4.10" "@jridgewell/trace-mapping" "^0.3.9" -"@jridgewell/gen-mapping@^0.3.5": - version "0.3.5" - resolved "https://registry.yarnpkg.com/@jridgewell/gen-mapping/-/gen-mapping-0.3.5.tgz#dcce6aff74bdf6dad1a95802b69b04a2fcb1fb36" - integrity sha512-IzL8ZoEDIBRWEzlCcRhOaCupYyN5gdIK+Q6fbFdPDg6HqX6jpkItn7DFIpW9LQzXG6Df9sA7+OKnq0qlz/GaQg== - dependencies: - "@jridgewell/set-array" "^1.2.1" - "@jridgewell/sourcemap-codec" "^1.4.10" - "@jridgewell/trace-mapping" "^0.3.24" - "@jridgewell/resolve-uri@^3.1.0": version "3.1.1" resolved "https://registry.yarnpkg.com/@jridgewell/resolve-uri/-/resolve-uri-3.1.1.tgz#c08679063f279615a3326583ba3a90d1d82cc721" @@ -2595,11 +1695,6 @@ resolved "https://registry.yarnpkg.com/@jridgewell/set-array/-/set-array-1.1.2.tgz#7c6cf998d6d20b914c0a55a91ae928ff25965e72" integrity sha512-xnkseuNADM0gt2bs+BvhO0p78Mk762YnZdsuzFV018NoG1Sj1SCQvpSqa7XUaTam5vAGasABV9qXASMKnFMwMw== -"@jridgewell/set-array@^1.2.1": - 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dependencies: - "@babel/compat-data" "^7.22.6" - "@babel/helper-define-polyfill-provider" "^0.6.2" - semver "^6.3.1" - babel-plugin-polyfill-corejs2@^0.4.6: version "0.4.6" resolved "https://registry.yarnpkg.com/babel-plugin-polyfill-corejs2/-/babel-plugin-polyfill-corejs2-0.4.6.tgz#b2df0251d8e99f229a8e60fc4efa9a68b41c8313" @@ -3605,14 +2680,6 @@ babel-plugin-polyfill-corejs2@^0.4.6: "@babel/helper-define-polyfill-provider" "^0.4.3" semver "^6.3.1" -babel-plugin-polyfill-corejs3@^0.10.6: - version "0.10.6" - resolved "https://registry.yarnpkg.com/babel-plugin-polyfill-corejs3/-/babel-plugin-polyfill-corejs3-0.10.6.tgz#2deda57caef50f59c525aeb4964d3b2f867710c7" - integrity sha512-b37+KR2i/khY5sKmWNVQAnitvquQbNdWy6lJdsr0kmquCKEEUgMKK4SboVM3HtfnZilfjr4MMQ7vY58FVWDtIA== - dependencies: - "@babel/helper-define-polyfill-provider" "^0.6.2" - core-js-compat "^3.38.0" - babel-plugin-polyfill-corejs3@^0.8.5: version "0.8.6" resolved "https://registry.yarnpkg.com/babel-plugin-polyfill-corejs3/-/babel-plugin-polyfill-corejs3-0.8.6.tgz#25c2d20002da91fe328ff89095c85a391d6856cf" @@ -3628,13 +2695,6 @@ babel-plugin-polyfill-regenerator@^0.5.3: dependencies: "@babel/helper-define-polyfill-provider" "^0.4.3" -babel-plugin-polyfill-regenerator@^0.6.1: - version "0.6.2" - resolved "https://registry.yarnpkg.com/babel-plugin-polyfill-regenerator/-/babel-plugin-polyfill-regenerator-0.6.2.tgz#addc47e240edd1da1058ebda03021f382bba785e" - integrity sha512-2R25rQZWP63nGwaAswvDazbPXfrM3HwVoBXK6HcqeKrSrL/JqcC/rDcf95l4r7LXLyxDXc8uQDa064GubtCABg== - dependencies: - "@babel/helper-define-polyfill-provider" "^0.6.2" - bail@^2.0.0: version "2.0.2" resolved "https://registry.yarnpkg.com/bail/-/bail-2.0.2.tgz#d26f5cd8fe5d6f832a31517b9f7c356040ba6d5d" @@ -3736,17 +2796,7 @@ braces@^3.0.2, braces@~3.0.2: dependencies: fill-range "^7.0.1" -browserslist@^4.0.0, browserslist@^4.14.5, browserslist@^4.18.1, browserslist@^4.21.10, browserslist@^4.21.9, browserslist@^4.22.1: - version "4.22.1" - resolved "https://registry.yarnpkg.com/browserslist/-/browserslist-4.22.1.tgz#ba91958d1a59b87dab6fed8dfbcb3da5e2e9c619" - integrity sha512-FEVc202+2iuClEhZhrWy6ZiAcRLvNMyYcxZ8raemul1DYVOVdFsbqckWLdsixQZCpJlwe77Z3UTalE7jsjnKfQ== - dependencies: - caniuse-lite "^1.0.30001541" - electron-to-chromium "^1.4.535" - node-releases "^2.0.13" - update-browserslist-db "^1.0.13" - -browserslist@^4.22.2: +browserslist@^4.0.0, browserslist@^4.14.5, browserslist@^4.18.1, browserslist@^4.21.10, browserslist@^4.21.4, browserslist@^4.21.9, browserslist@^4.22.2: version "4.22.2" resolved "https://registry.yarnpkg.com/browserslist/-/browserslist-4.22.2.tgz#704c4943072bd81ea18997f3bd2180e89c77874b" integrity sha512-0UgcrvQmBDvZHFGdYUehrCNIazki7/lUP3kkoi/r3YB2amZbFM9J43ZRkJTXBUZK4gmx56+Sqk9+Vs9mwZx9+A== @@ -3756,16 +2806,6 @@ browserslist@^4.22.2: node-releases "^2.0.14" update-browserslist-db "^1.0.13" -browserslist@^4.23.0, browserslist@^4.23.1, browserslist@^4.23.3: - version "4.23.3" - resolved "https://registry.yarnpkg.com/browserslist/-/browserslist-4.23.3.tgz#debb029d3c93ebc97ffbc8d9cbb03403e227c800" - integrity sha512-btwCFJVjI4YWDNfau8RhZ+B1Q/VLoUITrm3RlP6y1tYGWIOa+InuYiRGXUBXo8nA1qKmHMyLB/iVQg5TT4eFoA== - dependencies: - caniuse-lite "^1.0.30001646" - electron-to-chromium "^1.5.4" - node-releases "^2.0.18" - update-browserslist-db "^1.1.0" - buffer-from@^1.0.0: version "1.1.2" resolved "https://registry.yarnpkg.com/buffer-from/-/buffer-from-1.1.2.tgz#2b146a6fd72e80b4f55d255f35ed59a3a9a41bd5" @@ -3799,7 +2839,7 @@ cacheable-request@^10.2.8: normalize-url "^8.0.0" responselike "^3.0.0" -call-bind@^1.0.0, call-bind@^1.0.2: +call-bind@^1.0.0, call-bind@^1.0.5: version "1.0.5" resolved "https://registry.yarnpkg.com/call-bind/-/call-bind-1.0.5.tgz#6fa2b7845ce0ea49bf4d8b9ef64727a2c2e2e513" integrity sha512-C3nQxfFZxFRVoJoGKKI8y3MOEo129NQ+FgQ08iye+Mk4zNZZGdjfs06bVTr+DBSlA66Q2VEcMki/cUCP4SercQ== @@ -3841,14 +2881,9 @@ caniuse-api@^3.0.0: lodash.memoize "^4.1.2" lodash.uniq "^4.5.0" -caniuse-lite@^1.0.0, caniuse-lite@^1.0.30001538, caniuse-lite@^1.0.30001541, caniuse-lite@^1.0.30001565: - version "1.0.30001651" - resolved "https://registry.npmjs.org/caniuse-lite/-/caniuse-lite-1.0.30001651.tgz" - integrity sha512-9Cf+Xv1jJNe1xPZLGuUXLNkE1BoDkqRqYyFJ9TDYSqhduqA4hu4oR9HluGoWYQC/aj8WHjsGVV+bwkh0+tegRg== - -caniuse-lite@^1.0.30001646: +caniuse-lite@^1.0.0, caniuse-lite@^1.0.30001538, caniuse-lite@^1.0.30001565: version "1.0.30001653" - resolved "https://registry.yarnpkg.com/caniuse-lite/-/caniuse-lite-1.0.30001653.tgz#b8af452f8f33b1c77f122780a4aecebea0caca56" + resolved "https://registry.npmjs.org/caniuse-lite/-/caniuse-lite-1.0.30001653.tgz" integrity sha512-XGWQVB8wFQ2+9NZwZ10GxTYC5hk0Fa+q8cSkr0tgvMhYhMHP/QC+WTgrePMDBWiWc/pV+1ik82Al20XOK25Gcw== ccount@^2.0.0: @@ -3915,7 +2950,7 @@ cheerio-select@^2.1.0: domhandler "^5.0.3" domutils "^3.0.1" -cheerio@1.0.0-rc.12: +cheerio@^1.0.0-rc.12: version "1.0.0-rc.12" resolved "https://registry.yarnpkg.com/cheerio/-/cheerio-1.0.0-rc.12.tgz#788bf7466506b1c6bf5fae51d24a2c4d62e47683" integrity sha512-VqR8m68vM46BNnuZ5NtnGBKIE/DfN0cRIzg9n40EIq9NOv90ayxLBXA8fXC5gquFRGJSTRqBq25Jt2ECLR431Q== @@ -3954,9 +2989,9 @@ ci-info@^3.2.0: integrity sha512-NIxF55hv4nSqQswkAeiOi1r83xy8JldOFDTWiug55KBu9Jnblncd2U6ViHmYgHf01TPZS77NJBhBMKdWj9HQMQ== clean-css@^5.2.2, clean-css@^5.3.2, clean-css@~5.3.2: - 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integrity sha512-a8zeCdyVk7uF2elKIGz67AjcXOxjRbwOLz8SbklEso1V+2DoW4OkAMZN9S9GBgvZIaqQi/OemFX4OiSoQEmg1Q== + version "3.34.0" + resolved "https://registry.yarnpkg.com/core-js-pure/-/core-js-pure-3.34.0.tgz#981e462500708664c91b827a75b011f04a8134a0" + integrity sha512-pmhivkYXkymswFfbXsANmBAewXx86UBfmagP+w0wkK06kLsLlTK5oQmsURPivzMkIBQiYq2cjamcZExIwlFQIg== core-js@^3.31.1: - version "3.33.2" - resolved "https://registry.yarnpkg.com/core-js/-/core-js-3.33.2.tgz#312bbf6996a3a517c04c99b9909cdd27138d1ceb" - integrity sha512-XeBzWI6QL3nJQiHmdzbAOiMYqjrb7hwU7A39Qhvd/POSa/t9E1AeZyEZx3fNvp/vtM8zXwhoL0FsiS0hD0pruQ== + version "3.34.0" + resolved "https://registry.yarnpkg.com/core-js/-/core-js-3.34.0.tgz#5705e6ad5982678612e96987d05b27c6c7c274a5" + integrity sha512-aDdvlDder8QmY91H88GzNi9EtQi2TjvQhpCX6B1v/dAZHU1AuLgHvRh54RiOerpEhEW46Tkf+vgAViB/CWC0ag== core-util-is@~1.0.0: version "1.0.3" @@ -4220,7 +3243,18 @@ cosmiconfig@^6.0.0: path-type "^4.0.0" yaml "^1.7.2" -cosmiconfig@^8.1.3, cosmiconfig@^8.2.0: +cosmiconfig@^7.0.1: + version "7.1.0" + resolved "https://registry.yarnpkg.com/cosmiconfig/-/cosmiconfig-7.1.0.tgz#1443b9afa596b670082ea46cbd8f6a62b84635f6" + integrity sha512-AdmX6xUzdNASswsFtmwSt7Vj8po9IuqXm0UXz7QKPuEUmPB4XyjGfaAr2PSuELMwkRMVH1EpIkX5bTZGRB3eCA== + dependencies: + "@types/parse-json" "^4.0.0" + import-fresh "^3.2.1" + parse-json "^5.0.0" + path-type "^4.0.0" + yaml "^1.10.0" + +cosmiconfig@^8.2.0: version "8.3.6" resolved "https://registry.yarnpkg.com/cosmiconfig/-/cosmiconfig-8.3.6.tgz#060a2b871d66dba6c8538ea1118ba1ac16f5fae3" integrity sha512-kcZ6+W5QzcJ3P1Mt+83OUv/oHFqZHIx8DuxG6eZ5RGMERoLqp4BuGjhHLYGK+Kf5XVkQvqBSmAy/nGWN3qDgEA== @@ -4246,10 +3280,10 @@ crypto-random-string@^4.0.0: dependencies: type-fest "^1.0.1" -css-declaration-sorter@^7.2.0: - version "7.2.0" - resolved "https://registry.yarnpkg.com/css-declaration-sorter/-/css-declaration-sorter-7.2.0.tgz#6dec1c9523bc4a643e088aab8f09e67a54961024" - integrity sha512-h70rUM+3PNFuaBDTLe8wF/cdWu+dOZmb7pJt8Z2sedYbAcQVQV/tEchueg3GWxwqS0cxtbxmaHEdkNACqcvsow== +css-declaration-sorter@^6.3.1: + version "6.4.1" + resolved "https://registry.yarnpkg.com/css-declaration-sorter/-/css-declaration-sorter-6.4.1.tgz#28beac7c20bad7f1775be3a7129d7eae409a3a71" + integrity sha512-rtdthzxKuyq6IzqX6jEcIzQF/YqccluefyCYheovBOLhFT/drQA9zj/UbRAa9J7C0o6EG6u3E6g+vKkay7/k3g== css-loader@^6.8.1: version "6.8.1" @@ -4265,17 +3299,17 @@ css-loader@^6.8.1: postcss-value-parser "^4.2.0" semver "^7.3.8" -css-minimizer-webpack-plugin@^5.0.1: - version "5.0.1" - resolved "https://registry.yarnpkg.com/css-minimizer-webpack-plugin/-/css-minimizer-webpack-plugin-5.0.1.tgz#33effe662edb1a0bf08ad633c32fa75d0f7ec565" - integrity sha512-3caImjKFQkS+ws1TGcFn0V1HyDJFq1Euy589JlD6/3rV2kj+w7r5G9WDMgSHvpvXHNZ2calVypZWuEDQd9wfLg== - dependencies: - "@jridgewell/trace-mapping" "^0.3.18" - cssnano "^6.0.1" - jest-worker "^29.4.3" - postcss "^8.4.24" - schema-utils "^4.0.1" - serialize-javascript "^6.0.1" +css-minimizer-webpack-plugin@^4.2.2: + version "4.2.2" + resolved "https://registry.yarnpkg.com/css-minimizer-webpack-plugin/-/css-minimizer-webpack-plugin-4.2.2.tgz#79f6199eb5adf1ff7ba57f105e3752d15211eb35" + integrity sha512-s3Of/4jKfw1Hj9CxEO1E5oXhQAxlayuHO2y/ML+C6I9sQ7FdzfEV6QgMLN3vI+qFsjJGIAFLKtQK7t8BOXAIyA== + dependencies: + cssnano "^5.1.8" + jest-worker "^29.1.2" + postcss "^8.4.17" + schema-utils "^4.0.0" + serialize-javascript "^6.0.0" + source-map "^0.6.1" css-select@^4.1.3: version "4.3.0" @@ -4299,21 +3333,13 @@ css-select@^5.1.0: domutils "^3.0.1" nth-check "^2.0.1" -css-tree@^2.3.1: - version "2.3.1" - resolved "https://registry.yarnpkg.com/css-tree/-/css-tree-2.3.1.tgz#10264ce1e5442e8572fc82fbe490644ff54b5c20" - integrity sha512-6Fv1DV/TYw//QF5IzQdqsNDjx/wc8TrMBZsqjL9eW01tWb7R7k/mq+/VXfJCl7SoD5emsJop9cOByJZfs8hYIw== - 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style-to-object "^0.4.0" + style-to-object "^1.0.0" unist-util-position "^5.0.0" vfile-message "^4.0.0" @@ -5512,6 +4524,11 @@ html-entities@^2.3.2: resolved "https://registry.yarnpkg.com/html-entities/-/html-entities-2.4.0.tgz#edd0cee70402584c8c76cc2c0556db09d1f45061" integrity sha512-igBTJcNNNhvZFRtm8uA6xMY6xYleeDwn3PeBCkDz7tHttv4F2hsDI2aPgNERWzvRcNYHNT3ymRaQzllmXj4YsQ== +html-escaper@^2.0.2: + version "2.0.2" + resolved "https://registry.yarnpkg.com/html-escaper/-/html-escaper-2.0.2.tgz#dfd60027da36a36dfcbe236262c00a5822681453" + integrity sha512-H2iMtd0I4Mt5eYiapRdIDjp+XzelXQ0tFE4JS7YFwFevXXMmOp9myNrUvCg0D6ws8iqkRPBfKHgbwig1SmlLfg== + html-minifier-terser@^6.0.2: version "6.1.0" resolved "https://registry.yarnpkg.com/html-minifier-terser/-/html-minifier-terser-6.1.0.tgz#bfc818934cc07918f6b3669f5774ecdfd48f32ab" @@ -5549,9 +4566,9 @@ html-void-elements@^3.0.0: integrity sha512-bEqo66MRXsUGxWHV5IP0PUiAWwoEjba4VCzg0LjFJBpchPaTfyfCKTG6bc5F8ucKec3q5y6qOdGyYTSBEvhCrg== html-webpack-plugin@^5.5.3: - 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-lodash.flatten@^4.4.0: - version "4.4.0" - resolved "https://registry.yarnpkg.com/lodash.flatten/-/lodash.flatten-4.4.0.tgz#f31c22225a9632d2bbf8e4addbef240aa765a61f" - integrity sha512-C5N2Z3DgnnKr0LOpv/hKCgKdb7ZZwafIrsesve6lmzvZIRZRGaZ/l6Q8+2W7NaT+ZwO3fFlSCzCzrDCFdJfZ4g== - -lodash.invokemap@^4.6.0: - version "4.6.0" - resolved "https://registry.yarnpkg.com/lodash.invokemap/-/lodash.invokemap-4.6.0.tgz#1748cda5d8b0ef8369c4eb3ec54c21feba1f2d62" - integrity sha512-CfkycNtMqgUlfjfdh2BhKO/ZXrP8ePOX5lEU/g0R3ItJcnuxWDwokMGKx1hWcfOikmyOVx6X9IwWnDGlgKl61w== - lodash.memoize@^4.1.2: version "4.1.2" resolved "https://registry.yarnpkg.com/lodash.memoize/-/lodash.memoize-4.1.2.tgz#bcc6c49a42a2840ed997f323eada5ecd182e0bfe" integrity sha512-t7j+NzmgnQzTAYXcsHYLgimltOV1MXHtlOWf6GjL9Kj8GK5FInw5JotxvbOs+IvV1/Dzo04/fCGfLVs7aXb4Ag== -lodash.pullall@^4.2.0: - version "4.2.0" - resolved "https://registry.yarnpkg.com/lodash.pullall/-/lodash.pullall-4.2.0.tgz#9d98b8518b7c965b0fae4099bd9fb7df8bbf38ba" - integrity sha512-VhqxBKH0ZxPpLhiu68YD1KnHmbhQJQctcipvmFnqIBDYzcIHzf3Zpu0tpeOKtR4x76p9yohc506eGdOjTmyIBg== - lodash.uniq@^4.5.0: version "4.5.0" resolved "https://registry.yarnpkg.com/lodash.uniq/-/lodash.uniq-4.5.0.tgz#d0225373aeb652adc1bc82e4945339a842754773" integrity sha512-xfBaXQd9ryd9dlSDvnvI0lvxfLJlYAZzXomUYzLKtUeOQvOP5piqAWuGtrhWeqaXK9hhoM/iyJc5AV+XfsX3HQ== -lodash.uniqby@^4.7.0: - version "4.7.0" - resolved "https://registry.yarnpkg.com/lodash.uniqby/-/lodash.uniqby-4.7.0.tgz#d99c07a669e9e6d24e1362dfe266c67616af1302" - integrity sha512-e/zcLx6CSbmaEgFHCA7BnoQKyCtKMxnuWrJygbwPs/AIn+IMKl66L8/s+wBUn5LRw2pZx3bUHibiV1b6aTWIww== - lodash@^4.17.20, lodash@^4.17.21: version "4.17.21" resolved "https://registry.yarnpkg.com/lodash/-/lodash-4.17.21.tgz#679591c564c3bffaae8454cf0b3df370c3d6911c" @@ -6463,15 +5460,10 @@ mdast-util-to-string@^4.0.0: dependencies: "@types/mdast" "^4.0.0" -mdn-data@2.0.28: - version "2.0.28" - resolved "https://registry.yarnpkg.com/mdn-data/-/mdn-data-2.0.28.tgz#5ec48e7bef120654539069e1ae4ddc81ca490eba" - integrity sha512-aylIc7Z9y4yzHYAJNuESG3hfhC+0Ibp/MAMiaOZgNv4pmEdFyfZhhhny4MNiAfWdBQ1RQ2mfDWmM1x8SvGyp8g== - -mdn-data@2.0.30: - version "2.0.30" - resolved "https://registry.yarnpkg.com/mdn-data/-/mdn-data-2.0.30.tgz#ce4df6f80af6cfbe218ecd5c552ba13c4dfa08cc" - integrity sha512-GaqWWShW4kv/G9IEucWScBx9G1/vsFZZJUO+tD26M8J8z3Kw5RDQjaoZe03YAClgeS/SWPOcb4nkFBTEi5DUEA== +mdn-data@2.0.14: + version "2.0.14" + resolved "https://registry.yarnpkg.com/mdn-data/-/mdn-data-2.0.14.tgz#7113fc4281917d63ce29b43446f701e68c25ba50" + integrity sha512-dn6wd0uw5GsdswPFfsgMp5NSB0/aDe6fK94YJV/AJDYXL6HVLWBsxeq7js7Ad+mU2K9LAlwpk6kN2D5mwCPVow== media-typer@0.3.0: version "0.3.0" @@ -7025,11 +6017,6 @@ multicast-dns@^7.2.5: dns-packet "^5.2.2" thunky "^1.0.2" -nanoid@^3.3.6: - version "3.3.6" - resolved "https://registry.yarnpkg.com/nanoid/-/nanoid-3.3.6.tgz#443380c856d6e9f9824267d960b4236ad583ea4c" - integrity sha512-BGcqMMJuToF7i1rt+2PWSNVnWIkGCU78jBG3RxO/bZlnZPK2Cmi2QaffxGO/2RvWi9sL+FAiRiXMgsyxQ1DIDA== - nanoid@^3.3.7: version "3.3.7" resolved "https://registry.yarnpkg.com/nanoid/-/nanoid-3.3.7.tgz#d0c301a691bc8d54efa0a2226ccf3fe2fd656bd8" @@ -7054,11 +6041,11 @@ no-case@^3.0.4: tslib "^2.0.3" node-emoji@^2.1.0: - version "2.1.0" - resolved "https://registry.yarnpkg.com/node-emoji/-/node-emoji-2.1.0.tgz#93c99b0d3dfe7d5e37c056aded389e013c72d0c5" - integrity sha512-tcsBm9C6FmPN5Wo7OjFi9lgMyJjvkAeirmjR/ax8Ttfqy4N8PoFic26uqFTIgayHPNI5FH4ltUvfh9kHzwcK9A== + version "2.1.3" + resolved "https://registry.yarnpkg.com/node-emoji/-/node-emoji-2.1.3.tgz#93cfabb5cc7c3653aa52f29d6ffb7927d8047c06" + integrity sha512-E2WEOVsgs7O16zsURJ/eH8BqhF029wGpEOnv7Urwdo2wmQanOACwJQh0devF9D9RhoZru0+9JXIS0dBXIAz+lA== dependencies: - "@sindresorhus/is" "^3.1.2" + "@sindresorhus/is" "^4.6.0" char-regex "^1.0.2" emojilib "^2.4.0" skin-tone "^2.0.0" @@ -7068,21 +6055,11 @@ node-forge@^1: resolved "https://registry.yarnpkg.com/node-forge/-/node-forge-1.3.1.tgz#be8da2af243b2417d5f646a770663a92b7e9ded3" integrity sha512-dPEtOeMvF9VMcYV/1Wb8CPoVAXtp6MKMlcbAt4ddqmGqUJ6fQZFXkNZNkNlfevtNkGtaSoXf/vNNNSvgrdXwtA== -node-releases@^2.0.13: - version "2.0.13" - resolved "https://registry.yarnpkg.com/node-releases/-/node-releases-2.0.13.tgz#d5ed1627c23e3461e819b02e57b75e4899b1c81d" - integrity sha512-uYr7J37ae/ORWdZeQ1xxMJe3NtdmqMC/JZK+geofDrkLUApKRHPd18/TxtBOJ4A0/+uUIliorNrfYV6s1b02eQ== - node-releases@^2.0.14: version "2.0.14" resolved "https://registry.yarnpkg.com/node-releases/-/node-releases-2.0.14.tgz#2ffb053bceb8b2be8495ece1ab6ce600c4461b0b" integrity sha512-y10wOWt8yZpqXmOgRo77WaHEmhYQYGNA6y421PKsKYWEK8aW+cqAphborZDhqfyKrbZEN92CN1X2KbafY2s7Yw== -node-releases@^2.0.18: - version "2.0.18" - resolved "https://registry.yarnpkg.com/node-releases/-/node-releases-2.0.18.tgz#f010e8d35e2fe8d6b2944f03f70213ecedc4ca3f" - integrity sha512-d9VeXT4SJ7ZeOqGX6R5EM022wpL+eWPooLI+5UpWn2jCT1aosUQEhQP214x33Wkwx3JQMvIm+tIoVOdodFS40g== - normalize-path@^3.0.0, normalize-path@~3.0.0: version "3.0.0" resolved "https://registry.yarnpkg.com/normalize-path/-/normalize-path-3.0.0.tgz#0dcd69ff23a1c9b11fd0978316644a0388216a65" @@ -7093,6 +6070,11 @@ normalize-range@^0.1.2: resolved "https://registry.yarnpkg.com/normalize-range/-/normalize-range-0.1.2.tgz#2d10c06bdfd312ea9777695a4d28439456b75942" integrity sha512-bdok/XvKII3nUpklnV6P2hxtMNrCboOjAcyBuQnWEhO665FwrSNRxU+AqpsyvO6LgGYPspN+lu5CLtw4jPRKNA== +normalize-url@^6.0.1: + version "6.1.0" + resolved "https://registry.yarnpkg.com/normalize-url/-/normalize-url-6.1.0.tgz#40d0885b535deffe3f3147bec877d05fe4c5668a" + integrity sha512-DlL+XwOy3NxAQ8xuC0okPgK46iuVNAK01YN7RueYBqqFeGsBjV9XmCAzAdgt+667bCl5kPh9EqKKDwnaPG1I7A== + normalize-url@^8.0.0: version "8.0.0" resolved "https://registry.yarnpkg.com/normalize-url/-/normalize-url-8.0.0.tgz#593dbd284f743e8dcf6a5ddf8fadff149c82701a" @@ -7133,12 +6115,12 @@ object-keys@^1.1.1: integrity sha512-NuAESUOUMrlIXOfHKzD6bpPu3tYt3xvjNdRIQ+FeT0lNb4K8WR70CaDxhuNguS2XG+GjkyMwOzsN5ZktImfhLA== object.assign@^4.1.0: - version "4.1.4" - resolved "https://registry.yarnpkg.com/object.assign/-/object.assign-4.1.4.tgz#9673c7c7c351ab8c4d0b516f4343ebf4dfb7799f" - integrity sha512-1mxKf0e58bvyjSCtKYY4sRe9itRk3PJpquJOjeIkz885CczcI4IvJJDLPS72oowuSh+pBxUFROpX+TU++hxhZQ== + version "4.1.5" + resolved "https://registry.yarnpkg.com/object.assign/-/object.assign-4.1.5.tgz#3a833f9ab7fdb80fc9e8d2300c803d216d8fdbb0" + integrity sha512-byy+U7gp+FVwmyzKPYhW2h5l3crpmGsxl7X2s8y43IgxvG4g3QZ6CffDtsNQy1WsmZpQbO+ybo0AlW7TY6DcBQ== dependencies: - call-bind "^1.0.2" - define-properties "^1.1.4" + call-bind "^1.0.5" + define-properties "^1.2.1" has-symbols "^1.0.3" object-keys "^1.1.1" @@ -7407,11 +6389,6 @@ picocolors@^1.0.0: resolved "https://registry.yarnpkg.com/picocolors/-/picocolors-1.0.0.tgz#cb5bdc74ff3f51892236eaf79d68bc44564ab81c" integrity sha512-1fygroTLlHu66zi26VoTDv8yRgm0Fccecssto+MhsZ0D/DGW2sm8E8AjW7NU5VVTRt5GxbeZ5qBuJr+HyLYkjQ== -picocolors@^1.0.1: - version "1.0.1" - resolved "https://registry.yarnpkg.com/picocolors/-/picocolors-1.0.1.tgz#a8ad579b571952f0e5d25892de5445bcfe25aaa1" - 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version "6.0.0" - resolved "https://registry.yarnpkg.com/@docusaurus/react-loadable/-/react-loadable-6.0.0.tgz#de6c7f73c96542bd70786b8e522d535d69069dc4" - integrity sha512-YMMxTUQV/QFSnbgrP3tjDzLHRg7vsbMn8e9HAa8o/1iXoiomo48b7sk/kkmWEuWNDPJVlKSJRB6Y2fHqdJk+SQ== - dependencies: - "@types/react" "*" - react-router-config@^5.1.1: version "5.1.1" resolved "https://registry.yarnpkg.com/react-router-config/-/react-router-config-5.1.1.tgz#0f4263d1a80c6b2dc7b9c1902c9526478194a988" @@ -8355,7 +7310,7 @@ schema-utils@^3.0.0, schema-utils@^3.1.1, schema-utils@^3.2.0: ajv "^6.12.5" ajv-keywords "^3.5.2" -schema-utils@^4.0.0, schema-utils@^4.0.1: +schema-utils@^4.0.0: version "4.2.0" resolved "https://registry.yarnpkg.com/schema-utils/-/schema-utils-4.2.0.tgz#70d7c93e153a273a805801882ebd3bff20d89c8b" integrity sha512-L0jRsrPpjdckP3oPug3/VxNKt2trR8TcabrM6FOAAlvC/9Phcmm+cuAgTlxBqdBR1WJx7Naj9WHw+aOmheSVbw== @@ -8581,14 +7536,6 @@ slash@^4.0.0: resolved "https://registry.yarnpkg.com/slash/-/slash-4.0.0.tgz#2422372176c4c6c5addb5e2ada885af984b396a7" integrity sha512-3dOsAHXXUkQTpOYcoAxLIorMTp4gIQr5IW3iVb7A7lFIp0VHhnynm9izx6TssdrIcVIESAlVjtnO2K8bg+Coew== -snake-case@^3.0.4: - version "3.0.4" - resolved "https://registry.yarnpkg.com/snake-case/-/snake-case-3.0.4.tgz#4f2bbd568e9935abdfd593f34c691dadb49c452c" - integrity sha512-LAOh4z89bGQvl9pFfNF8V146i7o7/CqFPbqzYgP+yYzDIDeS9HaNFtXABamRW+AQzEVODcvE79ljJ+8a9YSdMg== - dependencies: - dot-case "^3.0.4" - tslib "^2.0.3" - sockjs@^0.3.24: version "0.3.24" resolved "https://registry.yarnpkg.com/sockjs/-/sockjs-0.3.24.tgz#c9bc8995f33a111bea0395ec30aa3206bdb5ccce" @@ -8598,15 +7545,10 @@ sockjs@^0.3.24: uuid "^8.3.2" websocket-driver "^0.7.4" -sort-css-media-queries@2.2.0: - version "2.2.0" - resolved "https://registry.yarnpkg.com/sort-css-media-queries/-/sort-css-media-queries-2.2.0.tgz#aa33cf4a08e0225059448b6c40eddbf9f1c8334c" - integrity sha512-0xtkGhWCC9MGt/EzgnvbbbKhqWjl1+/rncmhTh5qCpbYguXh6S/qwePfv/JQ8jePXXmqingylxoC49pCkSPIbA== - -source-map-js@^1.0.1, source-map-js@^1.2.0: - version "1.2.0" - resolved "https://registry.yarnpkg.com/source-map-js/-/source-map-js-1.2.0.tgz#16b809c162517b5b8c3e7dcd315a2a5c2612b2af" - integrity sha512-itJW8lvSA0TXEphiRoawsCksnlf8SyvmFzIhltqAHluXd88pkCd+cXJVHTDwdCr0IzwptSm035IHQktUu1QUMg== +sort-css-media-queries@2.1.0: + version "2.1.0" + resolved "https://registry.yarnpkg.com/sort-css-media-queries/-/sort-css-media-queries-2.1.0.tgz#7c85e06f79826baabb232f5560e9745d7a78c4ce" + integrity sha512-IeWvo8NkNiY2vVYdPa27MCQiR0MN0M80johAYFVxWWXQ44KU84WNxjslwBHmc/7ZL2ccwkM7/e6S5aiKZXm7jA== source-map-js@^1.0.2: version "1.0.2" @@ -8621,7 +7563,7 @@ source-map-support@~0.5.20: buffer-from "^1.0.0" source-map "^0.6.0" -source-map@^0.6.0, source-map@~0.6.0: +source-map@^0.6.0, source-map@^0.6.1, source-map@~0.6.0: version "0.6.1" resolved "https://registry.yarnpkg.com/source-map/-/source-map-0.6.1.tgz#74722af32e9614e9c287a8d0bbde48b5e2f1a263" integrity sha512-UjgapumWlbMhkBgzT7Ykc5YXUT46F0iKu8SGXq0bcwP5dz/h0Plj6enJqjz1Zbq2l5WaqYnrVbwWOWMyF3F47g== @@ -8669,6 +7611,11 @@ srcset@^4.0.0: resolved "https://registry.yarnpkg.com/srcset/-/srcset-4.0.0.tgz#336816b665b14cd013ba545b6fe62357f86e65f4" integrity sha512-wvLeHgcVHKO8Sc/H/5lkGreJQVeYMm9rlmt8PuR1xE31rIuXhuzznUUqAt8MqLhB3MqJdFzlNAfpcWnxiFUcPw== +stable@^0.1.8: + version "0.1.8" + resolved "https://registry.yarnpkg.com/stable/-/stable-0.1.8.tgz#836eb3c8382fe2936feaf544631017ce7d47a3cf" + integrity sha512-ji9qxRnOVfcuLDySj9qzhGSEFVobyt1kIOSkj1qZzYLzq7Tos/oUUWvotUPQLlrsidqsK6tBH89Bc9kL5zHA6w== + statuses@2.0.1: version "2.0.1" resolved "https://registry.yarnpkg.com/statuses/-/statuses-2.0.1.tgz#55cb000ccf1d48728bd23c685a063998cf1a1b63" @@ -8680,9 +7627,9 @@ statuses@2.0.1: integrity sha512-OpZ3zP+jT1PI7I8nemJX4AKmAX070ZkYPVWV/AaKTJl+tXCTGyVdC1a4SL8RUQYEwk/f34ZX8UTykN68FwrqAA== std-env@^3.0.1: - version "3.4.3" - resolved "https://registry.yarnpkg.com/std-env/-/std-env-3.4.3.tgz#326f11db518db751c83fd58574f449b7c3060910" - integrity sha512-f9aPhy8fYBuMN+sNfakZV18U39PbalgjXG3lLB9WkaYTxijru61wb57V9wxxNthXM5Sd88ETBWi29qLAsHO52Q== + version "3.6.0" + resolved "https://registry.yarnpkg.com/std-env/-/std-env-3.6.0.tgz#94807562bddc68fa90f2e02c5fd5b6865bb4e98e" + integrity sha512-aFZ19IgVmhdB2uX599ve2kE6BIE3YMnQ6Gp6BURhW/oIzpXGKr878TQfAQZn1+i0Flcc/UKUy1gOlcfaUBCryg== string-width@^4.1.0, string-width@^4.2.0: version "4.2.3" @@ -8774,13 +7721,20 @@ style-to-object@^0.4.0: dependencies: inline-style-parser "0.1.1" -stylehacks@^6.1.1: - version "6.1.1" - resolved "https://registry.yarnpkg.com/stylehacks/-/stylehacks-6.1.1.tgz#543f91c10d17d00a440430362d419f79c25545a6" - integrity sha512-gSTTEQ670cJNoaeIp9KX6lZmm8LJ3jPB5yJmX8Zq/wQxOsAFXV3qjWzHas3YYk1qesuVIyYWWUpZ0vSE/dTSGg== +style-to-object@^1.0.0: + version "1.0.5" + resolved "https://registry.yarnpkg.com/style-to-object/-/style-to-object-1.0.5.tgz#5e918349bc3a39eee3a804497d97fcbbf2f0d7c0" + integrity sha512-rDRwHtoDD3UMMrmZ6BzOW0naTjMsVZLIjsGleSKS/0Oz+cgCfAPRspaqJuE8rDzpKha/nEvnM0IF4seEAZUTKQ== + dependencies: + inline-style-parser "0.2.2" + +stylehacks@^5.1.1: + version "5.1.1" + resolved "https://registry.yarnpkg.com/stylehacks/-/stylehacks-5.1.1.tgz#7934a34eb59d7152149fa69d6e9e56f2fc34bcc9" + integrity sha512-sBpcd5Hx7G6seo7b1LkpttvTz7ikD0LlH5RmdcBNb6fFR0Fl7LQwHDFr300q4cwUqi+IYrFGmsIHieMBfnN/Bw== dependencies: - browserslist "^4.23.0" - postcss-selector-parser "^6.0.16" + browserslist "^4.21.4" + postcss-selector-parser "^6.0.4" supports-color@^5.3.0: version "5.5.0" @@ -8813,18 +7767,18 @@ svg-parser@^2.0.4: resolved "https://registry.yarnpkg.com/svg-parser/-/svg-parser-2.0.4.tgz#fdc2e29e13951736140b76cb122c8ee6630eb6b5" integrity sha512-e4hG1hRwoOdRb37cIMSgzNsxyzKfayW6VOflrwvR+/bzrkyxY/31WkbgnQpgtrNp1SdpJvpUAGTa/ZoiPNDuRQ== -svgo@^3.0.2, svgo@^3.2.0: - version "3.3.2" - resolved "https://registry.yarnpkg.com/svgo/-/svgo-3.3.2.tgz#ad58002652dffbb5986fc9716afe52d869ecbda8" - integrity sha512-OoohrmuUlBs8B8o6MB2Aevn+pRIH9zDALSR+6hhqVfa6fRwG/Qw9VUMSMW9VNg2CFc/MTIfabtdOVl9ODIJjpw== +svgo@^2.7.0, svgo@^2.8.0: + version "2.8.0" + resolved "https://registry.yarnpkg.com/svgo/-/svgo-2.8.0.tgz#4ff80cce6710dc2795f0c7c74101e6764cfccd24" + integrity sha512-+N/Q9kV1+F+UeWYoSiULYo4xYSDQlTgb+ayMobAXPwMnLvop7oxKMo9OzIrX5x3eS4L4f2UHhc9axXwY8DpChg== dependencies: "@trysound/sax" "0.2.0" commander "^7.2.0" - css-select "^5.1.0" - css-tree "^2.3.1" - css-what "^6.1.0" - csso "^5.0.5" + css-select "^4.1.3" + css-tree "^1.1.3" + csso "^4.2.0" picocolors "^1.0.0" + stable "^0.1.8" tapable@^1.0.0: version "1.1.3" @@ -8848,9 +7802,9 @@ terser-webpack-plugin@^5.3.7, terser-webpack-plugin@^5.3.9: terser "^5.16.8" terser@^5.10.0, terser@^5.15.1, terser@^5.16.8: - version "5.24.0" - resolved "https://registry.yarnpkg.com/terser/-/terser-5.24.0.tgz#4ae50302977bca4831ccc7b4fef63a3c04228364" - integrity sha512-ZpGR4Hy3+wBEzVEnHvstMvqpD/nABNelQn/z2r0fjVWGQsN3bpOLzQlqDxmb4CDZnXq5lpjnQ+mHQLAOpfM5iw== + version "5.26.0" + resolved "https://registry.yarnpkg.com/terser/-/terser-5.26.0.tgz#ee9f05d929f4189a9c28a0feb889d96d50126fe1" + integrity sha512-dytTGoE2oHgbNV9nTzgBEPaqAWvcJNl66VZ0BkJqlvp71IjO8CxdBx/ykCNb47cLnCmCvRZ6ZR0tLkqvZCdVBQ== dependencies: "@jridgewell/source-map" "^0.3.3" acorn "^8.8.2" @@ -9063,14 +8017,6 @@ update-browserslist-db@^1.0.13: escalade "^3.1.1" picocolors "^1.0.0" -update-browserslist-db@^1.1.0: - version "1.1.0" - resolved "https://registry.yarnpkg.com/update-browserslist-db/-/update-browserslist-db-1.1.0.tgz#7ca61c0d8650766090728046e416a8cde682859e" - integrity sha512-EdRAaAyk2cUE1wOf2DkEhzxqOQvFOoRJFNS6NeyJ01Gp2beMRpBAINjM2iDXE3KCuKhwnvHIQCJm6ThL2Z+HzQ== - dependencies: - escalade "^3.1.2" - picocolors "^1.0.1" - update-notifier@^6.0.2: version "6.0.2" resolved "https://registry.yarnpkg.com/update-notifier/-/update-notifier-6.0.2.tgz#a6990253dfe6d5a02bd04fbb6a61543f55026b60" @@ -9188,23 +8134,19 @@ web-namespaces@^2.0.0: integrity sha512-bKr1DkiNa2krS7qxNtdrtHAmzuYGFQLiQ13TsorsdT6ULTkPLKuu5+GsFpDlg6JFjUTwX2DyhMPG2be8uPrqsQ== webpack-bundle-analyzer@^4.9.0: - version "4.9.1" - resolved "https://registry.yarnpkg.com/webpack-bundle-analyzer/-/webpack-bundle-analyzer-4.9.1.tgz#d00bbf3f17500c10985084f22f1a2bf45cb2f09d" - integrity sha512-jnd6EoYrf9yMxCyYDPj8eutJvtjQNp8PHmni/e/ulydHBWhT5J3menXt3HEkScsu9YqMAcG4CfFjs3rj5pVU1w== + version "4.10.1" + resolved "https://registry.yarnpkg.com/webpack-bundle-analyzer/-/webpack-bundle-analyzer-4.10.1.tgz#84b7473b630a7b8c21c741f81d8fe4593208b454" + integrity sha512-s3P7pgexgT/HTUSYgxJyn28A+99mmLq4HsJepMPzu0R8ImJc52QNqaFYW1Z2z2uIb1/J3eYgaAWVpaC+v/1aAQ== dependencies: "@discoveryjs/json-ext" "0.5.7" acorn "^8.0.4" acorn-walk "^8.0.0" commander "^7.2.0" + debounce "^1.2.1" escape-string-regexp "^4.0.0" gzip-size "^6.0.0" + html-escaper "^2.0.2" is-plain-object "^5.0.0" - lodash.debounce "^4.0.8" - lodash.escape "^4.0.1" - lodash.flatten "^4.4.0" - lodash.invokemap "^4.6.0" - lodash.pullall "^4.2.0" - lodash.uniqby "^4.7.0" opener "^1.5.2" picocolors "^1.0.0" sirv "^2.0.3" @@ -9266,7 +8208,7 @@ webpack-merge@^5.9.0: flat "^5.0.2" wildcard "^2.0.0" -webpack-sources@^3.2.3: +webpack-sources@^3.2.2, webpack-sources@^3.2.3: version "3.2.3" resolved "https://registry.yarnpkg.com/webpack-sources/-/webpack-sources-3.2.3.tgz#2d4daab8451fd4b240cc27055ff6a0c2ccea0cde" integrity sha512-/DyMEOrDgLKKIG0fmvtz+4dUX/3Ghozwgm6iPp8KRhvn+eQf9+Q7GWxVNMk3+uCPWfdXYC4ExGBckIXdFEfH1w== @@ -9407,7 +8349,7 @@ yallist@^4.0.0: resolved "https://registry.yarnpkg.com/yallist/-/yallist-4.0.0.tgz#9bb92790d9c0effec63be73519e11a35019a3a72" integrity sha512-3wdGidZyq5PB084XLES5TpOSRA3wjXAlIWMhum2kRcv/41Sn2emQ0dycQW4uZXLejwKvg6EsvbdlVL+FYEct7A== -yaml@^1.7.2: +yaml@^1.10.0, yaml@^1.10.2, yaml@^1.7.2: version "1.10.2" resolved "https://registry.yarnpkg.com/yaml/-/yaml-1.10.2.tgz#2301c5ffbf12b467de8da2333a459e29e7920e4b" integrity sha512-r3vXyErRCYJ7wg28yvBY5VSoAF8ZvlcW9/BwUzEtUsjvX/DKs24dIkuwjtuprwJJHsbyUbLApepYTR1BN4uHrg== diff --git a/docs/en/_assets/commonMarkdown/loadMethodIntro.md b/docs/en/_assets/commonMarkdown/loadMethodIntro.md index dd5164ea9e8d7..1cdec09d07da4 100644 --- a/docs/en/_assets/commonMarkdown/loadMethodIntro.md +++ b/docs/en/_assets/commonMarkdown/loadMethodIntro.md @@ -7,6 +7,6 @@ Each of these options has its own advantages, which are detailed in the followin In most cases, we recommend that you use the INSERT+`FILES()` method, which is much easier to use. -However, the INSERT+`FILES()` method currently supports only the Parquet and ORC file formats. Therefore, if you need to load data of other file formats such as CSV, or [perform data changes such as DELETE during data loading](../../loading/Load_to_Primary_Key_tables.md), you can resort to Broker Load. +However, the INSERT+`FILES()` method currently supports only the Parquet and ORC file formats. Therefore, if you need to load data of other file formats such as CSV, or perform data changes such as DELETE during data loading, you can resort to Broker Load. If you need to load a large number of data files with a significant data volume in total (for example, more than 100 GB or even 1 TB), we recommend that you use the Pipe method. Pipe can split the files based on their number or size, breaking down the load job into smaller, sequential tasks. This approach ensures that errors in one file do not impact the entire load job and minimizes the need for retries due to data errors. diff --git a/docs/en/_assets/commonMarkdown/multi-service-access.mdx b/docs/en/_assets/commonMarkdown/multi-service-access.mdx new file mode 100644 index 0000000000000..a76bc56932fdf --- /dev/null +++ b/docs/en/_assets/commonMarkdown/multi-service-access.mdx @@ -0,0 +1 @@ +For the best practices of multi-service access control, see [Multi-service access control](../../administration/user_privs/User_privilege.md#multi-service-access-control). diff --git a/docs/en/_assets/commonMarkdown/quickstart-iceberg-tip.mdx b/docs/en/_assets/commonMarkdown/quickstart-iceberg-tip.mdx new file mode 100644 index 0000000000000..e32a3d871a85f --- /dev/null +++ b/docs/en/_assets/commonMarkdown/quickstart-iceberg-tip.mdx @@ -0,0 +1,5 @@ + +:::tip +This example uses the Local Climatological Data(LCD) dataset featured in the [StarRocks Basics](../../quick_start/shared-nothing.md) Quick Start. You can load the data and try the example yourself. +::: + diff --git a/docs/en/_assets/commonMarkdown/quickstart-overview-tip.mdx b/docs/en/_assets/commonMarkdown/quickstart-overview-tip.mdx new file mode 100644 index 0000000000000..a2618790f9d25 --- /dev/null +++ b/docs/en/_assets/commonMarkdown/quickstart-overview-tip.mdx @@ -0,0 +1,3 @@ +## Learn by doing + +Try the [Quick Starts](../../quick_start/quick_start.mdx) to get an overview of using StarRocks with realistic scenarios. diff --git a/docs/en/_assets/commonMarkdown/quickstart-routine-load-tip.mdx b/docs/en/_assets/commonMarkdown/quickstart-routine-load-tip.mdx new file mode 100644 index 0000000000000..8abc4a00b6e49 --- /dev/null +++ b/docs/en/_assets/commonMarkdown/quickstart-routine-load-tip.mdx @@ -0,0 +1,5 @@ + +:::tip +Try Routine Load out in this [Quick Start](../../quick_start/routine-load.md) +::: + diff --git a/docs/en/_assets/commonMarkdown/quickstart-shared-data.mdx b/docs/en/_assets/commonMarkdown/quickstart-shared-data.mdx new file mode 100644 index 0000000000000..dc5a34a47c1c4 --- /dev/null +++ b/docs/en/_assets/commonMarkdown/quickstart-shared-data.mdx @@ -0,0 +1,5 @@ + +:::tip +Give [shared-data](../../quick_start/shared-data.md) a try using MinIO for object storage. +::: + diff --git a/docs/en/_assets/commonMarkdown/quickstart-shared-nothing-tip.mdx b/docs/en/_assets/commonMarkdown/quickstart-shared-nothing-tip.mdx new file mode 100644 index 0000000000000..e32a3d871a85f --- /dev/null +++ b/docs/en/_assets/commonMarkdown/quickstart-shared-nothing-tip.mdx @@ -0,0 +1,5 @@ + +:::tip +This example uses the Local Climatological Data(LCD) dataset featured in the [StarRocks Basics](../../quick_start/shared-nothing.md) Quick Start. You can load the data and try the example yourself. +::: + diff --git a/docs/en/administration/management/Backup_and_restore.md b/docs/en/administration/management/Backup_and_restore.md index 13fc0915a6bfa..102a9d49836c4 100644 --- a/docs/en/administration/management/Backup_and_restore.md +++ b/docs/en/administration/management/Backup_and_restore.md @@ -22,7 +22,7 @@ StarRocks supports the following remote storage systems: StarRocks supports FULL backup on the granularity level of database, table, or partition. -If you have stored a large amount of data in a table, we recommend that you back up and restore data by partition. This way, you can reduce the cost of retries in case of job failures. If you need to back up incremental data on a regular basis, you can strategize a [dynamic partitioning](../../table_design/dynamic_partitioning.md) plan (by a certain time interval, for example) for your table, and back up only new partitions each time. +If you have stored a large amount of data in a table, we recommend that you back up and restore data by partition. This way, you can reduce the cost of retries in case of job failures. If you need to back up incremental data on a regular basis, you can strategize a [dynamic partitioning](../../table_design/data_distribution/dynamic_partitioning.md) plan (by a certain time interval, for example) for your table, and back up only new partitions each time. ### Create a repository diff --git a/docs/en/administration/management/resource_management/Blacklist.md b/docs/en/administration/management/resource_management/Blacklist.md index 94b287323bbed..75f2808cafcbe 100644 --- a/docs/en/administration/management/resource_management/Blacklist.md +++ b/docs/en/administration/management/resource_management/Blacklist.md @@ -1,5 +1,6 @@ --- displayed_sidebar: docs +sidebar_position: 80 --- # Blacklist Management diff --git a/docs/en/administration/management/resource_management/Load_balance.md b/docs/en/administration/management/resource_management/Load_balance.md index f89954c208057..c5dc13084425e 100644 --- a/docs/en/administration/management/resource_management/Load_balance.md +++ b/docs/en/administration/management/resource_management/Load_balance.md @@ -1,5 +1,6 @@ --- displayed_sidebar: docs +sidebar_position: 60 --- # Load Balancing diff --git a/docs/en/administration/management/resource_management/Memory_management.md b/docs/en/administration/management/resource_management/Memory_management.md index 919a1c23a08f5..b109b46cab98f 100644 --- a/docs/en/administration/management/resource_management/Memory_management.md +++ b/docs/en/administration/management/resource_management/Memory_management.md @@ -1,5 +1,6 @@ --- displayed_sidebar: docs +sidebar_position: 40 --- # Memory Management diff --git a/docs/en/administration/management/resource_management/Query_management.md b/docs/en/administration/management/resource_management/Query_management.md index 3f93f0eeb89ed..f71c6606db4c8 100644 --- a/docs/en/administration/management/resource_management/Query_management.md +++ b/docs/en/administration/management/resource_management/Query_management.md @@ -1,5 +1,6 @@ --- displayed_sidebar: docs +sidebar_position: 30 --- # Query Management diff --git a/docs/en/administration/management/resource_management/Replica.md b/docs/en/administration/management/resource_management/Replica.md index 1597e1fade556..9daccfb352a7f 100644 --- a/docs/en/administration/management/resource_management/Replica.md +++ b/docs/en/administration/management/resource_management/Replica.md @@ -1,5 +1,6 @@ --- displayed_sidebar: docs +sidebar_position: 70 --- # Replica management diff --git a/docs/en/administration/management/resource_management/be_label.md b/docs/en/administration/management/resource_management/be_label.md index 920deb6da6245..d44e3e25679f7 100644 --- a/docs/en/administration/management/resource_management/be_label.md +++ b/docs/en/administration/management/resource_management/be_label.md @@ -1,5 +1,6 @@ --- displayed_sidebar: docs +sidebar_position: 80 --- # Add labels on BEs diff --git a/docs/en/administration/management/resource_management/filemanager.md b/docs/en/administration/management/resource_management/filemanager.md index fdd37b11e49d9..7ba94f9ad8c6f 100644 --- a/docs/en/administration/management/resource_management/filemanager.md +++ b/docs/en/administration/management/resource_management/filemanager.md @@ -1,5 +1,6 @@ --- displayed_sidebar: docs +sidebar_position: 90 --- # File manager diff --git a/docs/en/administration/management/resource_management/query_queues.md b/docs/en/administration/management/resource_management/query_queues.md index 9aa1644c14854..9c9580c59acf9 100644 --- a/docs/en/administration/management/resource_management/query_queues.md +++ b/docs/en/administration/management/resource_management/query_queues.md @@ -1,5 +1,6 @@ --- displayed_sidebar: docs +sidebar_position: 20 --- # Query queues diff --git a/docs/en/administration/management/resource_management/resource_group.md b/docs/en/administration/management/resource_management/resource_group.md index 17f2606d07893..cd09ceb40709a 100644 --- a/docs/en/administration/management/resource_management/resource_group.md +++ b/docs/en/administration/management/resource_management/resource_group.md @@ -1,5 +1,6 @@ --- displayed_sidebar: docs +sidebar_position: 10 --- # Resource group @@ -60,7 +61,7 @@ You can specify CPU and memory resource quotas for a resource group on a BE by u > **NOTE** > - > The amount of memory that can be used for queries is indicated by the `query_pool` parameter. For more information about the parameter, see [Memory management](Memory_management.md). + > The amount of memory that can be used for queries is indicated by the `query_pool` parameter. - `concurrency_limit` @@ -68,7 +69,7 @@ You can specify CPU and memory resource quotas for a resource group on a BE by u - `max_cpu_cores` - The CPU core threshold for triggering query queue in FE. For more details, refer to [Query queues - Specify resource thresholds for resource group-level query queues](./query_queues.md#specify-resource-thresholds-for-resource-group-level-query-queues). It takes effect only when it is set to greater than `0`. Range: [0, `avg_be_cpu_cores`], where `avg_be_cpu_cores` represents the average number of CPU cores across all BE nodes. Default: 0. + The CPU core threshold for triggering query queue in FE. This only takes effect when it is set to greater than `0`. Range: [0, `avg_be_cpu_cores`], where `avg_be_cpu_cores` represents the average number of CPU cores across all BE nodes. Default: 0. - `spill_mem_limit_threshold` @@ -360,9 +361,9 @@ The following FE metrics only provide statistics within the current FE node: | starrocks_fe_query_resource_group | Count | Instantaneous | The number of queries historically run in this resource group (including those currently running). | | starrocks_fe_query_resource_group_latency | ms | Instantaneous | The query latency percentile for this resource group. The label `type` indicates specific percentiles, including `mean`, `75_quantile`, `95_quantile`, `98_quantile`, `99_quantile`, `999_quantile`. | | starrocks_fe_query_resource_group_err | Count | Instantaneous | The number of queries in this resource group that encountered an error. | -| starrocks_fe_resource_group_query_queue_total | Count | Instantaneous | The total number of queries historically queued in this resource group (including those currently running). This metric is supported from v3.1.4 onwards. It is valid only when query queues are enabled, see [Query Queues](query_queues.md) for details. | -| starrocks_fe_resource_group_query_queue_pending | Count | Instantaneous | The number of queries currently in the queue of this resource group. This metric is supported from v3.1.4 onwards. It is valid only when query queues are enabled, see [Query Queues](query_queues.md) for details. | -| starrocks_fe_resource_group_query_queue_timeout | Count | Instantaneous | The number of queries in this resource group that have timed out while in the queue. This metric is supported from v3.1.4 onwards. It is valid only when query queues are enabled, see [Query Queues](query_queues.md) for details. | +| starrocks_fe_resource_group_query_queue_total | Count | Instantaneous | The total number of queries historically queued in this resource group (including those currently running). This metric is supported from v3.1.4 onwards. It is valid only when query queues are enabled. | +| starrocks_fe_resource_group_query_queue_pending | Count | Instantaneous | The number of queries currently in the queue of this resource group. This metric is supported from v3.1.4 onwards. It is valid only when query queues are enabled. | +| starrocks_fe_resource_group_query_queue_timeout | Count | Instantaneous | The number of queries in this resource group that have timed out while in the queue. This metric is supported from v3.1.4 onwards. It is valid only when query queues are enabled. | ### BE metrics @@ -412,11 +413,3 @@ MySQL [(none)]> SHOW USAGE RESOURCE GROUPS; | wg2 | 0 | 127.0.0.1 | 0.400 | 4 | 8 | +------------+----+-----------+-----------------+-----------------+------------------+ ``` - -## What to do next - -After you configure resource groups, you can manage memory resources and queries. For more information, see the following topics: - -- [Memory management](./Memory_management.md) - -- [Query management](./Query_management.md) diff --git a/docs/en/administration/management/resource_management/spill_to_disk.md b/docs/en/administration/management/resource_management/spill_to_disk.md index e51a984931349..10711586056cd 100644 --- a/docs/en/administration/management/resource_management/spill_to_disk.md +++ b/docs/en/administration/management/resource_management/spill_to_disk.md @@ -1,5 +1,6 @@ --- displayed_sidebar: docs +sidebar_position: 50 --- # Spill to disk diff --git a/docs/en/data_source/catalog/iceberg_catalog.md b/docs/en/data_source/catalog/iceberg_catalog.md index b0a8bc76c1457..7494d5e77fb04 100644 --- a/docs/en/data_source/catalog/iceberg_catalog.md +++ b/docs/en/data_source/catalog/iceberg_catalog.md @@ -4,12 +4,11 @@ toc_max_heading_level: 5 --- import Tabs from '@theme/Tabs'; import TabItem from '@theme/TabItem'; +import QSTip from '../../_assets/commonMarkdown/quickstart-iceberg-tip.mdx' # Iceberg catalog -:::tip -Try it in this [hands-on tutorial](../../quick_start/iceberg.md) -::: + An Iceberg catalog is a type of external catalog that is supported by StarRocks from v2.4 onwards. With Iceberg catalogs, you can: diff --git a/docs/en/deployment/post_deployment_setup.md b/docs/en/deployment/post_deployment_setup.md index f5b85773fdb85..3bebabdf24969 100644 --- a/docs/en/deployment/post_deployment_setup.md +++ b/docs/en/deployment/post_deployment_setup.md @@ -90,4 +90,4 @@ SET PROPERTY FOR '' 'max_user_connections' = '1000'; ## What to do next -After deploying and setting up your StarRocks cluster, you can then proceed to design tables that best work for your scenarios. See [Understand StarRocks table design](../table_design/Table_design.md) for detailed instructions on designing a table. +After deploying and setting up your StarRocks cluster, you can then proceed to design tables that best work for your scenarios. See [Understand StarRocks table design](../table_design/table_design.md) for detailed instructions on designing a table. diff --git a/docs/en/introduction/Architecture.md b/docs/en/introduction/Architecture.md index ad5e22424b4d3..b1b1f6a36fde3 100644 --- a/docs/en/introduction/Architecture.md +++ b/docs/en/introduction/Architecture.md @@ -1,6 +1,7 @@ --- displayed_sidebar: docs --- +import QSOverview from '../_assets/commonMarkdown/quickstart-overview-tip.mdx' # Architecture @@ -79,7 +80,4 @@ Queries against hot data scan the cache directly and then the local disk, while Caching can be enabled when creating tables. If caching is enabled, data will be written to both the local disk and backend object storage. During queries, the CN nodes first read data from the local disk. If the data is not found, it will be retrieved from the backend object storage and simultaneously cached on the local disk. -## Learn by doing - -- Give [shared-data](../quick_start/shared-data.md) a try using MinIO for object storage. -- Kubernetes users can use the [Helm quick start](../quick_start/helm.md) and deploy three FEs and three BEs in a shared-nothing architecture using persistent volumes. \ No newline at end of file + diff --git a/docs/en/loading/BrokerLoad.md b/docs/en/loading/BrokerLoad.md index a25d0b1ed5bb2..5298c64eb6ede 100644 --- a/docs/en/loading/BrokerLoad.md +++ b/docs/en/loading/BrokerLoad.md @@ -94,7 +94,7 @@ Note that in StarRocks some literals are used as reserved keywords by the SQL la > **NOTE** > - > Since v2.5.7, StarRocks can automatically set the number of buckets (BUCKETS) when you create a table or add a partition. You no longer need to manually set the number of buckets. For detailed information, see [set the number of buckets](../table_design/Data_distribution.md#set-the-number-of-buckets). + > Since v2.5.7, StarRocks can automatically set the number of buckets (BUCKETS) when you create a table or add a partition. You no longer need to manually set the number of buckets. For detailed information, see [set the number of buckets](../table_design/data_distribution/Data_distribution.md#set-the-number-of-buckets). a. Create a Primary Key table named `table1`. The table consists of three columns: `id`, `name`, and `score`, of which `id` is the primary key. diff --git a/docs/en/loading/Etl_in_loading.md b/docs/en/loading/Etl_in_loading.md index 15cdf9cdc47be..aea539cdd4304 100644 --- a/docs/en/loading/Etl_in_loading.md +++ b/docs/en/loading/Etl_in_loading.md @@ -74,7 +74,7 @@ If you choose [Routine Load](./RoutineLoad.md), make sure that topics are create > **NOTE** > - > Since v2.5.7, StarRocks can automatically set the number of buckets (BUCKETS) when you create a table or add a partition. You no longer need to manually set the number of buckets. For detailed information, see [set the number of buckets](../table_design/Data_distribution.md#set-the-number-of-buckets). + > Since v2.5.7, StarRocks can automatically set the number of buckets (BUCKETS) when you create a table or add a partition. You no longer need to manually set the number of buckets. For detailed information, see [set the number of buckets](../table_design/data_distribution/Data_distribution.md#set-the-number-of-buckets). a. Create a table named `table1`, which consists of three columns: `event_date`, `event_type`, and `user_id`. diff --git a/docs/en/loading/Flink_cdc_load.md b/docs/en/loading/Flink_cdc_load.md index 8da8eeca37e2f..e7257f47766a9 100644 --- a/docs/en/loading/Flink_cdc_load.md +++ b/docs/en/loading/Flink_cdc_load.md @@ -286,7 +286,7 @@ To synchronize data from MySQL in real time, the system needs to read data from > **NOTICE** > - > Since v2.5.7, StarRocks can automatically set the number of buckets (BUCKETS) when you create a table or add a partition. You no longer need to manually set the number of buckets. For detailed information, see [set the number of buckets](../table_design/Data_distribution.md#set-the-number-of-buckets). + > Since v2.5.7, StarRocks can automatically set the number of buckets (BUCKETS) when you create a table or add a partition. You no longer need to manually set the number of buckets. For detailed information, see [set the number of buckets](../table_design/data_distribution/Data_distribution.md#set-the-number-of-buckets). ## Synchronize data diff --git a/docs/en/loading/InsertInto.md b/docs/en/loading/InsertInto.md index d354e1059d9a2..f646e7f6c1420 100644 --- a/docs/en/loading/InsertInto.md +++ b/docs/en/loading/InsertInto.md @@ -25,7 +25,7 @@ StarRocks v2.4 further supports overwriting data into a table by using INSERT OV - You can cancel a synchronous INSERT transaction only by pressing the **Ctrl** and **C** keys from your MySQL client. - You can submit an asynchronous INSERT task using [SUBMIT TASK](../sql-reference/sql-statements/loading_unloading/ETL/SUBMIT_TASK.md). - As for the current version of StarRocks, the INSERT transaction fails by default if the data of any rows does not comply with the schema of the table. For example, the INSERT transaction fails if the length of a field in any row exceeds the length limit for the mapping field in the table. You can set the session variable `enable_insert_strict` to `false` to allow the transaction to continue by filtering out the rows that mismatch the table. -- If you execute the INSERT statement frequently to load small batches of data into StarRocks, excessive data versions are generated. It severely affects query performance. We recommend that, in production, you should not load data with the INSERT command too often or use it as a routine for data loading on a daily basis. If your application or analytic scenario demand solutions to loading streaming data or small data batches separately, we recommend you use Apache Kafka® as your data source and load the data via [Routine Load](../loading/RoutineLoad.md). +- If you execute the INSERT statement frequently to load small batches of data into StarRocks, excessive data versions are generated. It severely affects query performance. We recommend that, in production, you should not load data with the INSERT command too often or use it as a routine for data loading on a daily basis. If your application or analytic scenario demand solutions to loading streaming data or small data batches separately, we recommend you use Apache Kafka® as your data source and load the data via Routine Load. - If you execute the INSERT OVERWRITE statement, StarRocks creates temporary partitions for the partitions which store the original data, inserts new data into the temporary partitions, and [swaps the original partitions with the temporary partitions](../sql-reference/sql-statements/table_bucket_part_index/ALTER_TABLE.md#use-a-temporary-partition-to-replace-current-partition). All these operations are executed in the FE Leader node. Hence, if the FE Leader node crashes while executing INSERT OVERWRITE command, the whole load transaction will fail, and the temporary partitions will be truncated. ## Preparation @@ -111,7 +111,7 @@ DISTRIBUTED BY HASH(user); > **NOTICE** > -> Since v2.5.7, StarRocks can automatically set the number of buckets (BUCKETS) when you create a table or add a partition. You no longer need to manually set the number of buckets. For detailed information, see [set the number of buckets](../table_design/Data_distribution.md#set-the-number-of-buckets). +> Since v2.5.7, StarRocks can automatically set the number of buckets (BUCKETS) when you create a table or add a partition. You no longer need to manually set the number of buckets. For detailed information, see [set the number of buckets](../table_design/data_distribution/Data_distribution.md#set-the-number-of-buckets). ## Insert data via INSERT INTO VALUES diff --git a/docs/en/loading/Load_to_Primary_Key_tables.md b/docs/en/loading/Load_to_Primary_Key_tables.md index d6e390b0dc2f3..daeea2be8340b 100644 --- a/docs/en/loading/Load_to_Primary_Key_tables.md +++ b/docs/en/loading/Load_to_Primary_Key_tables.md @@ -107,7 +107,7 @@ If the data file you want to load involves only UPSERT operations, you do not ne > **NOTE** > - > Since v2.5.7, StarRocks can automatically set the number of buckets (BUCKETS) when you create a table or add a partition. You no longer need to manually set the number of buckets. For detailed information, see [set the number of buckets](../table_design/Data_distribution.md#set-the-number-of-buckets). + > Since v2.5.7, StarRocks can automatically set the number of buckets (BUCKETS) when you create a table or add a partition. You no longer need to manually set the number of buckets. For detailed information, see [set the number of buckets](../table_design/data_distribution/Data_distribution.md#set-the-number-of-buckets). b. Insert a record into `table1`. @@ -269,7 +269,7 @@ If the data file you want to load involves only DELETE operations, you must add > **NOTE** > - > Since v2.5.7, StarRocks can automatically set the number of buckets (BUCKETS) when you create a table or add a partition. You no longer need to manually set the number of buckets. For detailed information, see [set the number of buckets](../table_design/Data_distribution.md#set-the-number-of-buckets). + > Since v2.5.7, StarRocks can automatically set the number of buckets (BUCKETS) when you create a table or add a partition. You no longer need to manually set the number of buckets. For detailed information, see [set the number of buckets](../table_design/data_distribution/Data_distribution.md#set-the-number-of-buckets). b. Insert two records into `table2`. @@ -381,7 +381,7 @@ If the data file you want to load involves both UPSERT and DELETE operations, yo > **NOTE** > - > Since v2.5.7, StarRocks can automatically set the number of buckets (BUCKETS) when you create a table or add a partition. You no longer need to manually set the number of buckets. For detailed information, see [set the number of buckets](../table_design/Data_distribution.md#set-the-number-of-buckets). + > Since v2.5.7, StarRocks can automatically set the number of buckets (BUCKETS) when you create a table or add a partition. You no longer need to manually set the number of buckets. For detailed information, see [set the number of buckets](../table_design/data_distribution/Data_distribution.md#set-the-number-of-buckets). b. Insert two records into `table3`. @@ -505,7 +505,7 @@ This section uses CSV as an example to describe how to perform partial updates. > **NOTE** > - > Since v2.5.7, StarRocks can automatically set the number of buckets (BUCKETS) when you create a table or add a partition. You no longer need to manually set the number of buckets. For detailed information, see [set the number of buckets](../table_design/Data_distribution.md#set-the-number-of-buckets). + > Since v2.5.7, StarRocks can automatically set the number of buckets (BUCKETS) when you create a table or add a partition. You no longer need to manually set the number of buckets. For detailed information, see [set the number of buckets](../table_design/data_distribution/Data_distribution.md#set-the-number-of-buckets). b. Insert a record into `table4`. @@ -638,7 +638,7 @@ The conditional update feature is designed to resolve data disorder. If the sour > **NOTE** > - > Since v2.5.7, StarRocks can automatically set the number of buckets (BUCKETS) when you create a table or add a partition. You no longer need to manually set the number of buckets. For detailed information, see [set the number of buckets](../table_design/Data_distribution.md#set-the-number-of-buckets). + > Since v2.5.7, StarRocks can automatically set the number of buckets (BUCKETS) when you create a table or add a partition. You no longer need to manually set the number of buckets. For detailed information, see [set the number of buckets](../table_design/data_distribution/Data_distribution.md#set-the-number-of-buckets). b. Insert a record into `table5`. diff --git a/docs/en/loading/RoutineLoad.md b/docs/en/loading/RoutineLoad.md index e86f81f09f02d..8e16895d070e1 100644 --- a/docs/en/loading/RoutineLoad.md +++ b/docs/en/loading/RoutineLoad.md @@ -5,10 +5,9 @@ displayed_sidebar: docs # Load data using Routine Load import InsertPrivNote from '../_assets/commonMarkdown/insertPrivNote.md' +import QSTip from '../_assets/commonMarkdown/quickstart-routine-load-tip.mdx' -:::tip -Try Routine Load out in this [Quick Start](../quick_start/routine-load.md) -::: + This topic introduces how to create a Routine Load job to stream Kafka messages (events) into StarRocks, and familiarizes you with some basic concepts about Routine Load. @@ -115,7 +114,7 @@ DISTRIBUTED BY HASH(`order_id`); > **NOTICE** > -> Since v2.5.7, StarRocks can automatically set the number of buckets (BUCKETS) when you create a table or add a partition. You no longer need to manually set the number of buckets. For detailed information, see [set the number of buckets](../table_design/Data_distribution.md#set-the-number-of-buckets). +> Since v2.5.7, StarRocks can automatically set the number of buckets (BUCKETS) when you create a table or add a partition. You no longer need to manually set the number of buckets. For detailed information, see [set the number of buckets](../table_design/data_distribution/Data_distribution.md#set-the-number-of-buckets). #### Submit a Routine Load job @@ -196,7 +195,7 @@ After submitting the load job, you can execute the [SHOW ROUTINE LOAD](../sql-re In the example, the number of BE nodes that are alive is `5`, the number of the pre-specified Kafka topic partitions is `5`, and the value of `max_routine_load_task_concurrent_num` is `5`. To increase the actual load task concurrency, you can increase the `desired_concurrent_number` from the default value `3` to `5`. - For more about the properties, see [CREATE ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md). For detailed instructions on accelerating the loading, see [Routine Load FAQ](../faq/loading/Routine_load_faq.md). + For more about the properties, see [CREATE ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md). ### Load JSON-format data @@ -234,7 +233,7 @@ DISTRIBUTED BY HASH(`commodity_id`); > **NOTICE** > -> Since v2.5.7, StarRocks can automatically set the number of buckets (BUCKETS) when you create a table or add a partition. You no longer need to manually set the number of buckets. For detailed information, see [set the number of buckets](../table_design/Data_distribution.md#set-the-number-of-buckets). +> Since v2.5.7, StarRocks can automatically set the number of buckets (BUCKETS) when you create a table or add a partition. You no longer need to manually set the number of buckets. For detailed information, see [set the number of buckets](../table_design/data_distribution/Data_distribution.md#set-the-number-of-buckets). #### Submit a Routine Load job @@ -339,7 +338,7 @@ DISTRIBUTED BY HASH(`id`); > **NOTICE** > -> Since v2.5.7, StarRocks can automatically set the number of buckets (BUCKETS) when you create a table or add a partition. You no longer need to manually set the number of buckets. For detailed information, see [set the number of buckets](../table_design/Data_distribution.md#set-the-number-of-buckets). +> Since v2.5.7, StarRocks can automatically set the number of buckets (BUCKETS) when you create a table or add a partition. You no longer need to manually set the number of buckets. For detailed information, see [set the number of buckets](../table_design/data_distribution/Data_distribution.md#set-the-number-of-buckets). #### Submit a Routine Load job @@ -551,7 +550,3 @@ The following example stops the load job `example_tbl2_ordertest2`: ```SQL STOP ROUTINE LOAD FOR example_tbl2_ordertest2; ``` - -## FAQ - -Please see [Routine Load FAQ](../faq/loading/Routine_load_faq.md). diff --git a/docs/en/loading/StreamLoad.md b/docs/en/loading/StreamLoad.md index 86dc3e736414f..3cf3e02e6bf70 100644 --- a/docs/en/loading/StreamLoad.md +++ b/docs/en/loading/StreamLoad.md @@ -106,7 +106,7 @@ DISTRIBUTED BY HASH(`id`); :::note -Since v2.5.7, StarRocks can automatically set the number of buckets (BUCKETS) when you create a table or add a partition. You no longer need to manually set the number of buckets. For detailed information, see [set the number of buckets](../table_design/Data_distribution.md#set-the-number-of-buckets). +Since v2.5.7, StarRocks can automatically set the number of buckets (BUCKETS) when you create a table or add a partition. You no longer need to manually set the number of buckets. For detailed information, see [set the number of buckets](../table_design/data_distribution/Data_distribution.md#set-the-number-of-buckets). ::: @@ -183,7 +183,7 @@ DISTRIBUTED BY HASH(`id`); :::note -Since v2.5.7, StarRocks can set the number of(BUCKETS) automatically when you create a table or add a partition. You no longer need to manually set the number of buckets. For detailed information, see [set the number of buckets](../table_design/Data_distribution.md#set-the-number-of-buckets). +Since v2.5.7, StarRocks can set the number of(BUCKETS) automatically when you create a table or add a partition. You no longer need to manually set the number of buckets. For detailed information, see [set the number of buckets](../table_design/data_distribution/Data_distribution.md#set-the-number-of-buckets). ::: diff --git a/docs/en/release_notes/release-2.4.md b/docs/en/release_notes/release-2.4.md index 5e3f248597d13..9b3bdabf3f2d3 100644 --- a/docs/en/release_notes/release-2.4.md +++ b/docs/en/release_notes/release-2.4.md @@ -219,7 +219,7 @@ Release date: October 20, 2022 - Histograms are added to CBO statistics. Full statistics collection is further optimized. For more information, see [Gather CBO statistics](../using_starrocks/Cost_based_optimizer.md). -- Adaptive multi-threading is enabled for tablet scanning to reduce the dependency of scanning performance on the tablet number. As a result, you can set the number of buckets more easily. For more information, see [Determine the number of buckets](../table_design/Data_distribution.md#how-to-determine-the-number-of-buckets). +- Adaptive multi-threading is enabled for tablet scanning to reduce the dependency of scanning performance on the tablet number. As a result, you can set the number of buckets more easily. For more information, see [Determine the number of buckets](../table_design/data_distribution/Data_distribution.md#how-to-determine-the-number-of-buckets). - Supports querying compressed TXT files in Apache Hive. diff --git a/docs/en/sql-reference/data-types/semi_structured/Array.md b/docs/en/sql-reference/data-types/semi_structured/Array.md index e44378b3a6646..b66e64e617d97 100644 --- a/docs/en/sql-reference/data-types/semi_structured/Array.md +++ b/docs/en/sql-reference/data-types/semi_structured/Array.md @@ -201,7 +201,7 @@ INSERT INTO t0 VALUES(1, [1,2,3]); ### Use Stream Load or Routine Load to load CSV-formatted arrays - Arrays in CSV files are separated with comma by default. You can use [Stream Load](../../../loading/StreamLoad.md#load-csv-data) or [Routine Load](../../../loading/RoutineLoad.md#load-csv-format-data) to load CSV text files or CSV data in Kafka. + Arrays in CSV files are separated with comma by default. You can use [Stream Load or Routine Load](../../../loading/loading_introduction/Loading_intro.md) to load CSV text files or CSV data in Kafka. ## Query ARRAY data diff --git a/docs/en/sql-reference/data-types/semi_structured/JSON.md b/docs/en/sql-reference/data-types/semi_structured/JSON.md index defb82033918a..84ee1b72707ba 100644 --- a/docs/en/sql-reference/data-types/semi_structured/JSON.md +++ b/docs/en/sql-reference/data-types/semi_structured/JSON.md @@ -69,7 +69,7 @@ StarRocks supports the following data type conversions at Parquet file loading. | LIST | ARRAY | | Other data types such as UNION and TIMESTAMP | Not supported | -- Method 4: Use [Routine](../../../loading/RoutineLoad.md) load to continuously load JSON data from Kafka into StarRocks. +- Method 4: Use [Routine](../../../loading/loading_introduction/Loading_intro.md) load to continuously load JSON data from Kafka into StarRocks. ### Query and process JSON data diff --git a/docs/en/sql-reference/information_schema/loads.md b/docs/en/sql-reference/information_schema/loads.md index d2886387d9604..a92d833e9f711 100644 --- a/docs/en/sql-reference/information_schema/loads.md +++ b/docs/en/sql-reference/information_schema/loads.md @@ -13,7 +13,7 @@ The following fields are provided in `loads`: | JOB_ID | The unique ID assigned by StarRocks to identify the load job. | | LABEL | The label of the load job. | | DATABASE_NAME | The name of the database to which the destination StarRocks tables belong. | -| STATE | The state of the load job. Valid values:
  • `PENDING`: The load job is created.
  • `QUEUEING`: The load job is in the queue waiting to be scheduled.
  • `LOADING`: The load job is running.
  • `PREPARED`: The transaction has been committed.
  • `FINISHED`: The load job succeeded.
  • `CANCELLED`: The load job failed.
For more information, see the "Asynchronous loading" section in [Loading concepts](../../loading/loading_introduction/loading_concepts.md#asynchronous-loading). | +| STATE | The state of the load job. Valid values:
  • `PENDING`: The load job is created.
  • `QUEUEING`: The load job is in the queue waiting to be scheduled.
  • `LOADING`: The load job is running.
  • `PREPARED`: The transaction has been committed.
  • `FINISHED`: The load job succeeded.
  • `CANCELLED`: The load job failed.
| | PROGRESS | The progress of the ETL stage and LOADING stage of the load job. | | TYPE | The type of the load job. For Broker Load, the return value is `BROKER`. For INSERT, the return value is `INSERT`. | | PRIORITY | The priority of the load job. Valid values: `HIGHEST`, `HIGH`, `NORMAL`, `LOW`, and `LOWEST`. | diff --git a/docs/en/sql-reference/sql-functions/like-predicate-functions/regexp_extract.md b/docs/en/sql-reference/sql-functions/like-predicate-functions/regexp_extract.md index 2e3259cce229b..dc2b47a37b965 100644 --- a/docs/en/sql-reference/sql-functions/like-predicate-functions/regexp_extract.md +++ b/docs/en/sql-reference/sql-functions/like-predicate-functions/regexp_extract.md @@ -2,6 +2,8 @@ displayed_sidebar: docs --- +import Tip from '../../../_assets/commonMarkdown/quickstart-shared-nothing-tip.mdx'; + # regexp_extract ## Description @@ -16,9 +18,7 @@ VARCHAR regexp_extract(VARCHAR str, VARCHAR pattern, int pos) ## Examples -:::tip -This example uses the Local Climatological Data(LCD) dataset featured in the [StarRocks Basics](../../../quick_start/shared-nothing.md) Quick Start. You can load the data and try the example yourself. -::: + Given this data: diff --git a/docs/en/sql-reference/sql-functions/table-functions/files.md b/docs/en/sql-reference/sql-functions/table-functions/files.md index d378e2ac44f73..f8e302bb094fc 100644 --- a/docs/en/sql-reference/sql-functions/table-functions/files.md +++ b/docs/en/sql-reference/sql-functions/table-functions/files.md @@ -10,7 +10,7 @@ Defines data files in remote storage. From v3.1.0 onwards, StarRocks supports defining read-only files in remote storage using the table function FILES(). It can access remote storage with the path-related properties of the files, infers the table schema of the data in the files, and returns the data rows. You can directly query the data rows using [SELECT](../../sql-statements/table_bucket_part_index/SELECT.md), load the data rows into an existing table using [INSERT](../../sql-statements/loading_unloading/INSERT.md), or create a new table and load the data rows into it using [CREATE TABLE AS SELECT](../../sql-statements/table_bucket_part_index/CREATE_TABLE_AS_SELECT.md). -From v3.2.0 onwards, FILES() supports writing data into files in remote storage. You can [use INSERT INTO FILES() to unload data from StarRocks to remote storage](../../../unloading/unload_using_insert_into_files.md). +From v3.2.0 onwards, FILES() supports writing data into files in remote storage. You can use INSERT INTO FILES() to unload data from StarRocks to remote storage. Currently, the FILES() function supports the following data sources and file formats: @@ -218,7 +218,7 @@ If StarRocks fails to unionize all the columns, it generates a schema error repo ### unload_data_param -From v3.2 onwards, FILES() supports defining writable files in remote storage for data unloading. For detailed instructions, see [Unload data using INSERT INTO FILES](../../../unloading/unload_using_insert_into_files.md). +From v3.2 onwards, FILES() supports defining writable files in remote storage for data unloading. ```sql -- Supported from v3.2 onwards. diff --git a/docs/en/sql-reference/sql-statements/Resource/CREATE_RESOURCE.md b/docs/en/sql-reference/sql-statements/Resource/CREATE_RESOURCE.md index c028ec80e6a82..0eb7698ee9db9 100644 --- a/docs/en/sql-reference/sql-statements/Resource/CREATE_RESOURCE.md +++ b/docs/en/sql-reference/sql-statements/Resource/CREATE_RESOURCE.md @@ -6,7 +6,7 @@ displayed_sidebar: docs ## Description -Creates resources. The following types of resources can be created: Apache Spark™, Apache Hive™, Apache Iceberg, Apache Hudi, and JDBC. Spark resources are used in [Spark Load](../../../loading/SparkLoad.md) to manage loading information, such as YARN configurations, storage path of intermediate data, and Broker configurations. Hive, Iceberg, Hudi, and JDBC resources are used for managing data source access information involved in querying [External tables](../../../data_source/External_table.md). +Creates resources. The following types of resources can be created: Apache Spark™, Apache Hive™, Apache Iceberg, Apache Hudi, and JDBC. Spark resources are used in Spark Load to manage loading information, such as YARN configurations, storage path of intermediate data, and Broker configurations. Hive, Iceberg, Hudi, and JDBC resources are used for managing data source access information involved in querying [External tables](../../../data_source/External_table.md). :::tip diff --git a/docs/en/sql-reference/sql-statements/account-management/GRANT.md b/docs/en/sql-reference/sql-statements/account-management/GRANT.md index c702bac84f807..36aa10c199681 100644 --- a/docs/en/sql-reference/sql-statements/account-management/GRANT.md +++ b/docs/en/sql-reference/sql-statements/account-management/GRANT.md @@ -6,6 +6,7 @@ toc_max_heading_level: 4 # GRANT import UserPrivilegeCase from '../../../_assets/commonMarkdown/userPrivilegeCase.md' +import MultiServiceAccess from '../../../_assets/commonMarkdown/multi-service-access.mdx' ## Description @@ -13,7 +14,7 @@ Grants one or more privileges on specific objects to a user or a role. Grants roles to users or other roles. -For more information about the privileges that can be granted, see [Privilege items](../../../administration/user_privs/privilege_item.md). +For more information about the privileges that can be granted, see [Privilege items](../../../administration/user_privs/privilege_overview.md). After a GRANT operation is performed, you can run [SHOW GRANTS](./SHOW_GRANTS.md) to view detailed privilege information or run [REVOKE](REVOKE.md) to revoke a privilege or role. @@ -259,4 +260,5 @@ GRANT IMPERSONATE ON USER 'rose'@'%' TO USER 'jack'@'%'; -For the best practices of multi-service access control, see [Multi-service access control](../../../administration/user_privs/User_privilege.md#multi-service-access-control). + + diff --git a/docs/en/sql-reference/sql-statements/account-management/REVOKE.md b/docs/en/sql-reference/sql-statements/account-management/REVOKE.md index e093bfe0da585..6b2309311f1d7 100644 --- a/docs/en/sql-reference/sql-statements/account-management/REVOKE.md +++ b/docs/en/sql-reference/sql-statements/account-management/REVOKE.md @@ -6,11 +6,11 @@ displayed_sidebar: docs ## Description -Revokes specific privileges or roles from a user or a role. For the privileges supported by StarRocks, see [Privileges supported by StarRocks](../../../administration/user_privs/privilege_item.md). +Revokes specific privileges or roles from a user or a role. For the privileges supported by StarRocks, see [Privileges supported by StarRocks](../../../administration/user_privs/privilege_overview.md). :::tip -- Common users can only revoke their privileges that have the `WITH GRANT OPTION` keyword from other users and roles. For information about `WITH GRANT OPTION`, see [GRANT](GRANT.md). +- Common users can only revoke their privileges that have the `WITH GRANT OPTION` keyword from other users and roles. For information about `WITH GRANT OPTION`, see [GRANT](./GRANT.md). - Only users with the `user_admin` role has the privilege to revoke privileges from other users. ::: diff --git a/docs/en/sql-reference/sql-statements/account-management/SET_PASSWORD.md b/docs/en/sql-reference/sql-statements/account-management/SET_PASSWORD.md index 25878c7d8126c..5248f99a820c0 100644 --- a/docs/en/sql-reference/sql-statements/account-management/SET_PASSWORD.md +++ b/docs/en/sql-reference/sql-statements/account-management/SET_PASSWORD.md @@ -12,7 +12,7 @@ Changes login password for users. The [ALTER USER](ALTER_USER.md) command can al - All users can reset their own password. - Only users with the `user_admin` role can change the password of other users. -- Only the `root` user itself can change its password. For more information, see [Reset root password](../../../administration/user_privs/User_privilege.md#reset-lost-root-password). +- Only the `root` user itself can change its password. For more information, see [the priviege overview](../../../administration/user_privs/privilege_overview.md). ::: diff --git a/docs/en/sql-reference/sql-statements/cluster-management/nodes_processes/ALTER_SYSTEM.md b/docs/en/sql-reference/sql-statements/cluster-management/nodes_processes/ALTER_SYSTEM.md index f65f8a593fd35..1eddc8c8ce194 100644 --- a/docs/en/sql-reference/sql-statements/cluster-management/nodes_processes/ALTER_SYSTEM.md +++ b/docs/en/sql-reference/sql-statements/cluster-management/nodes_processes/ALTER_SYSTEM.md @@ -109,7 +109,7 @@ Manages FE, BE, CN, Broker nodes, and metadata snapshots in a cluster. ### Broker -- Add Broker nodes. You can use Broker nodes to load data from HDFS or cloud storage into StarRocks. For more information, see [Load data from HDFS](../../../../loading/hdfs_load.md) or [Load data from cloud storage](../../../../loading/cloud_storage_load.md). +- Add Broker nodes. You can use Broker nodes to load data from HDFS or cloud storage into StarRocks. For more information, see [Loading](../../../../loading/loading_introduction/Loading_intro.md). ```SQL ALTER SYSTEM ADD BROKER ":"[, ...] diff --git a/docs/en/sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md b/docs/en/sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md index 92ebc04eb3be0..4437bf5603906 100644 --- a/docs/en/sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md +++ b/docs/en/sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md @@ -9,7 +9,7 @@ import InsertPrivNote from '../../../_assets/commonMarkdown/insertPrivNote.md' ## Description -StarRocks provides the MySQL-based loading method Broker Load. After you submit a load job, StarRocks asynchronously runs the job. You can use `SELECT * FROM information_schema.loads` to query the job result. This feature is supported from v3.1 onwards. For more information about the background information, principles, supported data file formats, how to perform single-table loads and multi-table loads, and how to view job results, see [Load data from HDFS](../../../loading/hdfs_load.md) and [Load data from cloud storage](../../../loading/cloud_storage_load.md). +StarRocks provides the MySQL-based loading method Broker Load. After you submit a load job, StarRocks asynchronously runs the job. You can use `SELECT * FROM information_schema.loads` to query the job result. This feature is supported from v3.1 onwards. For more information about the background information, principles, supported data file formats, how to perform single-table loads and multi-table loads, and how to view job results, see [loading overview](../../../loading/loading_introduction/Loading_intro.md). @@ -121,7 +121,7 @@ INTO TABLE - `TEMPORARY PARTITION` - Specifies the name of the [temporary partition](../../../table_design/Temporary_partition.md) into which you want to load data. You can specify multiple temporary partitions, which must be separated by commas (,). + Specifies the name of the [temporary partition](../../../table_design/data_distribution/Temporary_partition.md) into which you want to load data. You can specify multiple temporary partitions, which must be separated by commas (,). - `COLUMNS TERMINATED BY` @@ -177,7 +177,7 @@ INTO TABLE > > If the columns of the data file are mapped in sequence onto the columns of the StarRocks table, you do not need to specify `column_list`. - If you want to skip a specific column of the data file, you only need to temporarily name that column as different from any of the StarRocks table columns. For more information, see [Transform data at loading](../../../loading/Etl_in_loading.md). + If you want to skip a specific column of the data file, you only need to temporarily name that column as different from any of the StarRocks table columns. For more information, see [loading overview](../../../loading/loading_introduction/Loading_intro.md). - `COLUMNS FROM PATH AS` @@ -605,7 +605,7 @@ The following parameters are supported: - `priority` - Specifies the priority of the load job. Valid values: `LOWEST`, `LOW`, `NORMAL`, `HIGH`, and `HIGHEST`. Default value: `NORMAL`. Broker Load provides the [FE parameter](../../../administration/management/FE_configuration.md) `max_broker_load_job_concurrency`, determines the maximum number of Broker Load jobs that can be concurrently run within your StarRocks cluster. If the number of Broker Load jobs that are submitted within the specified time period exceeds the maximum number, excessive jobs will be waiting to be scheduled based on their priorities. + Specifies the priority of the load job. Valid values: `LOWEST`, `LOW`, `NORMAL`, `HIGH`, and `HIGHEST`. Default value: `NORMAL`. Broker Load provides the FE parameter `max_broker_load_job_concurrency`, determines the maximum number of Broker Load jobs that can be concurrently run within your StarRocks cluster. If the number of Broker Load jobs that are submitted within the specified time period exceeds the maximum number, excessive jobs will be waiting to be scheduled based on their priorities. You can use the [ALTER LOAD](ALTER_LOAD.md) statement to change the priority of an existing load job that is in the `QUEUEING` or `LOADING` state. @@ -623,8 +623,6 @@ The following parameters are supported: Specifies the name of the column you want to use as the condition to determine whether updates can take effect. The update from a source record to a destination record takes effect only when the source data record has a greater or equal value than the destination data record in the specified column. - Broker Load supports conditional updates since v3.1. For more information, see [Change data through loading](../../../loading/Load_to_Primary_Key_tables.md#conditional-updates). - > **NOTE** > > The column that you specify cannot be a primary key column. Additionally, only tables that use the Primary Key table support conditional updates. @@ -693,7 +691,7 @@ For examples about loading JSON-formatted data by using the matched mode, see [L ## Related configuration items -The [FE configuration item](../../../administration/management/FE_configuration.md) `max_broker_load_job_concurrency` specifies the maximum number of Broker Load jobs that can be concurrently run within your StarRocks cluster. +The FE configuration item `max_broker_load_job_concurrency` specifies the maximum number of Broker Load jobs that can be concurrently run within your StarRocks cluster. In StarRocks v2.4 and earlier, if the total number of Broker Load jobs that are submitted within a specific period of time exceeds the maximum number, excessive jobs will be queued and scheduled based on their submission time. @@ -707,7 +705,7 @@ A Broker Load job can be split into one or more tasks that concurrently run. The - If you declare multiple `data_desc` parameters, each of which specifies a distinct partition for the same table, a task is generated to load the data of each partition. -Additionally, each task can be further split into one or more instances, which are evenly distributed to and concurrently run on the BEs or CNs of your StarRocks cluster. StarRocks splits each task based on the FE parameter [`min_bytes_per_broker_scanner`](../../../administration/management/FE_configuration.md) and the number of BE or CN nodes. You can use the following formula to calculate the number of instances in an individual task: +Additionally, each task can be further split into one or more instances, which are evenly distributed to and concurrently run on the BEs or CNs of your StarRocks cluster. StarRocks splits each task based on the FE parameter `min_bytes_per_broker_scanner` and the number of BE or CN nodes. You can use the following formula to calculate the number of instances in an individual task: **Number of instances in an individual task = min(Amount of data to be loaded by an individual task/`min_bytes_per_broker_scanner`, Number of BE/CN nodes)** diff --git a/docs/en/sql-reference/sql-statements/loading_unloading/INSERT.md b/docs/en/sql-reference/sql-statements/loading_unloading/INSERT.md index afb1a7871b123..97005fcf5f152 100644 --- a/docs/en/sql-reference/sql-statements/loading_unloading/INSERT.md +++ b/docs/en/sql-reference/sql-statements/loading_unloading/INSERT.md @@ -6,7 +6,7 @@ displayed_sidebar: docs ## Description -Inserts data into a specific table or overwrites a specific table with data. For detailed information about the application scenarios, see [Load data with INSERT](../../../loading/InsertInto.md). From v3.2.0 onwards, INSERT supports writing data into files in remote storage. You can [use INSERT INTO FILES() to unload data from StarRocks to remote storage](../../../unloading/unload_using_insert_into_files.md). +Inserts data into a specific table or overwrites a specific table with data. From v3.2.0 onwards, INSERT supports writing data into files in remote storage. You can use INSERT INTO FILES() to unload data from StarRocks to remote storage. You can submit an asynchronous INSERT task using [SUBMIT TASK](ETL/SUBMIT_TASK.md). @@ -39,13 +39,13 @@ You can submit an asynchronous INSERT task using [SUBMIT TASK](ETL/SUBMIT_TASK.m | OVERWRITE | To overwrite the table with data. | | table_name | The name of the table into which you want to load data. It can be specified with the database the table resides as `db_name.table_name`. | | PARTITION | The partitions into which you want to load the data. You can specify multiple partitions, which must be separated by commas (,). It must be set to partitions that exist in the destination table. If you specify this parameter, the data will be inserted only into the specified partitions. If you do not specify this parameter, the data will be inserted into all partitions. | -| TEMPORARY PARTITION |The name of the [temporary partition](../../../table_design/Temporary_partition.md) into which you want to load data. You can specify multiple temporary partitions, which must be separated by commas (,).| +| TEMPORARY PARTITION |The name of the [temporary partition](../../../table_design/data_distribution/Temporary_partition.md) into which you want to load data. You can specify multiple temporary partitions, which must be separated by commas (,).| | label | The unique identification label for each data load transaction within the database. If it is not specified, the system automatically generates one for the transaction. We recommend you specify the label for the transaction. Otherwise, you cannot check the transaction status if a connection error occurs and no result is returned. You can check the transaction status via `SHOW LOAD WHERE label="label"` statement. For the naming conventions of labels, see [System Limits](../../System_limit.md). | | column_name | The name of the destination column(s) to load data in. It must be set as columns that exist in the destination table. The destination columns you specify are mapped one on one in sequence to the columns of the source table, regardless of what the destination column names are. If no destination column is specified, the default value is all columns in the destination table. If the specified column in the source table does not exist in the destination column, the default value will be written to this column, and the transaction will fail if the specified column does not have a default value. If the column type of the source table is inconsistent with that of the destination table, the system will perform an implicit conversion on the mismatched column. If the conversion fails, a syntax parsing error will be returned. | | expression | Expression that assigns values to the column. | | DEFAULT | Assigns default value to the column. | | query | Query statement whose result will be loaded into the destination table. It can be any SQL statement supported by StarRocks. | -| FILES() | Table function [FILES()](../../sql-functions/table-functions/files.md). You can use this function to unload data into remote storage. For more information, see [Use INSERT INTO FILES() to unload data to remote storage](../../../unloading/unload_using_insert_into_files.md). | +| FILES() | Table function [FILES()](../../sql-functions/table-functions/files.md). You can use this function to unload data into remote storage. | ## Return diff --git a/docs/en/sql-reference/sql-statements/loading_unloading/SHOW_LOAD.md b/docs/en/sql-reference/sql-statements/loading_unloading/SHOW_LOAD.md index f7f7eeb2fa307..800ca3e3d7d06 100644 --- a/docs/en/sql-reference/sql-statements/loading_unloading/SHOW_LOAD.md +++ b/docs/en/sql-reference/sql-statements/loading_unloading/SHOW_LOAD.md @@ -6,7 +6,7 @@ displayed_sidebar: docs ## Description -Displays information of all load jobs or given load jobs in a database. This statement can only display load jobs that are created by using [Broker Load](BROKER_LOAD.md), [INSERT](../data-mSPARK_LOAD.mdLoad](../loading_unloading/SPARK_LOAD.md). You can also view information of load jobs via the `curl` command. From v3.1 onwards, we recommend that you use the [SELECT](../table_bucket_part_index/SELECT.md) statement to query the results of Broker Load or Insert jobs from the [`loads`](../../information_schema/loads.md) table in the `information_schema` database. For more information, see [Load data from HDFS](../../../loading/hdfs_load.md), [Load data from cloud storage](../../../loading/cloud_storage_load.md), [Load data using INSERT](../../../loading/InsertInto.md), and [Bulk load using Apache Spark™](../../../loading/SparkLoad.md). +Displays information of all load jobs or given load jobs in a database. This statement can only display load jobs that are created by using Broker Load, INSERT, and SPARK_LOAD. You can also view load job information via the `curl` command. From v3.1 onwards, we recommend that you use the SELECT statement to query the results of Broker Load or Insert jobs from the `loads` table in the `information_schema` database. For more information, see [Loading](../../../loading/loading_introduction/Loading_intro.md). In addition to the preceding loading methods, StarRocks supports using Stream Load and Routine Load to load data. Stream Load is a synchronous operation and will directly return information of Stream Load jobs. Routine Load is an asynchronous operation where you can use the [SHOW ROUTINE LOAD](routine_load/SHOW_ROUTINE_LOAD.md) statement to display information of Routine Load jobs. diff --git a/docs/en/sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md b/docs/en/sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md index 9982519dc00e0..1c95d4fa4a407 100644 --- a/docs/en/sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md +++ b/docs/en/sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md @@ -2,12 +2,11 @@ displayed_sidebar: docs toc_max_heading_level: 4 --- +import Tip from '../../../_assets/commonMarkdown/quickstart-shared-nothing-tip.mdx'; # STREAM LOAD -:::tip -The [StarRocks in Docker](../../../quick_start/shared-nothing.md) quick start features Stream Load. Give it a try for hands-on experience and a detailed explanation of a realistic ETL flow. -::: + ## Description @@ -101,7 +100,7 @@ The parameters in the `data_desc` descriptor can be divided into three types: co | file_path | Yes | The save path of the data file. You can optionally include the extension of the file name. | | format | No | The format of the data file. Valid values: `CSV` and `JSON`. Default value: `CSV`. | | partitions | No | The partitions into which you want to load the data file. By default, if you do not specify this parameter, StarRocks loads the data file into all partitions of the StarRocks table. | -| temporary_partitions| No | The name of the [temporary partition](../../../table_design/Temporary_partition.md) into which you want to load data file. You can specify multiple temporary partitions, which must be separated by commas (,).| +| temporary_partitions| No | The name of the [temporary partition](../../../table_design/data_distribution/Temporary_partition.md) into which you want to load data file. You can specify multiple temporary partitions, which must be separated by commas (,).| | columns | No | The column mapping between the data file and the StarRocks table.
If the fields in the data file can be mapped in sequence onto the columns in the StarRocks table, you do not need to specify this parameter. Instead, you can use this parameter to implement data conversions. For example, if you load a CSV data file and the file consists of two columns that can be mapped in sequence onto the two columns, `id` and `city`, of the StarRocks table, you can specify `"columns: city,tmp_id, id = tmp_id * 100"`. For more information, see the "[Column mapping](#column-mapping)" section in this topic. | #### CSV parameters @@ -164,7 +163,7 @@ The following table describes the optional parameters. | load_mem_limit | No | The maximum amount of memory that can be provisioned to the load job. Unit: bytes. By default, the maximum memory size for a load job is 2 GB. The value of this parameter cannot exceed the maximum amount of memory that can be provisioned to each BE or CN. | | partial_update | No | Whether to use partial updates. Valid values: `TRUE` and `FALSE`. Default value: `FALSE`, indicating to disable this feature. | | partial_update_mode | No | Specifies the mode for partial updates. Valid values: `row` and `column`.
  • The value `row` (default) means partial updates in row mode, which is more suitable for real-time updates with many columns and small batches.
  • The value `column` means partial updates in column mode, which is more suitable for batch updates with few columns and many rows. In such scenarios, enabling the column mode offers faster update speeds. For example, in a table with 100 columns, if only 10 columns (10% of the total) are updated for all rows, the update speed of the column mode is 10 times faster.
| -| merge_condition | No | Specifies the name of the column you want to use as the condition to determine whether updates can take effect. The update from a source record to a destination record takes effect only when the source data record has a greater or equal value than the destination data record in the specified column. StarRocks supports conditional updates since v2.5. For more information, see [Change data through loading](../../../loading/Load_to_Primary_Key_tables.md).
**NOTE**
The column that you specify cannot be a primary key column. Additionally, only tables that use the Primary Key table support conditional updates. | +| merge_condition | No | Specifies the name of the column you want to use as the condition to determine whether updates can take effect. The update from a source record to a destination record takes effect only when the source data record has a greater or equal value than the destination data record in the specified column. StarRocks supports conditional updates since v2.5.
**NOTE**
The column that you specify cannot be a primary key column. Additionally, only tables that use the Primary Key table support conditional updates. | ## Column mapping diff --git a/docs/en/sql-reference/sql-statements/loading_unloading/routine_load/ALTER_ROUTINE_LOAD.md b/docs/en/sql-reference/sql-statements/loading_unloading/routine_load/ALTER_ROUTINE_LOAD.md index 959aa1f39176a..fc740dad50ba7 100644 --- a/docs/en/sql-reference/sql-statements/loading_unloading/routine_load/ALTER_ROUTINE_LOAD.md +++ b/docs/en/sql-reference/sql-statements/loading_unloading/routine_load/ALTER_ROUTINE_LOAD.md @@ -93,7 +93,7 @@ FROM data_source ## Examples -1. The following example increases the value of the property `desired_concurrent_number` of the load job to `5` in order to increase the parallelism of load tasks. For details on task parallelism, see [how to improve load performance](../../../../faq/loading/Routine_load_faq.md#how-can-i-improve-loading-performance). +1. The following example increases the value of the property `desired_concurrent_number` of the load job to `5` in order to increase the parallelism of load tasks. ```SQL ALTER ROUTINE LOAD FOR example_tbl_ordertest diff --git a/docs/en/sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md b/docs/en/sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md index 46f452657247a..b5916169d09ff 100644 --- a/docs/en/sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md +++ b/docs/en/sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md @@ -2,11 +2,11 @@ displayed_sidebar: docs --- +import Tip from '../../../../_assets/commonMarkdown/quickstart-routine-load-tip.mdx'; + # CREATE ROUTINE LOAD -:::tip -Try Routine Load out in this [Quick Start](../../../../quick_start/routine-load.md) -::: + Routine Load can continuously consume messages from Apache Kafka® and load data into StarRocks. Routine Load can consume CSV, JSON, and Avro (supported since v3.0.1) data from a Kafka cluster and access Kafka via multiple security protocols, including `plaintext`, `ssl`, `sasl_plaintext`, and `sasl_ssl`. @@ -14,7 +14,7 @@ This topic describes the syntax, parameters, and examples of the CREATE ROUTINE > **NOTE** > -> - For information about the application scenarios, principles, and basic operations of Routine Load, see [Load data using Routine Load](../../../../loading/RoutineLoad.md). +> - For information about the application scenarios, principles, and basic operations of Routine Load, see [Load data using Routine Load](../../../../loading/loading_introduction/Loading_intro.md). > - You can load data into StarRocks tables only as a user who has the INSERT privilege on those StarRocks tables. If you do not have the INSERT privilege, follow the instructions provided in [GRANT](../../account-management/GRANT.md) to grant the INSERT privilege to the user that you use to connect to your StarRocks cluster. ## Syntax @@ -96,7 +96,7 @@ PARTITION (p1, p2, p3) `TEMPORARY PARTITION` -The name of the [temporary partition](../../../../table_design/Temporary_partition.md) into which you want to load data. You can specify multiple temporary partitions, which must be separated by commas (,). +The name of the [temporary partition](../../../../table_design/data_distribution/Temporary_partition.md) into which you want to load data. You can specify multiple temporary partitions, which must be separated by commas (,). ### `job_properties` @@ -117,7 +117,7 @@ PROPERTIES ("" = ""[, "" = "" ...]) | log_rejected_record_num | No | Specifies the maximum number of unqualified data rows that can be logged. This parameter is supported from v3.1 onwards. Valid values: `0`, `-1`, and any non-zero positive integer. Default value: `0`.
  • The value `0` specifies that data rows that are filtered out will not be logged.
  • The value `-1` specifies that all data rows that are filtered out will be logged.
  • A non-zero positive integer such as `n` specifies that up to `n` data rows that are filtered out can be logged on each BE.
| | timezone | No | The time zone used by the load job. Default value: `Asia/Shanghai`. The value of this parameter affects the results returned by functions such as strftime(), alignment_timestamp(), and from_unixtime(). The time zone specified by this parameter is a session-level time zone. For more information, see [Configure a time zone](../../../../administration/management/timezone.md). | | partial_update | No | Whether to use partial updates. Valid values: `TRUE` and `FALSE`. Default value: `FALSE`, indicating to disable this feature. | -| merge_condition | No | Specifies the name of the column you want to use as the condition to determine whether to update data. Data will be updated only when the value of the data to be loaded into this column is greater than or equal to the current value of this column. For more information, see [Change data through loading](../../../../loading/Load_to_Primary_Key_tables.md).
**NOTE**
Only Primary Key tables support conditional updates. The column that you specify cannot be a primary key column. | +| merge_condition | No | Specifies the name of the column you want to use as the condition to determine whether to update data. Data will be updated only when the value of the data to be loaded into this column is greater than or equal to the current value of this column. **NOTE**
Only Primary Key tables support conditional updates. The column that you specify cannot be a primary key column. | | format | No | The format of the data to be loaded. Valid values: `CSV`, `JSON`, and `Avro` (supported since v3.0.1). Default value: `CSV`. | | trim_space | No | Specifies whether to remove spaces preceding and following column separators from the data file when the data file is in CSV format. Type: BOOLEAN. Default value: `false`.
For some databases, spaces are added to column separators when you export data as a CSV-formatted data file. Such spaces are called leading spaces or trailing spaces depending on their locations. By setting the `trim_space` parameter, you can enable StarRocks to remove such unnecessary spaces during data loading.
Note that StarRocks does not remove the spaces (including leading spaces and trailing spaces) within a field wrapped in a pair of `enclose`-specified characters. For example, the following field values use pipe (|) as the column separator and double quotation marks (`"`) as the `enclose`-specified character: | "Love StarRocks" |. If you set `trim_space` to `true`, StarRocks processes the preceding field values as |"Love StarRocks"|. | | enclose | No | Specifies the character that is used to wrap the field values in the data file according to [RFC4180](https://www.rfc-editor.org/rfc/rfc4180) when the data file is in CSV format. Type: single-byte character. Default value: `NONE`. The most prevalent characters are single quotation mark (`'`) and double quotation mark (`"`).
All special characters (including row separators and column separators) wrapped by using the `enclose`-specified character are considered normal symbols. StarRocks can do more than RFC4180 as it allows you to specify any single-byte character as the `enclose`-specified character.
If a field value contains an `enclose`-specified character, you can use the same character to escape that `enclose`-specified character. For example, you set `enclose` to `"`, and a field value is `a "quoted" c`. In this case, you can enter the field value as `"a ""quoted"" c"` into the data file. | @@ -333,10 +333,6 @@ FROM KAFKA To improve loading performance and avoid accumulative consumption, you can increase task parallelism by increasing the `desired_concurrent_number` value when you create the Routine Load job. Task parallelism allows splitting one Routine Load job into as many parallel tasks as possible. -> **Note** -> -> For more ways to improve loading performance, see [Routine Load FAQ](../../../../faq/loading/Routine_load_faq.md). - Note that the actual task parallelism is determined by the minimum value among the following multiple parameters: ```SQL diff --git a/docs/en/sql-reference/sql-statements/loading_unloading/routine_load/SHOW_ROUTINE_LOAD_TASK.md b/docs/en/sql-reference/sql-statements/loading_unloading/routine_load/SHOW_ROUTINE_LOAD_TASK.md index c462a644ab264..46befd6172435 100644 --- a/docs/en/sql-reference/sql-statements/loading_unloading/routine_load/SHOW_ROUTINE_LOAD_TASK.md +++ b/docs/en/sql-reference/sql-statements/loading_unloading/routine_load/SHOW_ROUTINE_LOAD_TASK.md @@ -14,8 +14,6 @@ Shows the execution information of load tasks within a Routine Load job. - -- For the relationship between a Routine Load job and the load tasks in it, see [Load data using Routine Load](../../../../loading/RoutineLoad.md#basic-concepts) - ::: ## Syntax diff --git a/docs/en/sql-reference/sql-statements/loading_unloading/unloading/EXPORT.md b/docs/en/sql-reference/sql-statements/loading_unloading/unloading/EXPORT.md index 10c4774556e52..7791753bc3884 100644 --- a/docs/en/sql-reference/sql-statements/loading_unloading/unloading/EXPORT.md +++ b/docs/en/sql-reference/sql-statements/loading_unloading/unloading/EXPORT.md @@ -64,7 +64,7 @@ WITH BROKER - `WITH BROKER` - In v2.4 and earlier, input `WITH BROKER ""` to specify the broker you want to use. From v2.5 onwards, you no longer need to specify a broker, but you still need to retain the `WITH BROKER` keyword. For more information, see [Export data using EXPORT > Background information](../../../../unloading/Export.md#background-information). + In v2.4 and earlier, input `WITH BROKER ""` to specify the broker you want to use. From v2.5 onwards, you no longer need to specify a broker, but you still need to retain the `WITH BROKER` keyword. - `broker_properties` diff --git a/docs/en/sql-reference/sql-statements/loading_unloading/unloading/SHOW_EXPORT.md b/docs/en/sql-reference/sql-statements/loading_unloading/unloading/SHOW_EXPORT.md index 6dccbe804bbb3..fbf0cc5ddf2ea 100644 --- a/docs/en/sql-reference/sql-statements/loading_unloading/unloading/SHOW_EXPORT.md +++ b/docs/en/sql-reference/sql-statements/loading_unloading/unloading/SHOW_EXPORT.md @@ -84,7 +84,7 @@ The parameters in the return result are described as follows: - `FINISHED`: The export job has been successfully completed. - `CANCELLED`: The export job has failed. -- `Progress`: the progress of the export job. The progress is measured in the unit of query plans. Suppose that the export job is divided into 10 query plans and three of them have finished. In this case, the progress of the export job is 30%. For more information, see ["Export data using EXPORT > Workflow"](../../../../unloading/Export.md#workflow). +- `Progress`: the progress of the export job. The progress is measured in the unit of query plans. Suppose that the export job is divided into 10 query plans and three of them have finished. In this case, the progress of the export job is 30%. - `TaskInfo`: the information of the export job. The information is a JSON object that consists of the following keys: @@ -93,7 +93,7 @@ The parameters in the return result are described as follows: - `column separator`: the column separator used in the exported data file. - `columns`: the names of the columns whose data is exported. - `tablet num`: the total number of tablets that are exported. - - `broker`: In v2.4 and earlier, this field is used to return the name of the broker that is used by the export job. From v2.5 onwards, this field returns an empty string. For more information, see ["Export data using EXPORT > Background information"](../../../../unloading/Export.md#background-information). + - `broker`: In v2.4 and earlier, this field is used to return the name of the broker that is used by the export job. From v2.5 onwards, this field returns an empty string. - `coord num`: the number of query plans into which the export job is divided. - `db`: the name of the database to which the exported data belongs. - `tbl`: the name of the table to which the exported data belongs diff --git a/docs/en/sql-reference/sql-statements/materialized_view/CREATE_MATERIALIZED_VIEW.md b/docs/en/sql-reference/sql-statements/materialized_view/CREATE_MATERIALIZED_VIEW.md index 2bf39b6cbba5d..c26b6d0573f5d 100644 --- a/docs/en/sql-reference/sql-statements/materialized_view/CREATE_MATERIALIZED_VIEW.md +++ b/docs/en/sql-reference/sql-statements/materialized_view/CREATE_MATERIALIZED_VIEW.md @@ -188,11 +188,11 @@ The bucketing strategy of the asynchronous materialized view. StarRocks supports DISTRIBUTED BY HASH ([, ...]) [BUCKETS ] ``` - For more information, see [Data distribution](../../../table_design/Data_distribution.md#data-distribution). + For more information, see [Data distribution](../../../table_design/data_distribution/Data_distribution.md#data-distribution). > **NOTE** > - > Since v2.5.7, StarRocks can automatically set the number of buckets (BUCKETS) when you create a table or add a partition. You no longer need to manually set the number of buckets. For detailed information, see [set the number of buckets](../../../table_design/Data_distribution.md#set-the-number-of-buckets). + > Since v2.5.7, StarRocks can automatically set the number of buckets (BUCKETS) when you create a table or add a partition. You no longer need to manually set the number of buckets. For detailed information, see [set the number of buckets](../../../table_design/data_distribution/Data_distribution.md#set-the-number-of-buckets). - **Random bucketing**: @@ -206,7 +206,7 @@ The bucketing strategy of the asynchronous materialized view. StarRocks supports > > Asynchronous materialized views with a random bucketing strategy cannot be assigned to a colocation group. - For more information, see [Random bucketing](../../../table_design/Data_distribution.md#random-bucketing-since-v31) + For more information, see [Random bucketing](../../../table_design/data_distribution/Data_distribution.md#random-bucketing-since-v31) **refresh_moment** (optional) @@ -259,8 +259,8 @@ Properties of the asynchronous materialized view. You can modify the properties - `storage_medium`: Storage medium type. Valid values: `HDD` and `SSD`. - `storage_cooldown_time`: the storage cooldown time for a partition. If both HDD and SSD storage mediums are used, data in the SSD storage is moved to the HDD storage after the time specified by this property. Format: "yyyy-MM-dd HH:mm:ss". The specified time must be later than the current time. If this property is not explicitly specified, the storage cooldown is not performed by default. - `partition_ttl`: The time-to-live (TTL) for partitions. Partitions whose data is within the specified time range are retained. Expired partitions are deleted automatically. Unit: `YEAR`, `MONTH`, `DAY`, `HOUR`, and `MINUTE`. For example, you can specify this property as `2 MONTH`. This property is recommended over `partition_ttl_number`. It is supported from v3.1.5 onwards. -- `partition_ttl_number`: The number of most recent materialized view partitions to retain. For the partitions with a start time earlier than the current time, after the number of these partitions exceeds this value, less recent partitions will be deleted. StarRocks will periodically check materialized view partitions according to the time interval specified in the FE configuration item `dynamic_partition_check_interval_seconds`, and automatically delete expired partitions. If you enabled the [dynamic partitioning](../../../table_design/dynamic_partitioning.md) strategy, the partitions created in advance are not counted in. When the value is `-1`, all partitions of the materialized view will be preserved. Default: `-1`. -- `partition_refresh_number`: In a single refresh, the maximum number of partitions to refresh. If the number of partitions to be refreshed exceeds this value, StarRocks will split the refresh task and complete it in batches. Only when the previous batch of partitions is refreshed successfully, StarRocks will continue to refresh the next batch of partitions until all partitions are refreshed. If any of the partitions fail to be refreshed, no subsequent refresh tasks will be generated. When the value is `-1`, the refresh task will not be split. Default: `-1`. +- `partition_ttl_number`: The number of most recent materialized view partitions to retain. For the partitions with a start time earlier than the current time, after the number of these partitions exceeds this value, less recent partitions will be deleted. StarRocks will periodically check materialized view partitions according to the time interval specified in the FE configuration item `dynamic_partition_check_interval_seconds`, and automatically delete expired partitions. If you enabled the [dynamic partitioning](../../../table_design/data_distribution/dynamic_partitioning.md) strategy, the partitions created in advance are not counted in. When the value is `-1`, all partitions of the materialized view will be preserved. Default: `-1`. +- `partition_refresh_number`: In a single refresh, the maximum number of partitions to refresh. If the number of partitions to be refreshed exceeds this value, StarRocks will split the refresh task and complete it in batches. Only when the previous batch of partitions is refreshed successfully, StarRocks will continue to refresh the next batch of partitions until all partitions are refreshed. If any of the partitions fail to be refreshed, no subsequent refresh tasks will be generated. When the value is `-1`, the refresh task will not be split. The default value is `-1`. - `excluded_trigger_tables`: If a base table of the materialized view is listed here, the automatic refresh task will not be triggered when the data in the base table is changed. This parameter only applies to load-triggered refresh strategy, and is usually used together with the property `auto_refresh_partitions_limit`. Format: `[db_name.]table_name`. When the value is an empty string, any data change in all base tables triggers the refresh of the corresponding materialized view. The default value is an empty string. - `auto_refresh_partitions_limit`: The number of most recent materialized view partitions that need to be refreshed when a materialized view refresh is triggered. You can use this property to limit the refresh range and reduce the refresh cost. However, because not all the partitions are refreshed, the data in the materialized view may not be consistent with the base table. Default: `-1`. When the value is `-1`, all partitions will be refreshed. When the value is a positive integer N, StarRocks sorts the existing partitions in chronological order, and refreshes the current partition and N-1 most recent partitions. If the number of partitions is less than N, StarRocks refreshes all existing partitions. If there are dynamic partitions created in advance in your materialized view, StarRocks refreshes all pre-created partitions. - `mv_rewrite_staleness_second`: If the materialized view's last refresh is within the time interval specified in this property, this materialized view can be used directly for query rewrite, regardless of whether the data in the base tables changes. If the last refresh is before this time interval, StarRocks checks whether the base tables have been updated to determine whether the materialized view can be used for query rewrite. Unit: Second. This property is supported from v3.0. diff --git a/docs/en/sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md b/docs/en/sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md index 27ffdab51d78d..7be06576894aa 100644 --- a/docs/en/sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md +++ b/docs/en/sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md @@ -114,11 +114,11 @@ Default value: `olap`. If this parameter is not specified, an OLAP table (StarRo Optional value: `mysql`, `elasticsearch`, `hive`, `jdbc` (2.3 and later), `iceberg`, and `hudi` (2.2 and later). If you want to create an external table to query external data sources, specify `CREATE EXTERNAL TABLE` and set `ENGINE` to any of these values. You can refer to [External table](../../../data_source/External_table.md) for more information. -**From v3.0 onwards, we recommend that you use catalogs to query data from Hive, Iceberg, Hudi, and JDBC data sources. External tables are deprecated. For more information, see [Hive catalog](../../../data_source/catalog/hive_catalog.md), [Iceberg catalog](../../../data_source/catalog/iceberg_catalog.md), [Hudi catalog](../../../data_source/catalog/hudi_catalog.md), and [JDBC catalog](../../../data_source/catalog/jdbc_catalog.md).** +**We recommend that you use catalogs to query data from Hive, Iceberg, Hudi, and JDBC data sources. External tables are deprecated.** -**From v3.1 onwards, StarRocks supports creating Parquet-formatted tables in Iceberg catalogs, and you can insert data to these Parquet-formatted Iceberg tables by using [INSERT INTO](../loading_unloading/INSERT.md). See [Create an Iceberg table](../../../data_source/catalog/iceberg_catalog.md#create-an-iceberg-table).** +**From v3.1 onwards, StarRocks supports creating Parquet-formatted tables in Iceberg catalogs, and you can insert data to these Parquet-formatted Iceberg tables by using INSERT INTO.** -**From v3.2 onwards, StarRocks supports creating Parquet-formatted tables in Hive catalogs, and you can insert data to these Parquet-formatted Hive tables by using [INSERT INTO](../loading_unloading/INSERT.md). See [Create a Hive table](../../../data_source/catalog/hive_catalog.md#create-a-hive-table).** +**From v3.2 onwards, StarRocks supports creating Parquet-formatted tables in Hive catalogs, and supports sinking data to these Parquet-formatted Hive tables by using INSERT INTO. - For MySQL, specify the following properties: @@ -234,7 +234,7 @@ Partition description can be used in the following ways: #### Create partitions dynamically -[Dynamic partitioning](../../../table_design/dynamic_partitioning.md) provides a time-to-live (TTL) management for partitions. StarRocks automatically creates new partitions in advance and removes expired partitions to ensure data freshness. To enable this feature, you can configure Dynamic partitioning related properties at table creation. +[Dynamic partitioning](../../../table_design/data_distribution/dynamic_partitioning.md) provides a time-to-live (TTL) management for partitions. StarRocks automatically creates new partitions in advance and removes expired partitions to ensure data freshness. To enable this feature, you can configure Dynamic partitioning related properties at table creation. #### Create partitions one by one @@ -330,7 +330,7 @@ You can specify the start and end values in `START()` and `END()` and the time u - The partitioning column can be of a date or integer type. - If the partitioning column is of a date type, you need to use the `INTERVAL` keyword to specify the time interval. You can specify the time unit as hour (since v3.0), day, week, month, or year. The naming conventions of partitions are the same as those for dynamic partitions. -For more information, see [Data distribution](../../../table_design/Data_distribution.md). +For more information, see [Data distribution](../../../table_design/data_distribution/Data_distribution.md). ### distribution_desc @@ -349,10 +349,10 @@ StarRocks supports hash bucketing and random bucketing. If you do not configure **Precautions** - You can only use random bucketing to create Duplicate Key tables. - You can not specify a [Colocation Group](../../../using_starrocks/Colocate_join.md) for a table bucketed randomly. - - [Spark Load](../../../loading/SparkLoad.md) cannot be used to load data into tables bucketed randomly. - - Since StarRocks v2.5.7, you do not need to set the number of buckets when you create a table. StarRocks automatically sets the number of buckets. If you want to set this parameter, see [Set the number of buckets](../../../table_design/Data_distribution.md#set-the-number-of-buckets). + - Spark Load cannot be used to load data into tables bucketed randomly. + - Since StarRocks v2.5.7, you do not need to set the number of buckets when you create a table. StarRocks automatically sets the number of buckets. If you want to set this parameter, see [Set the number of buckets](../../../table_design/data_distribution/Data_distribution.md#set-the-number-of-buckets). - For more information, see [Random bucketing](../../../table_design/Data_distribution.md#random-bucketing-since-v31). + For more information, see [Random bucketing](../../../table_design/data_distribution/Data_distribution.md#random-bucketing-since-v31). - Hash bucketing @@ -372,14 +372,14 @@ StarRocks supports hash bucketing and random bucketing. If you do not configure - If the query is complex, we recommend that you select a high cardinality column as the bucketing column to ensure balanced data distribution among buckets and improve cluster resource utilization. - If the query is relatively simple, we recommend that you select the column that is often used as the query condition as the bucketing column to improve query efficiency. - If partition data cannot be evenly distributed into each bucket by using one bucketing column, you can choose multiple bucketing columns (at most three). For more information, see [Choose bucketing columns](../../../table_design/Data_distribution.md#hash-bucketing). + If partition data cannot be evenly distributed into each bucket by using one bucketing column, you can choose multiple bucketing columns (at most three). For more information, see [Choose bucketing columns](../../../table_design/data_distribution/Data_distribution.md#hash-bucketing). **Precautions**: - **When you create a table, you must specify its bucketing columns**. - The values of bucketing columns cannot be updated. - Bucketing columns cannot be modified after they are specified. - - Since StarRocks v2.5.7, you do not need to set the number of buckets when you create a table. StarRocks automatically sets the number of buckets. If you want to set this parameter, see [Set the number of buckets](../../../table_design/Data_distribution.md#set-the-number-of-buckets). + - Since StarRocks v2.5.7, you do not need to set the number of buckets when you create a table. StarRocks automatically sets the number of buckets. If you want to set this parameter, see [Set the number of buckets](../../../table_design/data_distribution/Data_distribution.md#set-the-number-of-buckets). ### ORDER BY @@ -634,7 +634,7 @@ PROPERTIES ( > **NOTE** > - > To enable the local disk cache, you must specify the directory of the disk in the BE configuration item `storage_root_path`. For more information, see [BE Configuration items](../../../administration/management/BE_configuration.md). + > To enable the local disk cache, you must specify the directory of the disk in the BE configuration item `storage_root_path`. - `datacache.partition_duration`: The validity duration of the hot data. When the local disk cache is enabled, all data is loaded into the cache. When the cache is full, StarRocks deletes the less recently used data from the cache. When a query needs to scan the deleted data, StarRocks checks if the data is within the duration of validity. If the data is within the duration, StarRocks loads the data into the cache again. If the data is not within the duration, StarRocks does not load it into the cache. This property is a string value that can be specified with the following units: `YEAR`, `MONTH`, `DAY`, and `HOUR`, for example, `7 DAY` and `12 HOUR`. If it is not specified, all data is cached as the hot data. @@ -653,7 +653,7 @@ PROPERTIES ( > **NOTE** > > - StarRocks shared-data clusters do not support this parameter. - > - If you need to configure fast schema evolution at the cluster level, such as disabling fast schema evolution within the StarRocks cluster, you can set the FE dynamic parameter [`enable_fast_schema_evolution`](../../../administration/management/FE_configuration.md#enable_fast_schema_evolution). + > - If you need to configure fast schema evolution at the cluster level, such as disabling fast schema evolution within the StarRocks cluster, you can set the FE dynamic parameter `enable_fast_schema_evolution`. ## Examples diff --git a/docs/en/sql-reference/sql-statements/table_bucket_part_index/SHOW_CREATE_TABLE.md b/docs/en/sql-reference/sql-statements/table_bucket_part_index/SHOW_CREATE_TABLE.md index 6199821e5a72a..b1b5e50d86ff1 100644 --- a/docs/en/sql-reference/sql-statements/table_bucket_part_index/SHOW_CREATE_TABLE.md +++ b/docs/en/sql-reference/sql-statements/table_bucket_part_index/SHOW_CREATE_TABLE.md @@ -12,7 +12,7 @@ Returns the CREATE TABLE statement that was used to create a given table. Since v3.0, you can use the SHOW CREATE TABLE statement to view the CREATE TABLE statements of the tables that are managed by an external catalog and are stored in Apache Hive™, Apache Iceberg, Apache Hudi, or Delta Lake. -Since v2.5.7, StarRocks can automatically set the number of buckets (BUCKETS) when you create a table or add a partition. You no longer need to manually set the number of buckets. For detailed information, see [set the number of buckets](../../../table_design/Data_distribution.md#set-the-number-of-buckets). +Since v2.5.7, StarRocks can automatically set the number of buckets (BUCKETS) when you create a table or add a partition. You no longer need to manually set the number of buckets. For detailed information, see [set the number of buckets](../../../table_design/data_distribution/Data_distribution.md#set-the-number-of-buckets). - If you specified the number of buckets when creating a table, the output of SHOW CREATE TABLE will display the number of buckets. - If you did not specify the number of buckets when creating a table, the output of SHOW CREATE TABLE will not display the number of buckets. You can run [SHOW PARTITIONS](SHOW_PARTITIONS.md) to view the number of buckets for each partition. diff --git a/docs/en/sql-reference/sql-statements/table_bucket_part_index/SHOW_PARTITIONS.md b/docs/en/sql-reference/sql-statements/table_bucket_part_index/SHOW_PARTITIONS.md index eca9ada42bbb4..6dd85dfbe6177 100644 --- a/docs/en/sql-reference/sql-statements/table_bucket_part_index/SHOW_PARTITIONS.md +++ b/docs/en/sql-reference/sql-statements/table_bucket_part_index/SHOW_PARTITIONS.md @@ -6,7 +6,7 @@ displayed_sidebar: docs ## Description -Displays partition information, including common partitions and [temporary partitions](../../../table_design/Temporary_partition.md). +Displays partition information, including common partitions and [temporary partitions](../../../table_design/data_distribution/Temporary_partition.md). ## Syntax diff --git a/docs/en/table_design/StarRocks_table_design.md b/docs/en/table_design/StarRocks_table_design.md index ab24f8b23f113..be809602cf317 100644 --- a/docs/en/table_design/StarRocks_table_design.md +++ b/docs/en/table_design/StarRocks_table_design.md @@ -1,5 +1,6 @@ --- displayed_sidebar: docs +sidebar_position: 10 --- # Table overview @@ -93,7 +94,7 @@ StarRocks provides four types of tables which are Duplicate Key tables, Primary - Aggregate tables are suitable to store pre-aggregated data, helping reduce the amount of data scanned and calculated and improve efficiency for aggregation queries. - Unique tables are also suitable to store frequently updated realtime data. However this type of tables is being replaced by Primary Key tables, which are more powerful. -### [Data distribution](./Data_distribution.md) +### [Data distribution](data_distribution/Data_distribution.md) StarRocks uses a partitioning+bucketing two-tier data distribution strategy, to evenly distribute data across BEs. A well-designed data distribution strategy can effectively reduce the amount of data scanned and maximize StarRocks' concurrent processing capabilities, thereby increasing query performance. @@ -118,7 +119,7 @@ StarRocks provides two bucketing methods: In addition to basic data types such as NUMERIC, DATE, and STRING, StarRocks supports complex semi-structured data types, including ARRAY, JSON, MAP, and STRUCT. -### [Index](./indexes/indexes_overview.md) +### [Index](indexes/indexes.md) An index is a special data structure and is used as a pointer to data in a table. When the conditional columns in queries are indexed columns, StarRocks can swiftly locate the data that meets the conditions. diff --git a/docs/en/table_design/Table_design.md b/docs/en/table_design/Table_design.md deleted file mode 100644 index a5eae18cef61d..0000000000000 --- a/docs/en/table_design/Table_design.md +++ /dev/null @@ -1,12 +0,0 @@ ---- -displayed_sidebar: docs ---- - -# Introduction - -This chapter introduces the following topics: - -- Data models for different business scenarios -- Data distribution strategies -- Indexing technology -- Materialized view technology diff --git a/docs/en/table_design/data_compression.md b/docs/en/table_design/data_compression.md index 4331d4824a3c6..9af57147ad021 100644 --- a/docs/en/table_design/data_compression.md +++ b/docs/en/table_design/data_compression.md @@ -1,5 +1,6 @@ --- displayed_sidebar: docs +sidebar_position: 50 --- # Data compression diff --git a/docs/en/table_design/Data_distribution.md b/docs/en/table_design/data_distribution/Data_distribution.md similarity index 94% rename from docs/en/table_design/Data_distribution.md rename to docs/en/table_design/data_distribution/Data_distribution.md index 76b0b77149d86..1e775fbb226c0 100644 --- a/docs/en/table_design/Data_distribution.md +++ b/docs/en/table_design/data_distribution/Data_distribution.md @@ -2,6 +2,7 @@ displayed_sidebar: docs toc_max_heading_level: 4 description: Partition and bucket data +sidebar_position: 30 --- # Data distribution @@ -23,7 +24,7 @@ Configuring appropriate partitioning and bucketing at table creation can help to Modern distributed database systems generally use the following basic distribution methods: Round-Robin, Range, List, and Hash. -![Data distribution method](../_assets/3.3.2-1.png) +![Data distribution method](../../_assets/3.3.2-1.png) - **Round-Robin**: distributes data across different nodes in a cyclic. - **Range**: distributes data across different nodes based on the ranges of partitioning column values. As shown in the diagram, the ranges [1-3] and [4-6] correspond to different nodes. @@ -195,7 +196,7 @@ The number of buckets: By default, StarRocks automatically sets the number of bu > > Since v3.1, StarRocks's shared-data mode supports the time function expression and does not support the column expression. -Since v3.0, StarRocks has supported [expression partitioning](./expression_partitioning.md)](./expression_partitioning.md) (previously known as automatic partitioning) which is more flexible and easy to use. This partitioning method is suitable for most scenarios such as querying and managing data based on continuous date ranges or ENUM values. +Since v3.0, StarRocks has supported [expression partitioning](expression_partitioning.md)](./expression_partitioning.md) (previously known as automatic partitioning) which is more flexible and easy to use. This partitioning method is suitable for most scenarios such as querying and managing data based on continuous date ranges or ENUM values. You only need to configure a partition expression (a time function expression or a column expression) at table creation, and StarRocks will automatically create partitions during data loading. You no longer need to manually create numerous partitions in advance, nor configure dynamic partition properties. @@ -207,7 +208,7 @@ StarRocks stores data in the corresponding partitions based on the explicit mapp ##### Dynamic partitioning -[Dynamic partitioning](./dynamic_partitioning.md) related properties are configured at table creation. StarRocks automatically creates new partitions in advance and removes expired partitions to ensure data freshness, which implements time-to-live (TTL) management for partitions. +[Dynamic partitioning](dynamic_partitioning.md) related properties are configured at table creation. StarRocks automatically creates new partitions in advance and removes expired partitions to ensure data freshness, which implements time-to-live (TTL) management for partitions. Different from the automatic partition creation ability provided by the expression partitioning, dynamic partitioning can only periodically create new partitions based on the properties. If the new data does not belong to these partitions, an error is returned for the load job. However, the automatic partition creation ability provided by the expression partitioning can always create corresponding new partitions based on the loaded data. @@ -364,7 +365,7 @@ Multiple partitions can be created in batch at and after table creation. You ca #### List partitioning (since v3.1) -[List Partitioning](./list_partitioning.md) is suitable for accelerating queries and efficiently managing data based on enum values. It is especially useful for scenarios where a partition needs to include data with different values in a partitioning column. For example, if you frequently query and manage data based on countries and cities, you can use this partitioning method and select the `city` column as the partitioning column. In this case, one partition can contain data for various cities belonging to one country. +[List Partitioning](list_partitioning.md) is suitable for accelerating queries and efficiently managing data based on enum values. It is especially useful for scenarios where a partition needs to include data with different values in a partitioning column. For example, if you frequently query and manage data based on countries and cities, you can use this partitioning method and select the `city` column as the partitioning column. In this case, one partition can contain data for various cities belonging to one country. StarRocks stores data in the corresponding partitions based on the explicit mapping of the predefined value list for each partition. @@ -388,7 +389,7 @@ The following statement deletes partition `p1` from table `site_access`. > **NOTE** > -> This operation does not immediately delete data in a partition. Data is retained in the Trash for a period of time (one day by default). If a partition is mistakenly deleted, you can use the [RECOVER](../sql-reference/sql-statements/backup_restore/RECOVER.md) command to restore the partition and its data. +> This operation does not immediately delete data in a partition. Data is retained in the Trash for a period of time (one day by default). If a partition is mistakenly deleted, you can use the [RECOVER](../../sql-reference/sql-statements/backup_restore/RECOVER.md) command to restore the partition and its data. ```SQL ALTER TABLE site_access @@ -422,8 +423,8 @@ However, note that if you query massive amounts of data and frequently use certa #### Limits - You can only use random bucketing to create a Duplicate Key table. -- You cannot specify a table bucketed randomly to belong to a [Colocation Group](../using_starrocks/Colocate_join.md). -- [Spark Load](../loading/SparkLoad.md) cannot be used to load data into tables bucketed randomly. +- You cannot specify a table bucketed randomly to belong to a [Colocation Group](../../using_starrocks/Colocate_join.md). +- Spark Load cannot be used to load data into tables bucketed randomly. In the following CREATE TABLE example, the `DISTRIBUTED BY xxx` statement is not used, so StarRocks uses random bucketing by default, and automatically sets the number of buckets. @@ -572,7 +573,7 @@ Buckets reflect how data files are actually organized in StarRocks. :::warning - To enable the on-demand and dynamic increase of the number of buckets, you need to set the table property `PROPERTIES("bucket_size"="xxx")` to specify the size of a single bucket. If the data volume in a partition is small, you can set the `bucket_size` to 1 GB. Otherwise, you can set the `bucket_size` to 4 GB. - - Once the on-demand and dynamic increase of the number of buckets is enabled, and you need to rollback to version 3.1, you have to first delete the table which enables the dynamic increase in the number of buckets. Then you need to manually execute a metadata checkpoint using [ALTER SYSTEM CREATE IMAGE](../sql-reference/sql-statements/cluster-management/nodes_processes/ALTER_SYSTEM.md) before rolling back. + - Once the on-demand and dynamic increase of the number of buckets is enabled, and you need to rollback to version 3.1, you have to first delete the table which enables the dynamic increase in the number of buckets. Then you need to manually execute a metadata checkpoint using [ALTER SYSTEM CREATE IMAGE](../../sql-reference/sql-statements/cluster-management/nodes_processes/ALTER_SYSTEM.md) before rolling back. ::: @@ -685,7 +686,7 @@ Buckets reflect how data files are actually organized in StarRocks. :::warning - To enable the on-demand and dynamic increase of the number of buckets, you need to set the table property `PROPERTIES("bucket_size"="xxx")` to specify the size of a single bucket. If the data volume in a partition is small, you can set the `bucket_size` to 1 GB. Otherwise, you can set the `bucket_size` to 4 GB. - - Once the on-demand and dynamic increase of the number of buckets is enabled, and you need to rollback to version 3.1, you have to first delete the table which enables the dynamic increase in the number of buckets. Then you need to manually execute a metadata checkpoint using [ALTER SYSTEM CREATE IMAGE](../sql-reference/sql-statements/cluster-management/nodes_processes/ALTER_SYSTEM.md) before rolling back. + - Once the on-demand and dynamic increase of the number of buckets is enabled, and you need to rollback to version 3.1, you have to first delete the table which enables the dynamic increase in the number of buckets. Then you need to manually execute a metadata checkpoint using [ALTER SYSTEM CREATE IMAGE](../../sql-reference/sql-statements/cluster-management/nodes_processes/ALTER_SYSTEM.md) before rolling back. ::: @@ -757,7 +758,7 @@ Buckets reflect how data files are actually organized in StarRocks. #### View the number of buckets -After creating a table, you can execute [SHOW PARTITIONS](../sql-reference/sql-statements/table_bucket_part_index/SHOW_PARTITIONS.md) to view the number of buckets set by StarRocks for each partition. Tables configured with hash bucketing have a fixed number of buckets per partition. +After creating a table, you can execute [SHOW PARTITIONS](../../sql-reference/sql-statements/table_bucket_part_index/SHOW_PARTITIONS.md) to view the number of buckets set by StarRocks for each partition. Tables configured with hash bucketing have a fixed number of buckets per partition. :::info @@ -796,4 +797,4 @@ As query patterns and data volume evolve in business scenarios, the configuratio ALTER TABLE t ORDER BY k2, k1; ``` -For more information, see [ALTER TABLE](../sql-reference/sql-statements/table_bucket_part_index/ALTER_TABLE.md). +For more information, see [ALTER TABLE](../../sql-reference/sql-statements/table_bucket_part_index/ALTER_TABLE.md). diff --git a/docs/en/table_design/Temporary_partition.md b/docs/en/table_design/data_distribution/Temporary_partition.md similarity index 92% rename from docs/en/table_design/Temporary_partition.md rename to docs/en/table_design/data_distribution/Temporary_partition.md index 57c3a6084eb19..5de07a08291b0 100644 --- a/docs/en/table_design/Temporary_partition.md +++ b/docs/en/table_design/data_distribution/Temporary_partition.md @@ -1,5 +1,6 @@ --- displayed_sidebar: docs +sidebar_position: 40 --- # Temporary partition @@ -12,7 +13,7 @@ You can use the temporary partition feature in the following scenarios: - Atomic overwrite operation - If you need to rewrite the data in a partition while ensuring that the data can be queried during the rewriting process, you can first create a temporary partition based on the original formal partition, and load the new data into the temporary partition. Then you can use the replace operation to atomically replace the original formal partition with the temporary partition. For atomic overwrite operations on non-partitioned tables, see [ALTER TABLE - SWAP](../sql-reference/sql-statements/table_bucket_part_index/ALTER_TABLE.md#swap). + If you need to rewrite the data in a partition while ensuring that the data can be queried during the rewriting process, you can first create a temporary partition based on the original formal partition, and load the new data into the temporary partition. Then you can use the replace operation to atomically replace the original formal partition with the temporary partition. For atomic overwrite operations on non-partitioned tables, see [ALTER TABLE - SWAP](../../sql-reference/sql-statements/table_bucket_part_index/ALTER_TABLE.md#swap). - Adjust partition data query concurrency @@ -24,7 +25,7 @@ You can use the temporary partition feature in the following scenarios: ## Create temporary partitions -You can create one or more partitions at a time by using the [ALTER TABLE](../sql-reference/sql-statements/table_bucket_part_index/ALTER_TABLE.md) command. +You can create one or more partitions at a time by using the [ALTER TABLE](../../sql-reference/sql-statements/table_bucket_part_index/ALTER_TABLE.md) command. ### Syntax @@ -94,7 +95,7 @@ ADD TEMPORARY PARTITIONS START ("2020-04-01") END ("2021-01-01") EVERY (INTERVAL ## Show temporary partitions -You can view the temporary partitions by using the [SHOW TEMPORARY PARTITIONS](../sql-reference/sql-statements/table_bucket_part_index/SHOW_PARTITIONS.md) command. +You can view the temporary partitions by using the [SHOW TEMPORARY PARTITIONS](../../sql-reference/sql-statements/table_bucket_part_index/SHOW_PARTITIONS.md) command. ```SQL SHOW TEMPORARY PARTITIONS FROM [db_name.]table_name [WHERE] [ORDER BY] [LIMIT] @@ -114,7 +115,7 @@ INSERT INTO site_access TEMPORARY PARTITION (tp2) SELECT * FROM site_access_copy INSERT INTO site_access TEMPORARY PARTITION (tp3, tp4,...) SELECT * FROM site_access_copy PARTITION (p3, p4,...); ``` -For detailed syntax and parameter descriptions, see [INSERT INTO](../sql-reference/sql-statements/loading_unloading/INSERT.md). +For detailed syntax and parameter descriptions, see [INSERT INTO](../../sql-reference/sql-statements/loading_unloading/INSERT.md). ### Load data by using STREAM LOAD @@ -125,7 +126,7 @@ curl --location-trusted -u root: -H "label:123" -H "Expect:100-continue" -H "tem http://host:port/api/example_db/site_access/_stream_load ``` -For detailed syntax and parameter descriptions, see [STREAM LOAD](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md). +For detailed syntax and parameter descriptions, see [STREAM LOAD](../../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md). ### Load data by using BROKER LOAD @@ -145,7 +146,7 @@ WITH BROKER ); ``` -Note that `StorageCredentialParams` represents a group of authentication parameters which vary depending on the authentication method you choose. For detailed syntax and parameter descriptions, see [Broker Load](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md). +Note that `StorageCredentialParams` represents a group of authentication parameters which vary depending on the authentication method you choose. For detailed syntax and parameter descriptions, see [Broker Load](../../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md). ### Load data by using ROUTINE LOAD @@ -162,11 +163,11 @@ FROM KAFKA ); ``` -For detailed syntax and parameter descriptions, see [CREATE ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md). +For detailed syntax and parameter descriptions, see [CREATE ROUTINE LOAD](../../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md). ## Query data in temporary partitions -You can use the [SELECT](../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) statement to query data in specified temporary partitions. +You can use the [SELECT](../../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) statement to query data in specified temporary partitions. ```SQL SELECT * FROM @@ -191,7 +192,7 @@ ON site_access.site_id=site_access1.site_id and site_access.event_day=site_acces ## Replace original formal partitions with temporary partitions -You can use the [ALTER TABLE](../sql-reference/sql-statements/table_bucket_part_index/ALTER_TABLE.md) statement to replace the original formal partition with a temporary partition, thereby creating a new formal partition. +You can use the [ALTER TABLE](../../sql-reference/sql-statements/table_bucket_part_index/ALTER_TABLE.md) statement to replace the original formal partition with a temporary partition, thereby creating a new formal partition. > **NOTE** > diff --git a/docs/en/table_design/dynamic_partitioning.md b/docs/en/table_design/data_distribution/dynamic_partitioning.md similarity index 96% rename from docs/en/table_design/dynamic_partitioning.md rename to docs/en/table_design/data_distribution/dynamic_partitioning.md index f8fb2b6e33896..559297dbae544 100644 --- a/docs/en/table_design/dynamic_partitioning.md +++ b/docs/en/table_design/data_distribution/dynamic_partitioning.md @@ -1,5 +1,6 @@ --- displayed_sidebar: docs +sidebar_position: 30 --- # Dynamic partitioning @@ -8,7 +9,7 @@ StarRocks supports dynamic partitioning, which can automatically manage the time ## Enable dynamic partitioning -Take table `site_access` as an example. To enable dynamic partitioning, you need to configure the PROPERTIES parameter. For information about the configuration items, see [CREATE TABLE](../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md). +Take table `site_access` as an example. To enable dynamic partitioning, you need to configure the PROPERTIES parameter. For information about the configuration items, see [CREATE TABLE](../../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md). ```SQL CREATE TABLE site_access( @@ -75,7 +76,7 @@ SHOW PARTITIONS FROM site_access; ## Modify properties of dynamic partitioning -You can use the [ALTER TABLE](../sql-reference/sql-statements/table_bucket_part_index/ALTER_TABLE.md) statement to modify properties of dynamic partitioning, such as disabling dynamic partitioning. Take the following statement as an example. +You can use the [ALTER TABLE](../../sql-reference/sql-statements/table_bucket_part_index/ALTER_TABLE.md) statement to modify properties of dynamic partitioning, such as disabling dynamic partitioning. Take the following statement as an example. ```SQL ALTER TABLE site_access @@ -84,5 +85,5 @@ SET("dynamic_partition.enable"="false"); > Note: > -> - To check the properties of dynamic partitioning of a table, execute the [SHOW CREATE TABLE](../sql-reference/sql-statements/table_bucket_part_index/SHOW_CREATE_TABLE.md) statement. +> - To check the properties of dynamic partitioning of a table, execute the [SHOW CREATE TABLE](../../sql-reference/sql-statements/table_bucket_part_index/SHOW_CREATE_TABLE.md) statement. > - You can also use the ALTER TABLE statement to modify other properties of a table. diff --git a/docs/en/table_design/expression_partitioning.md b/docs/en/table_design/data_distribution/expression_partitioning.md similarity index 92% rename from docs/en/table_design/expression_partitioning.md rename to docs/en/table_design/data_distribution/expression_partitioning.md index 6264d0b47cec7..5f2f91be16a66 100644 --- a/docs/en/table_design/expression_partitioning.md +++ b/docs/en/table_design/data_distribution/expression_partitioning.md @@ -1,6 +1,7 @@ --- displayed_sidebar: docs description: Partition data in StarRocks +sidebar_position: 10 --- # Expression partitioning (recommended) @@ -13,7 +14,7 @@ You only need to specify a simple partition expression (either a time function e If you frequently query and manage data based on continuous time ranges, you only need to specify a date type (DATE or DATETIME) column as the partition column and specify year, month, day, or hour as the partition granularity in the time function expression. StarRocks will automatically create partitions and set the partitions' start and end dates or datetime based on the loaded data and partition expression. -However, in some special scenarios, such as partitioning historical data into partitions by month and recent data into partitions by day, you must use [range partitioning](./Data_distribution.md#range-partitioning) to create partitions. +However, in some special scenarios, such as partitioning historical data into partitions by month and recent data into partitions by day, you must use [range partitioning](Data_distribution.md#range-partitioning) to create partitions. ### Syntax @@ -32,7 +33,7 @@ expression ::= #### `expression` **Required**: YES
-**Description**: Currently, only the [date_trunc](../sql-reference/sql-functions/date-time-functions/date_trunc.md) and [time_slice](../sql-reference/sql-functions/date-time-functions/time_slice.md) functions are supported. If you use the function `time_slice`, you do not need to pass the `boundary` parameter. It is because in this scenario, the default and valid value for this parameter is `floor`, and the value cannot be `ceil`.
+**Description**: Currently, only the [date_trunc](../../sql-reference/sql-functions/date-time-functions/date_trunc.md) and [time_slice](../../sql-reference/sql-functions/date-time-functions/time_slice.md) functions are supported. If you use the function `time_slice`, you do not need to pass the `boundary` parameter. It is because in this scenario, the default and valid value for this parameter is `floor`, and the value cannot be `ceil`.
#### `time_unit` @@ -129,7 +130,7 @@ DISTRIBUTED BY HASH(event_day, site_id) If you frequently query and manage data of a specific type, you only need to specify the column representing the type as the partition column. StarRocks will automatically create partitions based on the partition column values of the loaded data. -However, in some special scenarios, such as when the table contains a column `city`, and you frequently query and manage data based on countries and cities. You must use [list partitioning](./list_partitioning.md) to store data of multiple cities within the same country in one partition. +However, in some special scenarios, such as when the table contains a column `city`, and you frequently query and manage data based on countries and cities. You must use [list partitioning](list_partitioning.md) to store data of multiple cities within the same country in one partition. ### Syntax @@ -149,7 +150,7 @@ partition_columns ::= #### `partition_columns` **Required**: YES
-**Description**: The names of partition columns.
  • The partition column values can be string (BINARY not supported), date or datetime, integer, and boolean values. The partition column allows `NULL` values.
  • Each partition can only contain data with the same value in the partition column. To include data with different values in a partition column in a partition, see [List partitioning](./list_partitioning.md).

+**Description**: The names of partition columns.
  • The partition column values can be string (BINARY not supported), date or datetime, integer, and boolean values. The partition column allows `NULL` values.
  • Each partition can only contain data with the same value in the partition column. To include data with different values in a partition column in a partition, see [List partitioning](list_partitioning.md).

### Usage notes @@ -185,7 +186,7 @@ INSERT INTO t_recharge_detail1 View the partitions. The result shows that StarRocks automatically creates a partition `p20220401_Houston1` based on the loaded data. During subsequent loading, data with the values `2022-04-01` and `Houston` in the partition columns `dt` and `city` are stored in this partition. :::tip -Each partition can only contain data with the specified one value for the partition column. To specify multiple values for a partition column in a partition, see [List partitions](./list_partitioning.md). +Each partition can only contain data with the specified one value for the partition column. To specify multiple values for a partition column in a partition, see [List partitions](list_partitioning.md). ::: ```SQL @@ -217,7 +218,7 @@ LastConsistencyCheckTime: NULL During data loading, StarRocks will automatically create partitions based on the loaded data and partition rule defined by the partition expression. -Note that if you use expression partitioning at table creation and need to use [INSERT OVERWRITE](../loading/InsertInto.md#overwrite-data-via-insert-overwrite-select) to overwrite data in a specific partition, whether the partition has been created or not, you currently need to explicitly provide a partition range in `PARTITION()`. This is different from [Range Partitioning](./Data_distribution.md#range-partitioning) or [List Partitioning](./list_partitioning.md), which allow you only to provide the partition name in `PARTITION ()`. +Note that if you use expression partitioning at table creation and need to use [INSERT OVERWRITE](../../loading/InsertInto.md#overwrite-data-via-insert-overwrite-select) to overwrite data in a specific partition, whether the partition has been created or not, you currently need to explicitly provide a partition range in `PARTITION()`. This is different from [Range Partitioning../Data_distribution.mdmd#range-partitioning) or [List Partitioning../list_partitioning.mdmd), which allow you only to provide the partition name in `PARTITION ()`. If you use a time function expression at table creation and want to overwrite data in a specific partition, you need to provide the starting date or datetime of that partition (the partition granularity configured at table creation). If the partition does not exist, it can be automatically created during data loading. @@ -254,4 +255,4 @@ MySQL > SHOW PARTITIONS FROM t_recharge_detail1; - Currently, using CTAS to create tables configured expression partitioning is not supported. - Currently, using Spark Load to load data to tables that use expression partitioning is not supported. - When the `ALTER TABLE DROP PARTITION ` statement is used to delete a partition created by using the column expression, data in the partition is directly removed and cannot be recovered. -- Currently, you cannot [backup and restore](../administration/management/Backup_and_restore.md) partitions created by the expression partitioning. +- Currently, you cannot [backup and restore](../../administration/management/Backup_and_restore.md) partitions created by the expression partitioning. diff --git a/docs/en/table_design/feature-support-data-distribution.md b/docs/en/table_design/data_distribution/feature-support-data-distribution.md similarity index 99% rename from docs/en/table_design/feature-support-data-distribution.md rename to docs/en/table_design/data_distribution/feature-support-data-distribution.md index a4101ae724cb3..b5cde96541a45 100644 --- a/docs/en/table_design/feature-support-data-distribution.md +++ b/docs/en/table_design/data_distribution/feature-support-data-distribution.md @@ -1,6 +1,7 @@ --- displayed_sidebar: docs sidebar_label: "Feature Support" +sidebar_position: 50 --- # Feature Support: Data Distribution diff --git a/docs/en/table_design/list_partitioning.md b/docs/en/table_design/data_distribution/list_partitioning.md similarity index 96% rename from docs/en/table_design/list_partitioning.md rename to docs/en/table_design/data_distribution/list_partitioning.md index 8d8a0f7490573..ad819526b1ec8 100644 --- a/docs/en/table_design/list_partitioning.md +++ b/docs/en/table_design/data_distribution/list_partitioning.md @@ -1,5 +1,6 @@ --- displayed_sidebar: docs +sidebar_position: 20 --- # List partitioning @@ -10,7 +11,7 @@ Since v3.1, StarRocks supports list partitioning. Data is partitioned based on a You need to explicitly specify the column values list in each partition. These values do not need to be continuous, unlike the continuous time or numeric range required in Range Partitioning. During data loading, StarRocks will store the data in the corresponding partition based on the mapping between the data's partitioning column values and the predefined column values for each partition. -![list_partitioning](../_assets/list_partitioning.png) +![list_partitioning](../../_assets/list_partitioning.png) List partitioning is suitable for storing data whose columns contain a small number of enum values, and you often query and manage data based on these enum values. For example, columns represent geographical locations, states, and categories. Each value in a column represents an independent category. By partitioning data based on enum values, you can improve query performance and facilitate data management. @@ -18,7 +19,7 @@ List partitioning is suitable for storing data whose columns contain a small num If a partition only needs to contain data with the same value of each partitioning column, it is recommended to use [expression partitioning](./expression_partitioning.md). -**Comparison between list partitioning and [expression partitioning](./expression_partitioning.md)** +**Comparison between list partitioning and [expression partitioning](expression_partitioning.md)** The main difference between list partitioning and expression partitioning (recommended) is that list partitioning requires you to manually create partitions one by one. On the other hand, expression partitioning can automatically create partitions during loading to simplify partitioning. And in most cases, expression partitioning can replace list partitioning. The specific comparison between the two is shown in the following table: @@ -111,5 +112,5 @@ DISTRIBUTED BY HASH(`id`); - List partitioning does support dynamic partitioning and creating multiple partitions at a time. - Currently, StarRocks's shared-data mode does not support this feature. - When the `ALTER TABLE DROP PARTITION ;` statement is used to delete a partition created by using list partitioning, data in the partition is directly removed and cannot be recovered. -- Currently you cannot [backup and restore](../administration/management/management.mdx) partitions created by the list partitioning. -- Currently, StarRocks does not support creating [asynchronous materialized views](../using_starrocks/Materialized_view.md) with base tables created with the list partitioning strategy. +- Currently you cannot backup and restore partitions created by the list partitioning. +- Currently, StarRocks does not support creating [asynchronous materialized views](../../using_starrocks/Materialized_view.md) with base tables created with the list partitioning strategy. diff --git a/docs/en/table_design/hybrid_table.md b/docs/en/table_design/hybrid_table.md index 54d7d07231b8f..df1675cb0b0d5 100644 --- a/docs/en/table_design/hybrid_table.md +++ b/docs/en/table_design/hybrid_table.md @@ -1,5 +1,6 @@ --- displayed_sidebar: docs +sidebar_position: 60 --- # [Preview] Hybrid row-column storage diff --git a/docs/en/table_design/indexes/Bitmap_index.md b/docs/en/table_design/indexes/Bitmap_index.md index f9ee299881760..a13a47c5b200e 100644 --- a/docs/en/table_design/indexes/Bitmap_index.md +++ b/docs/en/table_design/indexes/Bitmap_index.md @@ -1,5 +1,6 @@ --- displayed_sidebar: docs +sidebar_position: 20 --- # Bitmap indexes diff --git a/docs/en/table_design/indexes/Bloomfilter_index.md b/docs/en/table_design/indexes/Bloomfilter_index.md index 38f5291761fae..853f2f3f43f60 100644 --- a/docs/en/table_design/indexes/Bloomfilter_index.md +++ b/docs/en/table_design/indexes/Bloomfilter_index.md @@ -1,5 +1,6 @@ --- displayed_sidebar: docs +sidebar_position: 30 --- # Bloom filter indexes diff --git a/docs/en/table_design/indexes/Prefix_index_sort_key.md b/docs/en/table_design/indexes/Prefix_index_sort_key.md index ac69853927c27..6a078175f50f7 100644 --- a/docs/en/table_design/indexes/Prefix_index_sort_key.md +++ b/docs/en/table_design/indexes/Prefix_index_sort_key.md @@ -1,5 +1,6 @@ --- displayed_sidebar: docs +sidebar_position: 10 --- # Prefix indexes diff --git a/docs/en/table_design/indexes/_category_.yml b/docs/en/table_design/indexes/_category_.yml new file mode 100644 index 0000000000000..85cfeed6724de --- /dev/null +++ b/docs/en/table_design/indexes/_category_.yml @@ -0,0 +1,6 @@ +position: 50 # float position is supported +label: 'Indexes' +collapsible: true +collapsed: true +link: + type: generated-index diff --git a/docs/en/table_design/indexes/indexes_overview.md b/docs/en/table_design/indexes/indexes.md similarity index 99% rename from docs/en/table_design/indexes/indexes_overview.md rename to docs/en/table_design/indexes/indexes.md index ff3b9fb8095c7..b14f1b888b525 100644 --- a/docs/en/table_design/indexes/indexes_overview.md +++ b/docs/en/table_design/indexes/indexes.md @@ -1,5 +1,6 @@ --- displayed_sidebar: docs +sidebar_position: 5 --- # Indexes diff --git a/docs/en/table_design/catalog_db_tbl.md b/docs/en/table_design/table_design.md similarity index 97% rename from docs/en/table_design/catalog_db_tbl.md rename to docs/en/table_design/table_design.md index d83c93e40c5e9..00b630698190b 100644 --- a/docs/en/table_design/catalog_db_tbl.md +++ b/docs/en/table_design/table_design.md @@ -1,5 +1,6 @@ --- displayed_sidebar: docs +sidebar_position: 5 --- # Catalogs, databases, and tables @@ -52,6 +53,6 @@ Views, or logical views, are virtual tables that do not hold any data. Views onl Privileges determine which users can perform which operations on which objects. StarRocks adopts two types of privilege models: identity-based access control and role-based access control. You can first assign privileges to roles, and then assign roles to users. In this case, privileges are passed to users through roles. Or, you can directly assign privileges to user identities. -## [Data storage in storage-compute separation architecture](../introduction/Architecture.md#storage-compute-separation) +## Data storage in storage-compute separation architecture Since v3.0, StarRocks introduces the new storage-compute separation (shared-data) architecture. Data storage is separated from BEs. Data is persistently stored in remote object storage or HDFS, while local disks are used for caching hot data to accelerate queries. diff --git a/docs/en/table_design/table_types/_category_.yml b/docs/en/table_design/table_types/_category_.yml new file mode 100644 index 0000000000000..5c8c1e4ea516b --- /dev/null +++ b/docs/en/table_design/table_types/_category_.yml @@ -0,0 +1,7 @@ +position: 20 # float position is supported +label: 'Table types' +collapsible: true +collapsed: true +link: + type: doc + id: table_types diff --git a/docs/en/table_design/table_types/aggregate_table.md b/docs/en/table_design/table_types/aggregate_table.md index fbaf7be4b359e..0c8cea30c132e 100644 --- a/docs/en/table_design/table_types/aggregate_table.md +++ b/docs/en/table_design/table_types/aggregate_table.md @@ -1,5 +1,6 @@ --- displayed_sidebar: docs +sidebar_position: 40 --- # Aggregate table @@ -70,8 +71,8 @@ PROPERTIES ( > **NOTICE** > -> - When you create a table, you must specify the bucketing column by using the `DISTRIBUTED BY HASH` clause. For detailed information, see [bucketing](../Data_distribution.md#bucketing). -> - Since v2.5.7, StarRocks can automatically set the number of buckets (BUCKETS) when you create a table or add a partition. You no longer need to manually set the number of buckets. For detailed information, see [set the number of buckets](../Data_distribution.md#set-the-number-of-buckets). +> - When you create a table, you must specify the bucketing column by using the `DISTRIBUTED BY HASH` clause. For detailed information, see [bucketing](../data_distribution/Data_distribution.md#bucketing). +> - Since v2.5.7, StarRocks can automatically set the number of buckets (BUCKETS) when you create a table or add a partition. You no longer need to manually set the number of buckets. For detailed information, see [set the number of buckets](../data_distribution/Data_distribution.md#set-the-number-of-buckets). ## Usage notes diff --git a/docs/en/table_design/table_types/duplicate_key_table.md b/docs/en/table_design/table_types/duplicate_key_table.md index fe28f81753952..4c16dbf6da9c3 100644 --- a/docs/en/table_design/table_types/duplicate_key_table.md +++ b/docs/en/table_design/table_types/duplicate_key_table.md @@ -1,5 +1,6 @@ --- displayed_sidebar: docs +sidebar_position: 30 --- # Duplicate Key table @@ -36,8 +37,8 @@ DISTRIBUTED BY HASH(user_id); > **NOTICE** > -> - When you create a table, you must specify the bucketing column by using the `DISTRIBUTED BY HASH` clause. For detailed information, see [bucketing](../Data_distribution.md#bucketing). -> - Since v2.5.7, StarRocks can automatically set the number of buckets (BUCKETS) when you create a table or add a partition. You no longer need to manually set the number of buckets. For detailed information, see [set the number of buckets](../Data_distribution.md#set-the-number-of-buckets). +> - When you create a table, you must specify the bucketing column by using the `DISTRIBUTED BY HASH` clause. For detailed information, see [bucketing](../data_distribution/Data_distribution.md#bucketing). +> - Since v2.5.7, StarRocks can automatically set the number of buckets (BUCKETS) when you create a table or add a partition. You no longer need to manually set the number of buckets. For detailed information, see [set the number of buckets](../data_distribution/Data_distribution.md#set-the-number-of-buckets). ## Usage notes diff --git a/docs/en/table_design/table_types/primary_key_table.md b/docs/en/table_design/table_types/primary_key_table.md index ddb4a02732dcc..73be0ec8a2362 100644 --- a/docs/en/table_design/table_types/primary_key_table.md +++ b/docs/en/table_design/table_types/primary_key_table.md @@ -1,5 +1,6 @@ --- displayed_sidebar: docs +sidebar_position: 20 --- # Primary Key table @@ -101,7 +102,7 @@ For example, the `order_id` field in the order table can uniquely identify data Since v3.0, the sort key of a Primary Key table is decoupled from the table's primary key. Therefore, you can choose columns frequently used as query filter conditions to form the sort key. For example, if you frequently query product sales performance based on the combination of two dimensions, order date and merchant, you can specify the sort key as `dt` and `merchant_id` using the `ORDER BY (dt,merchant_id)` clause. -Note that if you use [data distribution strategies](../Data_distribution.md), the Primary Key table currently requires the primary key to include partitioning and bucketing columns. For example, the data distribution strategy uses `dt` as the partitioning column and `merchant_id` as the hash bucketing column. The primary key also needs to include `dt` and `merchant_id`. +Note that if you use [data distribution strategies](../data_distribution/Data_distribution.md), the Primary Key table currently requires the primary key to include partitioning and bucketing columns. For example, the data distribution strategy uses `dt` as the partitioning column and `merchant_id` as the hash bucketing column. The primary key also needs to include `dt` and `merchant_id`. In summary, the CREATE TABLE statement for the above order table can be as follows: diff --git a/docs/en/table_design/table_types/table_capabilities.md b/docs/en/table_design/table_types/table_capabilities.md index 3985a10687516..0c2172d06773d 100644 --- a/docs/en/table_design/table_types/table_capabilities.md +++ b/docs/en/table_design/table_types/table_capabilities.md @@ -1,5 +1,6 @@ --- displayed_sidebar: docs +sidebar_position: 10 --- # Capabilities of different table types diff --git a/docs/en/table_design/table_types/unique_key_table.md b/docs/en/table_design/table_types/unique_key_table.md index 6e6cc73f1255c..eedb913187b09 100644 --- a/docs/en/table_design/table_types/unique_key_table.md +++ b/docs/en/table_design/table_types/unique_key_table.md @@ -1,5 +1,6 @@ --- displayed_sidebar: docs +sidebar_position: 50 --- # Unique Key table @@ -52,8 +53,8 @@ DISTRIBUTED BY HASH(order_id); > **NOTICE** > -> - When you create a table, you must specify the bucketing column by using the `DISTRIBUTED BY HASH` clause. For detailed information, see [bucketing](../Data_distribution.md#bucketing). -> - Since v2.5.7, StarRocks can automatically set the number of buckets (BUCKETS) when you create a table or add a partition. You no longer need to manually set the number of buckets. For detailed information, see [set the number of buckets](../Data_distribution.md#set-the-number-of-buckets). +> - When you create a table, you must specify the bucketing column by using the `DISTRIBUTED BY HASH` clause. For detailed information, see [bucketing](../data_distribution/Data_distribution.md#bucketing). +> - Since v2.5.7, StarRocks can automatically set the number of buckets (BUCKETS) when you create a table or add a partition. You no longer need to manually set the number of buckets. For detailed information, see [set the number of buckets](../data_distribution/Data_distribution.md#set-the-number-of-buckets). ## Usage notes diff --git a/docs/en/using_starrocks/block_cache.md b/docs/en/using_starrocks/block_cache.md index 1d4923279ab7b..1c200c264efb4 100644 --- a/docs/en/using_starrocks/block_cache.md +++ b/docs/en/using_starrocks/block_cache.md @@ -83,8 +83,6 @@ You can download the following Grafana Dashboard templates based on your StarRoc - [Dashboard template for StarRocks shared-data cluster on virtual machines](http://starrocks-thirdparty.oss-cn-zhangjiakou.aliyuncs.com/StarRocks-Shared_data-for-vm.json) - [Dashboard template for StarRocks shared-data cluster on Kubernetes](http://starrocks-thirdparty.oss-cn-zhangjiakou.aliyuncs.com/StarRocks-Shared_data-for-k8s.json) -For more instructions on deploying monitoring and alert services for StarRocks, see [Monitor and alert](../administration/management/monitoring/Monitor_and_Alert.md). - ### Important metrics #### fslib read io_latency diff --git a/docs/en/using_starrocks/data_lake_query_acceleration_with_materialized_views.md b/docs/en/using_starrocks/data_lake_query_acceleration_with_materialized_views.md index fc748865fad7e..97b87075139bb 100644 --- a/docs/en/using_starrocks/data_lake_query_acceleration_with_materialized_views.md +++ b/docs/en/using_starrocks/data_lake_query_acceleration_with_materialized_views.md @@ -180,7 +180,7 @@ In scenarios involving query rewriting, if you use a very complex query statemen ## Best practices -In real-world business scenarios, you can identify queries with high execution latency and resource consumption by analyzing audit logs or [big query logs](../administration/management/monitor_manage_big_queries.md#analyze-big-query-logs). You can further use [query profiles](../administration/query_profile_overview.md) to pinpoint the specific stages where the query is slow. The following sections provide instructions and examples on how to boost data lake query performance with materialized views. +In real-world business scenarios, you can identify queries with high execution latency and resource consumption by analyzing audit logs or big query logs. You can further use [query profiles](../administration/query_profile_overview.md) to pinpoint the specific stages where the query is slow. The following sections provide instructions and examples on how to boost data lake query performance with materialized views. ### Case One: Accelerate join calculation in data lake diff --git a/docs/zh/administration/management/Backup_and_restore.md b/docs/zh/administration/management/Backup_and_restore.md index b1ccffcc609e9..e9d70c898dbf8 100644 --- a/docs/zh/administration/management/Backup_and_restore.md +++ b/docs/zh/administration/management/Backup_and_restore.md @@ -25,7 +25,7 @@ StarRocks 支持在以下外部存储系统中备份数据: StarRocks 支持以数据库、表、或分区为粒度全量备份数据。 -当表的数据量很大时,建议您按分区分别执行,以降低失败重试的代价。如果您需要对数据进行定期备份,建议您在建表时制定[动态分区](../../table_design/dynamic_partitioning.md)策略,从而可以在后期运维过程中,仅定期备份新增分区中的数据。 +当表的数据量很大时,建议您按分区分别执行,以降低失败重试的代价。如果您需要对数据进行定期备份,建议您在建表时制定[动态分区](../../table_design/data_distribution/dynamic_partitioning.md)策略,从而可以在后期运维过程中,仅定期备份新增分区中的数据。 ### 创建仓库 diff --git a/docs/zh/administration/management/FE_configuration.md b/docs/zh/administration/management/FE_configuration.md index 1793557a14a9f..925de52aa191f 100644 --- a/docs/zh/administration/management/FE_configuration.md +++ b/docs/zh/administration/management/FE_configuration.md @@ -2291,7 +2291,7 @@ ADMIN SET FRONTEND CONFIG ("key" = "value"); - 单位:- - 是否动态:是 - 描述:是否开启自动设置分桶功能。 - - 设置为 `true` 表示开启,您在建表或新增分区时无需指定分桶数目,StarRocks 自动决定分桶数量。自动设置分桶数目的策略,请参见[设置分桶数量](../../table_design/Data_distribution.md#设置分桶数量)。 + - 设置为 `true` 表示开启,您在建表或新增分区时无需指定分桶数目,StarRocks 自动决定分桶数量。自动设置分桶数目的策略,请参见[设置分桶数量](../../table_design/data_distribution/Data_distribution.md#设置分桶数量)。 - 设置为 `false` 表示关闭,您在建表时需要手动指定分桶数量。 - 新增分区时,如果您不指定分桶数量,则新分区的分桶数量继承建表时候的分桶数量。当然您也可以手动指定新增分区的分桶数量。 - 引入版本:v2.5.7 diff --git a/docs/zh/loading/BrokerLoad.md b/docs/zh/loading/BrokerLoad.md index 753823950cf3d..384d90bc98b24 100644 --- a/docs/zh/loading/BrokerLoad.md +++ b/docs/zh/loading/BrokerLoad.md @@ -101,7 +101,7 @@ Broker Load 支持从如下外部存储系统导入数据: > **说明** > - > 自 2.5.7 版本起,StarRocks 支持在建表和新增分区时自动设置分桶数量 (BUCKETS),您无需手动设置分桶数量。更多信息,请参见 [设置分桶数量](../table_design/Data_distribution.md#设置分桶数量)。 + > 自 2.5.7 版本起,StarRocks 支持在建表和新增分区时自动设置分桶数量 (BUCKETS),您无需手动设置分桶数量。更多信息,请参见 [设置分桶数量](../table_design/data_distribution/Data_distribution.md#设置分桶数量)。 a. 创建一张名为 `table1` 的主键表。表包含 `id`、`name` 和 `score` 三列,分别代表用户 ID、用户名称和用户得分,主键为 `id` 列,如下所示: diff --git a/docs/zh/loading/Etl_in_loading.md b/docs/zh/loading/Etl_in_loading.md index 777893b32593c..171654c87a8a2 100644 --- a/docs/zh/loading/Etl_in_loading.md +++ b/docs/zh/loading/Etl_in_loading.md @@ -74,7 +74,7 @@ StarRocks 支持在导入数据的过程中实现数据转换。 > **说明** > - > 自 2.5.7 版本起,StarRocks 支持在建表和新增分区时自动设置分桶数量 (BUCKETS),您无需手动设置分桶数量。更多信息,请参见 [设置分桶数量](../table_design/Data_distribution.md#设置分桶数量)。 + > 自 2.5.7 版本起,StarRocks 支持在建表和新增分区时自动设置分桶数量 (BUCKETS),您无需手动设置分桶数量。更多信息,请参见 [设置分桶数量](../table_design/data_distribution/Data_distribution.md#设置分桶数量)。 a. 创建一张名为 `table1` 的表,包含 `user_id`、`event_date` 和 `event_type` 三列,如下所示: diff --git a/docs/zh/loading/Flink_cdc_load.md b/docs/zh/loading/Flink_cdc_load.md index fc17e9e18ddc7..5facc994a4e93 100644 --- a/docs/zh/loading/Flink_cdc_load.md +++ b/docs/zh/loading/Flink_cdc_load.md @@ -292,7 +292,7 @@ StarRocks 支持多种方式将 MySQL 的数据实时同步至 StarRocks,支 > **注意** > - > 自 2.5.7 版本起,StarRocks 支持在建表和新增分区时自动设置分桶数量 (BUCKETS),您无需手动设置分桶数量。更多信息,请参见 [设置分桶数量](../table_design/Data_distribution.md#设置分桶数量)。 + > 自 2.5.7 版本起,StarRocks 支持在建表和新增分区时自动设置分桶数量 (BUCKETS),您无需手动设置分桶数量。更多信息,请参见 [设置分桶数量](../table_design/data_distribution/Data_distribution.md#设置分桶数量)。 ## 同步数据 diff --git a/docs/zh/loading/InsertInto.md b/docs/zh/loading/InsertInto.md index 9447b32e8b6a1..656b5184826ba 100644 --- a/docs/zh/loading/InsertInto.md +++ b/docs/zh/loading/InsertInto.md @@ -12,9 +12,9 @@ import InsertPrivNote from '../_assets/commonMarkdown/insertPrivNote.md' 2.4 版本中,StarRocks 进一步支持通过 INSERT OVERWRITE 语句批量**覆盖写入**目标表。INSERT OVERWRITE 语句通过整合以下三部分操作来实现覆盖写入: -1. 为目标分区[创建临时分区](../table_design/Temporary_partition.md#创建临时分区) -2. [写入数据至临时分区](../table_design/Temporary_partition.md#导入数据至临时分区) -3. [使用临时分区原子替换目标分区](../table_design/Temporary_partition.md#使用临时分区进行替换) +1. 为目标分区[创建临时分区](../table_design/data_distribution/Temporary_partition.md#创建临时分区) +2. [写入数据至临时分区](../table_design/data_distribution/Temporary_partition.md#导入数据至临时分区) +3. [使用临时分区原子替换目标分区](../table_design/data_distribution/Temporary_partition.md#使用临时分区进行替换) 如果您希望在替换前验证数据,可以根据以上步骤自行实现覆盖写入数据。 @@ -109,7 +109,7 @@ DISTRIBUTED BY HASH(user); > **注意** > -> 自 2.5.7 版本起,StarRocks 支持在建表和新增分区时自动设置分桶数量 (BUCKETS),您无需手动设置分桶数量。更多信息,请参见 [设置分桶数量](../table_design/Data_distribution.md#设置分桶数量)。 +> 自 2.5.7 版本起,StarRocks 支持在建表和新增分区时自动设置分桶数量 (BUCKETS),您无需手动设置分桶数量。更多信息,请参见 [设置分桶数量](../table_design/data_distribution/Data_distribution.md#设置分桶数量)。 ## 通过 INSERT INTO VALUES 语句导入数据 diff --git a/docs/zh/loading/Load_to_Primary_Key_tables.md b/docs/zh/loading/Load_to_Primary_Key_tables.md index 8591381c29876..f969dda3d6a22 100644 --- a/docs/zh/loading/Load_to_Primary_Key_tables.md +++ b/docs/zh/loading/Load_to_Primary_Key_tables.md @@ -106,7 +106,7 @@ StarRocks 的主键表目前支持 UPSERT 和 DELETE 操作,不支持区分 IN > **说明** > - > 自 2.5.7 版本起,StarRocks 支持在建表和新增分区时自动设置分桶数量 (BUCKETS),您无需手动设置分桶数量。更多信息,请参见 [设置分桶数量](../table_design/Data_distribution.md#设置分桶数量)。 + > 自 2.5.7 版本起,StarRocks 支持在建表和新增分区时自动设置分桶数量 (BUCKETS),您无需手动设置分桶数量。更多信息,请参见 [设置分桶数量](../table_design/data_distribution/Data_distribution.md#设置分桶数量)。 b. 向 `table1` 表中插入一条数据,如下所示: @@ -267,7 +267,7 @@ SELECT * FROM table1; > **说明** > - > 自 2.5.7 版本起,StarRocks 支持在建表和新增分区时自动设置分桶数量 (BUCKETS),您无需手动设置分桶数量。更多信息,请参见 [设置分桶数量](../table_design/Data_distribution.md#设置分桶数量)。 + > 自 2.5.7 版本起,StarRocks 支持在建表和新增分区时自动设置分桶数量 (BUCKETS),您无需手动设置分桶数量。更多信息,请参见 [设置分桶数量](../table_design/data_distribution/Data_distribution.md#设置分桶数量)。 b. 向 `table2` 表中插入数据,如下所示: @@ -379,7 +379,7 @@ SELECT * FROM table2; > **说明** > - > 自 2.5.7 版本起,StarRocks 支持在建表和新增分区时自动设置分桶数量 (BUCKETS),您无需手动设置分桶数量。更多信息,请参见 [设置分桶数量](../table_design/Data_distribution.md#设置分桶数量)。 + > 自 2.5.7 版本起,StarRocks 支持在建表和新增分区时自动设置分桶数量 (BUCKETS),您无需手动设置分桶数量。更多信息,请参见 [设置分桶数量](../table_design/data_distribution/Data_distribution.md#设置分桶数量)。 b. 向 `table3` 表中插入数据,如下所示: @@ -503,7 +503,7 @@ SELECT * FROM table3; > **说明** > - > 自 2.5.7 版本起,StarRocks 支持在建表和新增分区时自动设置分桶数量 (BUCKETS),您无需手动设置分桶数量。更多信息,请参见 [设置分桶数量](../table_design/Data_distribution.md#设置分桶数量)。 + > 自 2.5.7 版本起,StarRocks 支持在建表和新增分区时自动设置分桶数量 (BUCKETS),您无需手动设置分桶数量。更多信息,请参见 [设置分桶数量](../table_design/data_distribution/Data_distribution.md#设置分桶数量)。 b. 向 `table4` 表中插入一条数据,如下所示: @@ -639,7 +639,7 @@ SELECT * FROM table4; > **说明** > - > 自 2.5.7 版本起,StarRocks 支持在建表和新增分区时自动设置分桶数量 (BUCKETS),您无需手动设置分桶数量。更多信息,请参见 [设置分桶数量](../table_design/Data_distribution.md#设置分桶数量)。 + > 自 2.5.7 版本起,StarRocks 支持在建表和新增分区时自动设置分桶数量 (BUCKETS),您无需手动设置分桶数量。更多信息,请参见 [设置分桶数量](../table_design/data_distribution/Data_distribution.md#设置分桶数量)。 b. 向 `table5` 表中插入两条数据,如下所示: diff --git a/docs/zh/loading/RoutineLoad.md b/docs/zh/loading/RoutineLoad.md index 42a7d9607c409..21c5d9a308b10 100644 --- a/docs/zh/loading/RoutineLoad.md +++ b/docs/zh/loading/RoutineLoad.md @@ -120,7 +120,7 @@ DISTRIBUTED BY HASH(`order_id`); > **注意** > -> 自 2.5.7 版本起,StarRocks 支持在建表和新增分区时自动设置分桶数量 (BUCKETS),您无需手动设置分桶数量。更多信息,请参见 [设置分桶数量](../table_design/Data_distribution.md#设置分桶数量)。 +> 自 2.5.7 版本起,StarRocks 支持在建表和新增分区时自动设置分桶数量 (BUCKETS),您无需手动设置分桶数量。更多信息,请参见 [设置分桶数量](../table_design/data_distribution/Data_distribution.md#设置分桶数量)。 #### 导入作业 @@ -233,7 +233,7 @@ DISTRIBUTED BY HASH(`commodity_id`); > **注意** > -> 自 2.5.7 版本起,StarRocks 支持在建表和新增分区时自动设置分桶数量 (BUCKETS),您无需手动设置分桶数量。更多信息,请参见 [设置分桶数量](../table_design/Data_distribution.md#设置分桶数量)。 +> 自 2.5.7 版本起,StarRocks 支持在建表和新增分区时自动设置分桶数量 (BUCKETS),您无需手动设置分桶数量。更多信息,请参见 [设置分桶数量](../table_design/data_distribution/Data_distribution.md#设置分桶数量)。 #### 导入作业 @@ -324,7 +324,7 @@ DISTRIBUTED BY HASH(`id`); > **注意** > -> 自 2.5.7 版本起,StarRocks 支持在建表和新增分区时自动设置分桶数量 (BUCKETS),您无需手动设置分桶数量。更多信息,请参见 [设置分桶数量](../table_design/Data_distribution.md#设置分桶数量)。 +> 自 2.5.7 版本起,StarRocks 支持在建表和新增分区时自动设置分桶数量 (BUCKETS),您无需手动设置分桶数量。更多信息,请参见 [设置分桶数量](../table_design/data_distribution/Data_distribution.md#设置分桶数量)。 #### 导入作业 diff --git a/docs/zh/loading/StreamLoad.md b/docs/zh/loading/StreamLoad.md index 6bf2512b12508..9b0367a3cfc7f 100644 --- a/docs/zh/loading/StreamLoad.md +++ b/docs/zh/loading/StreamLoad.md @@ -106,7 +106,7 @@ DISTRIBUTED BY HASH(`id`); :::note -自 2.5.7 版本起,StarRocks 支持在建表和新增分区时自动设置分桶数量 (BUCKETS),您无需手动设置分桶数量。更多信息,请参见 [设置分桶数量](../table_design/Data_distribution.md#设置分桶数量)。 +自 2.5.7 版本起,StarRocks 支持在建表和新增分区时自动设置分桶数量 (BUCKETS),您无需手动设置分桶数量。更多信息,请参见 [设置分桶数量](../table_design/data_distribution/Data_distribution.md#设置分桶数量)。 ::: @@ -185,7 +185,7 @@ DISTRIBUTED BY HASH(`id`); :::note -自 2.5.7 版本起,StarRocks 支持在建表和新增分区时自动设置分桶数量 (BUCKETS),您无需手动设置分桶数量。更多信息,请参见 [设置分桶数量](../table_design/Data_distribution.md#设置分桶数量)。 +自 2.5.7 版本起,StarRocks 支持在建表和新增分区时自动设置分桶数量 (BUCKETS),您无需手动设置分桶数量。更多信息,请参见 [设置分桶数量](../table_design/data_distribution/Data_distribution.md#设置分桶数量)。 ::: diff --git a/docs/zh/release_notes/release-2.4.md b/docs/zh/release_notes/release-2.4.md index 26addda65960a..28bb0cf5fdfd2 100644 --- a/docs/zh/release_notes/release-2.4.md +++ b/docs/zh/release_notes/release-2.4.md @@ -219,7 +219,7 @@ displayed_sidebar: docs - 统计信息支持直方图,并进一步完善全量统计信息采集。相关文档,请参见[CBO统计信息](../using_starrocks/Cost_based_optimizer.md)。 -- 支持 Tablet 自适应多线程 Scan,降低 Scan 性能对同磁盘 Tablet 数量的依赖,从而可以简化分桶数量的设定。相关文档,请参见[确定分桶数量](../table_design/Data_distribution.md#确定分桶数量)。 +- 支持 Tablet 自适应多线程 Scan,降低 Scan 性能对同磁盘 Tablet 数量的依赖,从而可以简化分桶数量的设定。相关文档,请参见[确定分桶数量](../table_design/data_distribution/Data_distribution.md#确定分桶数量)。 - 支持查询 Apache Hive 中的压缩文本(.txt)文件。 diff --git a/docs/zh/sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md b/docs/zh/sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md index 1a61400993eb7..1f50ee9f5daca 100644 --- a/docs/zh/sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md +++ b/docs/zh/sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md @@ -118,7 +118,7 @@ INTO TABLE - `TEMPORARY PARTITION` - 指定要把数据导入哪些[临时分区](../../../table_design/Temporary_partition.md)。 + 指定要把数据导入哪些[临时分区](../../../table_design/data_distribution/Temporary_partition.md)。 - `COLUMNS TERMINATED BY` diff --git a/docs/zh/sql-reference/sql-statements/loading_unloading/INSERT.md b/docs/zh/sql-reference/sql-statements/loading_unloading/INSERT.md index d9341a246198f..f24f3cd4f4602 100644 --- a/docs/zh/sql-reference/sql-statements/loading_unloading/INSERT.md +++ b/docs/zh/sql-reference/sql-statements/loading_unloading/INSERT.md @@ -39,7 +39,7 @@ displayed_sidebar: docs | OVERWRITE | 将数据覆盖写入目标表。 | | table_name | 导入数据的目标表。可以为 `db_name.table_name` 形式。 | | PARTITION | 导入的目标分区。此参数必须是目标表中存在的分区,多个分区名称用逗号(,)分隔。如果指定该参数,数据只会被导入相应分区内。如果未指定,则默认将数据导入至目标表的所有分区。 | -| TEMPORARY PARTITION | 指定要把数据导入哪些[临时分区](../../../table_design/Temporary_partition.md)。| +| TEMPORARY PARTITION | 指定要把数据导入哪些[临时分区](../../../table_design/data_distribution/Temporary_partition.md)。| | label | 导入作业的标识,数据库内唯一。如果未指定,StarRocks 会自动为作业生成一个 Label。建议您指定 Label。否则,如果当前导入作业因网络错误无法返回结果,您将无法得知该导入操作是否成功。如果指定了 Label,可以通过 SQL 命令 `SHOW LOAD WHERE label="label";` 查看任务结果。关于 Label 命名要求,参见[系统限制](../../System_limit.md)。 | | column_name | 导入的目标列,必须是目标表中存在的列。该参数的对应关系与列名无关,但与其顺序一一对应。如果不指定目标列,默认为目标表中的所有列。如果源表中的某个列在目标列不存在,则写入默认值。如果当前列没有默认值,导入作业会失败。如果查询语句的结果列类型与目标列的类型不一致,会进行隐式转化,如果不能进行转化,那么 INSERT INTO 语句会报语法解析错误。 | | expression | 表达式,用以为对应列赋值。 | diff --git a/docs/zh/sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md b/docs/zh/sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md index f3b20ad7f9c9b..b7f8ae6d7831d 100644 --- a/docs/zh/sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md +++ b/docs/zh/sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md @@ -97,7 +97,7 @@ http://:/api///_stream_load | file_path | 是 | 指定源数据文件的保存路径。文件名里可选包含或者不包含扩展名。 | | format | 否 | 指定待导入数据的格式。取值包括 `CSV` 和 `JSON`。默认值:`CSV`。 | | partitions | 否 | 指定要把数据导入哪些分区。如果不指定该参数,则默认导入到 StarRocks 表所在的所有分区中。 | -| temporary_partitions | 否 | 指定要把数据导入哪些[临时分区](../../../table_design/Temporary_partition.md)。| +| temporary_partitions | 否 | 指定要把数据导入哪些[临时分区](../../../table_design/data_distribution/Temporary_partition.md)。| | columns | 否 | 指定源数据文件和 StarRocks 表之间的列对应关系。如果源数据文件中的列与 StarRocks 表中的列按顺序一一对应,则不需要指定 `columns` 参数。您可以通过 `columns` 参数实现数据转换。例如,要导入一个 CSV 格式的数据文件,文件中有两列,分别可以对应到目标 StarRocks 表的 `id` 和 `city` 两列。如果要实现把数据文件中第一列的数据乘以 100 以后再落入 StarRocks 表的转换,可以指定 `"columns: city,tmp_id, id = tmp_id * 100"`。具体请参见本文“[列映射](#列映射)”章节。 | #### CSV 适用参数 diff --git a/docs/zh/sql-reference/sql-statements/materialized_view/CREATE_MATERIALIZED_VIEW.md b/docs/zh/sql-reference/sql-statements/materialized_view/CREATE_MATERIALIZED_VIEW.md index 4ab3742ea3b76..8b0dc7647d215 100644 --- a/docs/zh/sql-reference/sql-statements/materialized_view/CREATE_MATERIALIZED_VIEW.md +++ b/docs/zh/sql-reference/sql-statements/materialized_view/CREATE_MATERIALIZED_VIEW.md @@ -184,11 +184,11 @@ AS DISTRIBUTED BY HASH ([, ...]) [BUCKETS ] ``` - 更多信息,请参见 [分桶](../../../table_design/Data_distribution.md#分桶)。 + 更多信息,请参见 [分桶](../../../table_design/data_distribution/Data_distribution.md#分桶)。 > **说明** > - > 自 2.5.7 版本起,StarRocks 支持在建表和新增分区时自动设置分桶数量 (BUCKETS),您无需手动设置分桶数量。更多信息,请参见 [设置分桶数量](../../../table_design/Data_distribution.md#设置分桶数量)。 + > 自 2.5.7 版本起,StarRocks 支持在建表和新增分区时自动设置分桶数量 (BUCKETS),您无需手动设置分桶数量。更多信息,请参见 [设置分桶数量](../../../table_design/data_distribution/Data_distribution.md#设置分桶数量)。 - **随机分桶**: @@ -202,7 +202,7 @@ AS > > 采用随机分桶方式的异步物化视图不支持设置 Colocation Group。 - 更多信息,请参见 [随机分桶](../../../table_design/Data_distribution.md#随机分桶自-v31)。 + 更多信息,请参见 [随机分桶](../../../table_design/data_distribution/Data_distribution.md#随机分桶自-v31)。 **refresh_moment**(选填) @@ -255,7 +255,7 @@ AS - `storage_medium`:存储介质类型。有效值:`HDD` 和 `SSD`。 - `storage_cooldown_time`: 当设置存储介质为 SSD 时,指定该分区在该时间点之后从 SSD 降冷到 HDD,设置的时间必须大于当前时间。如不指定该属性,默认不进行自动降冷。取值格式为:"yyyy-MM-dd HH:mm:ss"。 - `partition_ttl`: 物化视图分区的生存时间 (TTL)。数据在指定的时间范围内的分区将被保留,过期的分区将被自动删除。单位:`YEAR`、`MONTH`、`DAY`、`HOUR` 和 `MINUTE`。例如,您可以将此属性设置为 `2 MONTH`(2个月)。建议您使用此属性,不推荐使用 `partition_ttl_number`。该属性自 v3.1.5 起支持。 -- `partition_ttl_number`:需要保留的最近的物化视图分区数量。对于分区开始时间小于当前时间的分区,当数量超过该值之后,多余的分区将会被删除。StarRocks 将根据 FE 配置项 `dynamic_partition_check_interval_seconds` 中的时间间隔定期检查物化视图分区,并自动删除过期分区。在[动态分区](../../../table_design/dynamic_partitioning.md)场景下,提前创建的未来分区将不会被纳入 TTL 考虑。默认值:`-1`。当值为 `-1` 时,将保留物化视图所有分区。 +- `partition_ttl_number`:需要保留的最近的物化视图分区数量。对于分区开始时间小于当前时间的分区,当数量超过该值之后,多余的分区将会被删除。StarRocks 将根据 FE 配置项 `dynamic_partition_check_interval_seconds` 中的时间间隔定期检查物化视图分区,并自动删除过期分区。在[动态分区](../../../table_design/data_distribution/dynamic_partitioning.md)场景下,提前创建的未来分区将不会被纳入 TTL 考虑。默认值:`-1`。当值为 `-1` 时,将保留物化视图所有分区。 - `partition_refresh_number`:单次刷新中,最多刷新的分区数量。如果需要刷新的分区数量超过该值,StarRocks 将拆分这次刷新任务,并分批完成。仅当前一批分区刷新成功时,StarRocks 会继续刷新下一批分区,直至所有分区刷新完成。如果其中有分区刷新失败,将不会产生后续的刷新任务。默认值:`-1`。当值为 `-1` 时,将不会拆分刷新任务。 - `excluded_trigger_tables`:在此项属性中列出的基表,其数据产生变化时不会触发对应物化视图自动刷新。该参数仅针对导入触发式刷新,通常需要与属性 `auto_refresh_partitions_limit` 搭配使用。形式:`[db_name.]table_name`。默认值为空字符串。当值为空字符串时,任意的基表数据变化都将触发对应物化视图刷新。 - `auto_refresh_partitions_limit`:当触发物化视图刷新时,需要刷新的最近的物化视图分区数量。您可以通过该属性限制刷新的范围,降低刷新代价,但因为仅有部分分区刷新,有可能导致物化视图数据与基表无法保持一致。默认值:`-1`。当参数值为 `-1` 时,StarRocks 将刷新所有分区。当参数值为正整数 N 时,StarRocks 会将已存在的分区按时间先后排序,并刷新当前分区和 N-1 个历史分区。如果分区数不足 N,则刷新所有已存在的分区。如果物化视图存在提前创建的未来分区,将会刷新所有提前创建的分区。 diff --git a/docs/zh/sql-reference/sql-statements/table_bucket_part_index/ALTER_TABLE.md b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/ALTER_TABLE.md index fc0f194d3f74d..5445f5e87a273 100644 --- a/docs/zh/sql-reference/sql-statements/table_bucket_part_index/ALTER_TABLE.md +++ b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/ALTER_TABLE.md @@ -211,7 +211,7 @@ DROP PARTITION [IF EXISTS] [FORCE]; #### 增加临时分区 (ADD TEMPORARY PARTITION) -详细使用信息,请查阅[临时分区](../../../table_design/Temporary_partition.md)。 +详细使用信息,请查阅[临时分区](../../../table_design/data_distribution/Temporary_partition.md)。 语法: @@ -698,7 +698,7 @@ SET ("key" = "value",...) - `default.replication_num` - `storage_cooldown_ttl` - `storage_cooldown_time` - - [动态分区相关属性 properties](../../../table_design/dynamic_partitioning.md),比如 `dynamic_partition.enable` + - [动态分区相关属性 properties](../../../table_design/data_distribution/dynamic_partitioning.md),比如 `dynamic_partition.enable` - `enable_persistent_index` - `bloom_filter_columns` - `colocate_with` diff --git a/docs/zh/sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md index d30012b492009..a790ce761ad55 100644 --- a/docs/zh/sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md +++ b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md @@ -272,13 +272,13 @@ INDEX index_name (col_name[, col_name, ...]) [USING BITMAP] [COMMENT ''] ### **partition_desc** -支持三种分区方式,[表达式分区](../../../table_design/expression_partitioning.md)(推荐)、[Range 分区](../../../table_design/Data_distribution.md#range-分区) 和 [List 分区](../../../table_design/list_partitioning.md)。 +支持三种分区方式,[表达式分区](../../../table_design/data_distribution/expression_partitioning.md)(推荐)、[Range 分区](../../../table_design/data_distribution/Data_distribution.md#range-分区) 和 [List 分区](../../../table_design/data_distribution/list_partitioning.md)。 使用 Range 分区时,提供三种创建方式,其语法、说明和示例如下: - **动态创建分区** - [动态分区](../../../table_design/dynamic_partitioning.md)提供了分区生命周期管理(TTL)。StarRocks 会自动提前创建新的分区,并删除过期的分区,以确保数据时效性。要启用这个功能,您可以在创建表时配置与动态分区相关的属性。 + [动态分区](../../../table_design/data_distribution/dynamic_partitioning.md)提供了分区生命周期管理(TTL)。StarRocks 会自动提前创建新的分区,并删除过期的分区,以确保数据时效性。要启用这个功能,您可以在创建表时配置与动态分区相关的属性。 - **手动创建分区** @@ -428,7 +428,7 @@ INDEX index_name (col_name[, col_name, ...]) [USING BITMAP] [COMMENT ''] - 当分区列为整数类型时,START 值、END 值仍需要用双引号包裹。 - 仅支持指定一列作为分区列。 - 更多信息,请参见[批量创建分区](../../../table_design/Data_distribution.md#range-分区)。 + 更多信息,请参见[批量创建分区](../../../table_design/data_distribution/Data_distribution.md#range-分区)。 示例: @@ -467,9 +467,9 @@ INDEX index_name (col_name[, col_name, ...]) [USING BITMAP] [COMMENT ''] - 不支持主键表、更新表和聚合表。 - 不支持指定 [Colocation Group](../../../using_starrocks/Colocate_join.md)。 - 不支持 [Spark Load](../../../loading/SparkLoad.md)。 - - 自 2.5.7 版本起,建表时**无需手动指定分桶数量**,StarRocks 自动设置分桶数量。如果您需要手动设置分桶数量,请参见[设置分桶数量](../../../table_design/Data_distribution.md#设置分桶数量)。 + - 自 2.5.7 版本起,建表时**无需手动指定分桶数量**,StarRocks 自动设置分桶数量。如果您需要手动设置分桶数量,请参见[设置分桶数量](../../../table_design/data_distribution/Data_distribution.md#设置分桶数量)。 - 更多随机分桶的信息,请参见[随机分桶](../../../table_design/Data_distribution.md#随机分桶自-v31)。 + 更多随机分桶的信息,请参见[随机分桶](../../../table_design/data_distribution/Data_distribution.md#随机分桶自-v31)。 - 哈希分桶 @@ -486,14 +486,14 @@ INDEX index_name (col_name[, col_name, ...]) [USING BITMAP] [COMMENT ''] - 如果查询比较复杂,则建议选择高基数的列为分桶键,保证数据在各个分桶中尽量均衡,提高集群资源利用率。 - 如果查询比较简单,则建议选择经常作为查询条件的列为分桶键,提高查询效率。 并且,如果数据倾斜情况严重,您还可以使用多个列作为数据的分桶键,但是建议不超过 3 个列。 - 更多选择分桶键的信息,请参见[选择分桶键](../../../table_design/Data_distribution.md#哈希分桶). + 更多选择分桶键的信息,请参见[选择分桶键](../../../table_design/data_distribution/Data_distribution.md#哈希分桶). **注意事项** - **建表时,必须指定分桶键**。 - 作为分桶键的列,该列的值不支持更新。 - 分桶键指定后不支持修改。 - - 自 2.5.7 版本起,建表时**无需手动指定分桶数量**,StarRocks 自动设置分桶数量。如果您需要手动设置分桶数量,请参见[设置分桶数量](../../../table_design/Data_distribution.md#设置分桶数量)。 + - 自 2.5.7 版本起,建表时**无需手动指定分桶数量**,StarRocks 自动设置分桶数量。如果您需要手动设置分桶数量,请参见[设置分桶数量](../../../table_design/data_distribution/Data_distribution.md#设置分桶数量)。 ### **ORDER BY** diff --git a/docs/zh/sql-reference/sql-statements/table_bucket_part_index/SHOW_CREATE_TABLE.md b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/SHOW_CREATE_TABLE.md index de1c940aafa7f..177ed58d3ae37 100644 --- a/docs/zh/sql-reference/sql-statements/table_bucket_part_index/SHOW_CREATE_TABLE.md +++ b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/SHOW_CREATE_TABLE.md @@ -10,7 +10,7 @@ displayed_sidebar: docs 自 3.0 版本起支持使用该语句查看 External Catalog 下的表,包括 Apache Hive™ 、Apache Iceberg、Apache Hudi、Delta Lake 表。 -自 2.5.7 版本起,StarRocks 支持在建表和新增分区时自动设置分桶数量 (BUCKETS),您无需手动设置分桶数量。更多信息,请参见 [设置分桶数量](../../../table_design/Data_distribution.md#设置分桶数量)。 +自 2.5.7 版本起,StarRocks 支持在建表和新增分区时自动设置分桶数量 (BUCKETS),您无需手动设置分桶数量。更多信息,请参见 [设置分桶数量](../../../table_design/data_distribution/Data_distribution.md#设置分桶数量)。 - 如果您在建表时指定了分桶数,SHOW CREATE TABLE 会显示分桶数。 diff --git a/docs/zh/table_design/StarRocks_table_design.md b/docs/zh/table_design/StarRocks_table_design.md index f673e339c3646..1a592f0c2de2b 100644 --- a/docs/zh/table_design/StarRocks_table_design.md +++ b/docs/zh/table_design/StarRocks_table_design.md @@ -1,5 +1,6 @@ --- displayed_sidebar: docs +sidebar_position: 10 --- # 表概览 @@ -94,7 +95,7 @@ StarRocks 提供四种类型的表,包括明细表、主键表、聚合表和 - 聚合表适用于存储预聚合后的数据,可以降低聚合查询时所需扫描和计算的数据量,极大提高聚合查询的效率。 - 更新表适用于实时更新的业务场景,目前已逐渐被主键表取代。 -### [数据分布](./Data_distribution.md) +### [数据分布](data_distribution/Data_distribution.md) StarRocks 采用分区+分桶的两级数据分布策略,将数据均匀分布各个 BE 节点。查询时能够有效裁剪数据扫描量,最大限度地利用集群的并发性能,从而提升查询性能。 @@ -119,7 +120,7 @@ StarRocks 提供两种分桶方式: 除了基本的数据类型,如数值、日期和字符串类型,StarRocks 还支持复杂的半结构化数据类型,包括 ARRAY、JSON、MAP、STRUCT。 -### [索引](./indexes/indexes_overview.md) +### [索引](indexes/indexes.md) 索引是一种特殊的数据结构,相当于数据的目录。查询条件命中索引列时,StarRocks 能够快速定位到满足条件的数据的位置。 diff --git a/docs/zh/table_design/Table_design.md b/docs/zh/table_design/Table_design.md deleted file mode 100644 index c8b45779ae0d1..0000000000000 --- a/docs/zh/table_design/Table_design.md +++ /dev/null @@ -1,7 +0,0 @@ ---- -displayed_sidebar: docs ---- - -# 介绍 - -本章首先介绍 StarRocks 的表类型,用户可根据业务需要选择匹配的表类型; 然后在这个基础上,介绍数据分布策略; 最后介绍索引技术和物化视图处理技术。 diff --git a/docs/zh/table_design/data_compression.md b/docs/zh/table_design/data_compression.md index ed1c5f1ee49ab..2ca7105e4cc91 100644 --- a/docs/zh/table_design/data_compression.md +++ b/docs/zh/table_design/data_compression.md @@ -1,5 +1,6 @@ --- displayed_sidebar: docs +sidebar_position: 50 --- # 数据压缩 diff --git a/docs/zh/table_design/Data_distribution.md b/docs/zh/table_design/data_distribution/Data_distribution.md similarity index 94% rename from docs/zh/table_design/Data_distribution.md rename to docs/zh/table_design/data_distribution/Data_distribution.md index ca30a03fad262..5b2506ee41b26 100644 --- a/docs/zh/table_design/Data_distribution.md +++ b/docs/zh/table_design/data_distribution/Data_distribution.md @@ -3,6 +3,7 @@ displayed_sidebar: docs keywords: ['fenqu','fentong', 'lengre'] toc_max_heading_level: 4 description: 分区与分桶 +sidebar_position: 30 --- # 数据分布 @@ -24,7 +25,7 @@ import TabItem from '@theme/TabItem'; 现代分布式数据库中,常见的数据分布方式有如下几种:Round-Robin、Range、List 和 Hash。如下图所示: -![数据分布方式](../_assets/3.3.2-1.png) +![数据分布方式](../../_assets/3.3.2-1.png) - Round-Robin:以轮询的方式把数据逐个放置在相邻节点上。 @@ -191,9 +192,9 @@ StarRocks 支持单独和组合使用数据分布方式。 > **注意** > -> 3.1 版本起,StarRocks [存算分离模式](../deployment/shared_data/shared_data.mdx)支持时间函数的分区表达式。 +> 3.1 版本起,StarRocks [存算分离模式](../../deployment/shared_data/shared_data.mdx)支持时间函数的分区表达式。 -[表达式分区](./expression_partitioning.md),原称自动创建分区,更加灵活易用,适用于大多数场景,比如按照连续日期范围或者枚举值来查询和管理数据。 +[表达式分区](expression_partitioning.md),原称自动创建分区,更加灵活易用,适用于大多数场景,比如按照连续日期范围或者枚举值来查询和管理数据。 您仅需要在建表时使用分区表达式(时间函数表达式或列表达式),即可实现导入数据时自动创建分区,不需要预先创建出分区或者配置动态分区属性。 @@ -205,7 +206,7 @@ StarRocks 会根据您显式定义的范围与分区的映射关系将数据分 **动态分区** -建表时[配置动态分区属性](./dynamic_partitioning.md),StarRocks 会⾃动提前创建新的分区,删除过期分区,从而确保数据的时效性,实现对分区的⽣命周期管理(Time to Life,简称 “TTL”)。 +建表时[配置动态分区属性](dynamic_partitioning.md),StarRocks 会⾃动提前创建新的分区,删除过期分区,从而确保数据的时效性,实现对分区的⽣命周期管理(Time to Life,简称 “TTL”)。 区别于表达式分区中自动创建分区功能,动态创建分区只是根据您配置的动态分区属性,定期提前创建一些分区。如果导入的新数据不属于这些提前创建的分区,则导入任务会报错。而表达式分区中自动创建分区功能会根据导入数据创建对应的新分区。 @@ -361,7 +362,7 @@ DISTRIBUTED BY HASH(site_id); #### List 分区(自 v3.1) -[List 分区](./list_partitioning.md)适用于按照枚举值来查询和管理数据。尤其适用于一个分区中需要包含各分区列的多个值。比如经常按照国家和城市来查询和管理数据,则可以使用该方式,选择分区列为 `city`,一个分区包含属于一个国家的多个城市的数据。 +[List 分区](list_partitioning.md)适用于按照枚举值来查询和管理数据。尤其适用于一个分区中需要包含各分区列的多个值。比如经常按照国家和城市来查询和管理数据,则可以使用该方式,选择分区列为 `city`,一个分区包含属于一个国家的多个城市的数据。 StarRocks 会按照您显式定义的枚举值列表与分区的映射关系将数据分配到相应的分区中。 @@ -384,7 +385,7 @@ DISTRIBUTED BY HASH(site_id); 执行如下语句,删除 `site_access` 表中分区 p1 及数据: -> 说明:分区中的数据不会立即删除,会在 Trash 中保留一段时间(默认为一天)。如果误删分区,可以通过 [RECOVER 命令](../sql-reference/sql-statements/backup_restore/RECOVER.md)恢复分区及数据。 +> 说明:分区中的数据不会立即删除,会在 Trash 中保留一段时间(默认为一天)。如果误删分区,可以通过 [RECOVER 命令](../../sql-reference/sql-statements/backup_restore/RECOVER.md)恢复分区及数据。 ```SQL ALTER TABLE site_access @@ -418,8 +419,8 @@ SHOW PARTITIONS FROM site_access; **使用限制** - 仅支持明细表。 -- 不支持指定 [Colocation Group](../using_starrocks/Colocate_join.md)。 -- 不支持 [Spark Load](../loading/SparkLoad.md)。 +- 不支持指定 [Colocation Group](../../using_starrocks/Colocate_join.md)。 +- 不支持 [Spark Load](../../loading/SparkLoad.md)。 如下建表示例中,没有使用 `DISTRIBUTED BY xxx` 语句,即表示默认由 StarRocks 使用随机分桶,并且由 StarRocks 自动设置分桶数量。 @@ -561,7 +562,7 @@ DISTRIBUTED BY HASH(site_id,city_code); :::warning - 如果需要启用按需动态增加分桶数量,您需要设置表属性 `PROPERTIES("bucket_size"="xxx")`,指定单个分桶的大小。如果分区的数据量不大,则可以设置 `bucket_size` 为 1 GB,如果分区的数据量大,则可以设置 `bucket_size` 为 4 GB。 - - 启用后,如果需要回滚至 3.1 版本,则需要删除启用按需动态增加分桶数量的表,并且手动执行元数据 checkpoint [ALTER SYSTEM CREATE IMAGE](../sql-reference/sql-statements/cluster-management/nodes_processes/ALTER_SYSTEM.md) 成功后才能回滚。 + - 启用后,如果需要回滚至 3.1 版本,则需要删除启用按需动态增加分桶数量的表,并且手动执行元数据 checkpoint [ALTER SYSTEM CREATE IMAGE](../../sql-reference/sql-statements/cluster-management/nodes_processes/ALTER_SYSTEM.md) 成功后才能回滚。 ::: @@ -672,7 +673,7 @@ DISTRIBUTED BY HASH(site_id,city_code); :::warning - 如果需要启用按需动态增加分桶数量,您需要设置表属性 `PROPERTIES("bucket_size"="xxx")`,指定单个分桶的大小。如果分区的数据量不大,则可以设置 `bucket_size` 为 1 GB,如果分区的数据量大,则可以设置 `bucket_size` 为 4 GB。 - - 启用后,如果需要回滚至 3.1 版本,则需要删除启用按需动态增加分桶数量的表,并且手动执行元数据 checkpoint [ALTER SYSTEM CREATE IMAGE](../sql-reference/sql-statements/cluster-management/nodes_processes/ALTER_SYSTEM.md) 成功后才能回滚。 + - 启用后,如果需要回滚至 3.1 版本,则需要删除启用按需动态增加分桶数量的表,并且手动执行元数据 checkpoint [ALTER SYSTEM CREATE IMAGE](../../sql-reference/sql-statements/cluster-management/nodes_processes/ALTER_SYSTEM.md) 成功后才能回滚。 ::: @@ -744,13 +745,13 @@ DISTRIBUTED BY HASH(site_id,city_code); #### 查看分桶数量 -如果查看分区中分桶数量,您可以执行 [SHOW PARTITIONS](../sql-reference/sql-statements/table_bucket_part_index/SHOW_PARTITIONS.md)。 +如果查看分区中分桶数量,您可以执行 [SHOW PARTITIONS](../../sql-reference/sql-statements/table_bucket_part_index/SHOW_PARTITIONS.md)。 :::info - 如果是随机分桶表并且开启按需动态增加分桶数量,建表后在导入过程中,分区的分桶数量会**动态增加**,返回结果显示的是分区**当前**的分桶数量。 -- 如果是随机分桶表,分区内部实际的划分层次为:分区 > 子分区 > 分桶,为了增加分桶数量,StarRocks 实际上是新增一个子分区,子分区包括一定数量的分桶,因此 [SHOW PARTITIONS](../sql-reference/sql-statements/table_bucket_part_index/SHOW_PARTITIONS.md) 返回结果中会显示分区名称相同的多条数据行,表示同一分区中子分区的情况。 +- 如果是随机分桶表,分区内部实际的划分层次为:分区 > 子分区 > 分桶,为了增加分桶数量,StarRocks 实际上是新增一个子分区,子分区包括一定数量的分桶,因此 [SHOW PARTITIONS](../../sql-reference/sql-statements/table_bucket_part_index/SHOW_PARTITIONS.md) 返回结果中会显示分区名称相同的多条数据行,表示同一分区中子分区的情况。 ::: @@ -758,7 +759,7 @@ DISTRIBUTED BY HASH(site_id,city_code); > **注意** > -> StarRocks [存算分离模式](../deployment/shared_data/shared_data.mdx)暂不支持该特性。 +> StarRocks [存算分离模式](../../deployment/shared_data/shared_data.mdx)暂不支持该特性。 随着业务场景中查询模式和数据量变化,建表时设置的分桶方式和分桶数量,以及排序键可能不再能适应新的业务场景,导致查询性能下降,此时可以通过 `ALTER TABLE` 调整分桶方式和分桶数量,以及排序键,优化数据分布。比如: @@ -782,7 +783,7 @@ DISTRIBUTED BY HASH(site_id,city_code); ALTER TABLE t ORDER BY k2, k1; ``` -更多信息,参见 [ALTER TABLE](../sql-reference/sql-statements/table_bucket_part_index/ALTER_TABLE.md) 。 +更多信息,参见 [ALTER TABLE](../../sql-reference/sql-statements/table_bucket_part_index/ALTER_TABLE.md) 。 ## 最佳实践 diff --git a/docs/zh/table_design/Temporary_partition.md b/docs/zh/table_design/data_distribution/Temporary_partition.md similarity index 90% rename from docs/zh/table_design/Temporary_partition.md rename to docs/zh/table_design/data_distribution/Temporary_partition.md index 18a2917815cd0..37337b57b24b7 100644 --- a/docs/zh/table_design/Temporary_partition.md +++ b/docs/zh/table_design/data_distribution/Temporary_partition.md @@ -1,6 +1,7 @@ --- displayed_sidebar: docs keywords: ['fenqu'] +sidebar_position: 40 --- # 临时分区 @@ -13,7 +14,7 @@ keywords: ['fenqu'] - 原子覆盖写操作 - 如果您需要重写某一正式分区的数据,同时保证重写过程中可以查看数据,您可以先创建一个对应的临时分区,将新的数据导入到临时分区后,通过替换操作,原子地替换原有正式分区,生成新正式分区。对于非分区表的原子覆盖写操作,请参考 [ALTER TABLE - SWAP](../sql-reference/sql-statements/table_bucket_part_index/ALTER_TABLE.md#swap)。 + 如果您需要重写某一正式分区的数据,同时保证重写过程中可以查看数据,您可以先创建一个对应的临时分区,将新的数据导入到临时分区后,通过替换操作,原子地替换原有正式分区,生成新正式分区。对于非分区表的原子覆盖写操作,请参考 [ALTER TABLE - SWAP](../../sql-reference/sql-statements/table_bucket_part_index/ALTER_TABLE.md#swap)。 - 调整分区数据的查询并发 如果您需要修改某一正式分区的分桶数,您可以先创建一个对应分区范围的临时分区,并指定新的分桶数,然后通过 `INSERT INTO` 命令将原有正式分区的数据导入到临时分区中,通过替换操作,原子地替换原有正式分区,生成新正式分区。 @@ -96,7 +97,7 @@ ADD TEMPORARY PARTITIONS START ("2020-04-01") END ("2021-01-01") EVERY (INTERVAL ## 查看临时分区 -您可以通过如下 [SHOW TEMPORARY PARTITIONS](../sql-reference/sql-statements/table_bucket_part_index/SHOW_PARTITIONS.md) 命令,查看表的临时分区。 +您可以通过如下 [SHOW TEMPORARY PARTITIONS](../../sql-reference/sql-statements/table_bucket_part_index/SHOW_PARTITIONS.md) 命令,查看表的临时分区。 ```SQL SHOW TEMPORARY PARTITIONS FROM site_access; @@ -108,7 +109,7 @@ SHOW TEMPORARY PARTITIONS FROM site_access; ### 通过 `INSERT INTO` 命令导入 -您可以通过如下 [INSERT INTO](../sql-reference/sql-statements/loading_unloading/INSERT.md) 命令将数据导入临时分区。 +您可以通过如下 [INSERT INTO](../../sql-reference/sql-statements/loading_unloading/INSERT.md) 命令将数据导入临时分区。 ```SQL INSERT INTO site_access TEMPORARY PARTITION (tp1) VALUES ("2020-01-01",1,"ca","lily",4); @@ -125,7 +126,7 @@ curl --location-trusted -u : -H "label:label1" -H "temporary http://host:port/api/example_db/site_access/_stream_load ``` -有关语法和参数等更多信息,请参见 [STREAM LOAD](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md)。 +有关语法和参数等更多信息,请参见 [STREAM LOAD](../../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md)。 ### 通过 BROKER LOAD 方式导入 @@ -145,7 +146,7 @@ WITH BROKER ); ``` -有关语法和参数等更多信息,请参见 [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md)。 +有关语法和参数等更多信息,请参见 [BROKER LOAD](../../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md)。 ### 通过 ROUTINE LOAD 方式导入 @@ -162,7 +163,7 @@ FROM KAFKA ); ``` -有关语法和参数等更多信息,请参见 [CREATE ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md)。 +有关语法和参数等更多信息,请参见 [CREATE ROUTINE LOAD](../../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md)。 ## 查询临时分区的数据 @@ -288,9 +289,9 @@ ALTER TABLE site_access DROP TEMPORARY PARTITION tp1; 注意事项 -- 使用 `DROP` 命令直接删除数据库或表后,您可以在限定时间内通过 [RECOVER](../sql-reference/sql-statements/backup_restore/RECOVER.md) 命令恢复该数据库或表,但临时分区无法被恢复。 -- 使用 `ALTER` 命令删除正式分区后,您可以在限定时间内通过 [RECOVER](../sql-reference/sql-statements/backup_restore/RECOVER.md) 命令恢复。正式分区与临时分区不相关联,操作正式分区不会对临时分区产生影响。 -- 使用 `ALTER` 命令删除临时分区后,您无法通过 [RECOVER](../sql-reference/sql-statements/backup_restore/RECOVER.md) 命令恢复。 +- 使用 `DROP` 命令直接删除数据库或表后,您可以在限定时间内通过 [RECOVER](../../sql-reference/sql-statements/backup_restore/RECOVER.md) 命令恢复该数据库或表,但临时分区无法被恢复。 +- 使用 `ALTER` 命令删除正式分区后,您可以在限定时间内通过 [RECOVER](../../sql-reference/sql-statements/backup_restore/RECOVER.md) 命令恢复。正式分区与临时分区不相关联,操作正式分区不会对临时分区产生影响。 +- 使用 `ALTER` 命令删除临时分区后,您无法通过 [RECOVER](../../sql-reference/sql-statements/backup_restore/RECOVER.md) 命令恢复。 - 使用 `TRUNCATE` 命令清空表后,表的临时分区会被删除,且不可恢复。 - 使用 `TRUNCATE` 命令清空正式分区时,临时分区不受影响。 - 不可使用 `TRUNCATE` 命令清空临时分区。 diff --git a/docs/zh/table_design/dynamic_partitioning.md b/docs/zh/table_design/data_distribution/dynamic_partitioning.md similarity index 99% rename from docs/zh/table_design/dynamic_partitioning.md rename to docs/zh/table_design/data_distribution/dynamic_partitioning.md index bd591650ca4b4..a3eedaf5f8753 100644 --- a/docs/zh/table_design/dynamic_partitioning.md +++ b/docs/zh/table_design/data_distribution/dynamic_partitioning.md @@ -1,6 +1,7 @@ --- displayed_sidebar: docs keywords: ['fenqu'] +sidebar_position: 30 --- # 动态分区 diff --git a/docs/zh/table_design/expression_partitioning.md b/docs/zh/table_design/data_distribution/expression_partitioning.md similarity index 92% rename from docs/zh/table_design/expression_partitioning.md rename to docs/zh/table_design/data_distribution/expression_partitioning.md index 1fcc0d5a9305e..5c5618d01fb42 100644 --- a/docs/zh/table_design/expression_partitioning.md +++ b/docs/zh/table_design/data_distribution/expression_partitioning.md @@ -1,6 +1,7 @@ --- displayed_sidebar: docs keywords: ['fenqu'] +sidebar_position: 10 --- # 表达式分区(推荐) @@ -13,7 +14,7 @@ keywords: ['fenqu'] 如果您经常按照连续日期范围来查询和管理数据,则只需要在时间函数分区表达式中,指定一个日期类型(DATE 或者 DATETIME )的分区列,以及指定分区粒度(年、月、日或小时)。StarRocks 会根据导入的数据和分区表达式,自动创建分区并且设置分区的起止时间。 -不过在一些特殊场景下,比如历史数据按月划分分区、最近数据按天划分分区,则需要采用 [Range 分区](./Data_distribution.md#range-分区)创建分区。 +不过在一些特殊场景下,比如历史数据按月划分分区、最近数据按天划分分区,则需要采用 [Range 分区](Data_distribution.md#range-分区)创建分区。 ### 语法 @@ -31,7 +32,7 @@ expression ::= | 参数 | 是否必填 | 说明 | | ----------------------- | -------- | ------------------------------------------------------------ | -| `expression` | 是 | 目前仅支持 [date_trunc](../sql-reference/sql-functions/date-time-functions/date_trunc.md) 和 [time_slice](../sql-reference/sql-functions/date-time-functions/time_slice.md) 函数。并且如果您使用 `time_slice` 函数,则可以不传入参数 `boundary`,因为在该场景中该参数默认且仅支持为 `floor`,不支持为 `ceil`。 | +| `expression` | 是 | 目前仅支持 [date_trunc](../../sql-reference/sql-functions/date-time-functions/date_trunc.md) 和 [time_slice](../../sql-reference/sql-functions/date-time-functions/time_slice.md) 函数。并且如果您使用 `time_slice` 函数,则可以不传入参数 `boundary`,因为在该场景中该参数默认且仅支持为 `floor`,不支持为 `ceil`。 | | `time_unit` | 是 | 分区粒度,目前仅支持为 `hour`、`day`、`month` 或 `year`,暂时不支持为 `week`。如果分区粒度为 `hour`,则仅支持分区列为 DATETIME 类型,不支持为 DATE 类型。 | | `partition_column` | 是 | 分区列。
  • 仅支持为日期类型(DATE 或 DATETIME),不支持为其它类型。如果使用 `date_trunc` 函数,则分区列支持为 DATE 或 DATETIME 类型。如果使用 `time_slice` 函数,则分区列仅支持为 DATETIME 类型。分区列的值支持为 `NULL`。
  • 如果分区列是 DATE 类型,则范围支持为 [0000-01-01 ~ 9999-12-31]。如果分区列是 DATETIME 类型,则范围支持为 [0000-01-01 01:01:01 ~ 9999-12-31 23:59:59]。
  • 目前仅支持指定一个分区列,不支持指定多个分区列。
| | `partition_live_number` | 否 | 保留最近多少数量的分区。最近是指分区按时间的先后顺序进行排序,以**当前时间**为基准,然后从后往前数指定个数的分区进行保留,其余(更早的)分区会被删除。后台会定时调度任务来管理分区数量,调度间隔可以通过 FE 动态参数 `dynamic_partition_check_interval_seconds` 配置,默认为 600 秒,即 10 分钟。假设当前为 2023 年 4 月 4 日,`partition_live_number` 设置为 `2`,分区包含 `p20230401`、`p20230402`、`p20230403`、`p20230404`,则分区 `p20230403`、`p20230404` 会保留,其他分区会删除。如果导入了脏数据,比如未来时间 4 月 5 日和 6 日的数据,导致分区包含 `p20230401`、`p20230402`、`p20230403`、`p20230404`、`p20230405`、`p20230406`,则分区 `p20230403`、`p20230404`、`p20230405`、`p20230406` 会保留,其他分区会删除。| @@ -115,7 +116,7 @@ DISTRIBUTED BY HASH(event_day, site_id); 如果您经常按照枚举值来查询和管理数据,则您只需要指定表示类型的列为分区列,StarRocks 会根据导入的数据的分区列值,来自动划分并创建分区。 -不过在一些特殊场景下,比如表中包含表示城市的列,您经常按照国家和城市来查询和管理数据,希望将同属于一个国家的多个城市的数据存储在一个分区中,则需要使用 [List 分区](./list_partitioning.md)。 +不过在一些特殊场景下,比如表中包含表示城市的列,您经常按照国家和城市来查询和管理数据,希望将同属于一个国家的多个城市的数据存储在一个分区中,则需要使用 [List 分区](list_partitioning.md)。 ### 语法 @@ -134,7 +135,7 @@ partition_columns ::= | 参数 | 是否必填 | 参数 | | ----------------------- | -------- | ------------------------------------------------------------ | -| `partition_columns` | 是 | 分区列。
  • 支持为字符串(不支持 BINARY)、日期、整数和布尔值。不支持分区列的值为 `NULL`。
  • 导入后自动创建的一个分区中只能包含各分区列的一个值,如果需要包含各分区列的多值,请使用 [List 分区](./list_partitioning.md)。
| +| `partition_columns` | 是 | 分区列。
  • 支持为字符串(不支持 BINARY)、日期、整数和布尔值。不支持分区列的值为 `NULL`。
  • 导入后自动创建的一个分区中只能包含各分区列的一个值,如果需要包含各分区列的多值,请使用 [List 分区](list_partitioning.md)。
| ### 使用说明 @@ -170,7 +171,7 @@ INSERT INTO t_recharge_detail1 > **说明** > -> 分区中只能包含各分区列的一个值,如果需要一个分区中包含各分区列的多值,请使用 [List 分区](./list_partitioning.md)。 +> 分区中只能包含各分区列的一个值,如果需要一个分区中包含各分区列的多值,请使用 [List 分区](list_partitioning.md)。 ```SQL MySQL > SHOW PARTITIONS from t_recharge_detail1\G @@ -201,7 +202,7 @@ LastConsistencyCheckTime: NULL 导入数据时,StarRocks 会根据数据和分区表达式定义的分区规则,自动创建分区。 -值得注意的是,如果您建表时使用表达式分区,并且需要使用 [INSERT OVERWRITE](../loading/InsertInto.md#通过-insert-overwrite-select-语句覆盖写入数据) 覆盖写入**指定分区**的数据,不论该分区是否已经创建,目前您都需要在 `PARTITION()` 提供明确的分区范围。而不是同 Range 分区或 List 分区一样,只需要在`PARTITION (partition_name)` 中提供分区名称。 +值得注意的是,如果您建表时使用表达式分区,并且需要使用 [INSERT OVERWRITE](../../loading/InsertInto.md#通过-insert-overwrite-select-语句覆盖写入数据) 覆盖写入**指定分区**的数据,不论该分区是否已经创建,目前您都需要在 `PARTITION()` 提供明确的分区范围。而不是同 Range 分区或 List 分区一样,只需要在`PARTITION (partition_name)` 中提供分区名称。 如果建表时您使用时间函数表达式分区,则此时覆盖写入指定分区,您需要提供该分区的起始范围(分区粒度与建表时配置分区粒度一致)。如果该分区不存在,则导入数据时会自动创建该分区。 @@ -234,9 +235,9 @@ MySQL > SHOW PARTITIONS FROM t_recharge_detail1; ## 使用限制 -- 自 v3.1.0 起,StarRocks [存算分离模式](../deployment/shared_data/shared_data.mdx)支持[时间函数表达式分区](#时间函数表达式分区)。并且自 v3.1.1 起 StarRocks 存算分离模式支持[列表达式分区](#列表达式分区自-v31)。 +- 自 v3.1.0 起,StarRocks [存算分离模式](../../deployment/shared_data/shared_data.mdx)支持[时间函数表达式分区](#时间函数表达式分区)。并且自 v3.1.1 起 StarRocks 存算分离模式支持[列表达式分区](#列表达式分区自-v31)。 - 使用 CTAS 建表时暂时不支持表达式分区。 - 暂时不支持使用 Spark Load 导入数据至表达式分区的表。 - 使用 `ALTER TABLE DROP PARTITION ` 删除列表达式分区时,分区直接被删除并且不能被恢复。 -- 列表达式分区暂时不支持[备份与恢复](../administration/management/Backup_and_restore.md)。 +- 列表达式分区暂时不支持[备份与恢复](../../administration/management/Backup_and_restore.md)。 - 如果使用表达式分区,则仅支持回滚到 2.5.4 及以后的版本。 diff --git a/docs/zh/table_design/feature-support-data-distribution.md b/docs/zh/table_design/data_distribution/feature-support-data-distribution.md similarity index 98% rename from docs/zh/table_design/feature-support-data-distribution.md rename to docs/zh/table_design/data_distribution/feature-support-data-distribution.md index c85ed4ef2e3f1..b6d0987cc7a0c 100644 --- a/docs/zh/table_design/feature-support-data-distribution.md +++ b/docs/zh/table_design/data_distribution/feature-support-data-distribution.md @@ -1,6 +1,7 @@ --- displayed_sidebar: docs sidebar_label: "能力边界" +sidebar_position: 50 --- # 功能边界:数据分布 @@ -187,5 +188,5 @@ sidebar_label: "能力边界" ::: -有关 List 分区和表达式分区的详细比较,请参阅 [List 分区和表达式分区的区别](./list_partitioning.md)。 +有关 List 分区和表达式分区的详细比较,请参阅 [List 分区和表达式分区的区别](list_partitioning.md)。 diff --git a/docs/zh/table_design/list_partitioning.md b/docs/zh/table_design/data_distribution/list_partitioning.md similarity index 92% rename from docs/zh/table_design/list_partitioning.md rename to docs/zh/table_design/data_distribution/list_partitioning.md index 62710ab6db64f..9432d1d1c531f 100644 --- a/docs/zh/table_design/list_partitioning.md +++ b/docs/zh/table_design/data_distribution/list_partitioning.md @@ -1,5 +1,6 @@ --- displayed_sidebar: docs +sidebar_position: 20 --- # List 分区 @@ -10,15 +11,15 @@ displayed_sidebar: docs 您需要显式列出每个 List 分区所包含的枚举值列表,并且值不需要连续,区别于包含连续日期或者数值范围的 Range 分区。当新数据导入表中时,StarRocks 会根据数据的分区列值与分区的映射关系将数据分配到相应的分区中。 -![list_partitioning](../_assets/list_partitioning.png) +![list_partitioning](../../_assets/list_partitioning.png) List 分区适用于存储具有少量枚举值列的数据、并且经常按列的枚举值来查询和管理数据的场景。例如表示地理位置、状态、类别的列。列的每个值都代表一种独立的类别。按照列的枚举值对数据进行分区,可以提高查询性能和方便数据管理。 **尤其适用于一个分区中需要包含各分区列的多个值的场景**。例如表中存在 `City` 列表示个体所属的城市,并且您经常按照州和城市查询和管理数据,则建表时可以使用 `City` 列作为分区列进行 List 分区,指定同属一个州的多个城市的数据分在同一分区 `PARTITION pCalifornia VALUES IN ("Los Angeles","San Francisco","San Diego")`,可以加速查询和方便数据管理。 -如果一个分区只需要包含各分区列的一个值,则推荐您使用[表达式分区](./expression_partitioning.md)。 +如果一个分区只需要包含各分区列的一个值,则推荐您使用[表达式分区](expression_partitioning.md)。 -**List 分区和[表达式分区](./expression_partitioning.md)的区别** +**List 分区和[表达式分区](expression_partitioning.md)的区别** 两者主要区别在于 List 分区需要您手动一个一个创建分区。而表达式分区(推荐)可以实现导入时自动创建分区,来简化分区创建,并且大部分情况下可以替代 List 分区。两者具体对比如下表: @@ -108,8 +109,8 @@ DISTRIBUTED BY HASH(`id`); ## 使用限制 -- 不支持[动态](./dynamic_partitioning.md)和[批量创建](./Data_distribution.md#range-分区) List 分区。 +- 不支持[动态](./dynamic_partitioning.md) List 分区。 - StarRocks 存算分离模式 从 3.1.1 版本开始支持该功能。 - 使用 `ALTER TABLE DROP PARTITION ;` 分区直接被删除并且不能被恢复。 -- List 分区暂时不支持[备份与恢复](../administration/management/Backup_and_restore.md)。 -- [异步物化视图](../using_starrocks/Materialized_view.md)暂不支持基于使用 List 分区的基表创建。 +- List 分区暂时不支持[备份与恢复](../../administration/management/Backup_and_restore.md)。 +- [异步物化视图](../../using_starrocks/Materialized_view.md)暂不支持基于使用 List 分区的基表创建。 diff --git a/docs/zh/table_design/hybrid_table.md b/docs/zh/table_design/hybrid_table.md index db2281e59a6de..1f5280bbf0924 100644 --- a/docs/zh/table_design/hybrid_table.md +++ b/docs/zh/table_design/hybrid_table.md @@ -1,5 +1,6 @@ --- displayed_sidebar: docs +sidebar_position: 60 --- # 【公测中】行列混存表 diff --git a/docs/zh/table_design/indexes/Bitmap_index.md b/docs/zh/table_design/indexes/Bitmap_index.md index faf9a4bd13575..aaacff088d028 100644 --- a/docs/zh/table_design/indexes/Bitmap_index.md +++ b/docs/zh/table_design/indexes/Bitmap_index.md @@ -1,6 +1,7 @@ --- displayed_sidebar: docs keywords: ['suoyin'] +sidebar_position: 20 --- # Bitmap 索引 diff --git a/docs/zh/table_design/indexes/Bloomfilter_index.md b/docs/zh/table_design/indexes/Bloomfilter_index.md index e31729e31ca36..ad983cdca2be8 100644 --- a/docs/zh/table_design/indexes/Bloomfilter_index.md +++ b/docs/zh/table_design/indexes/Bloomfilter_index.md @@ -1,6 +1,7 @@ --- displayed_sidebar: docs keywords: ['suoyin'] +sidebar_position: 30 --- # Bloom filter 索引 diff --git a/docs/zh/table_design/indexes/Prefix_index_sort_key.md b/docs/zh/table_design/indexes/Prefix_index_sort_key.md index ddbbdfc59f489..660e4cfc8f5c7 100644 --- a/docs/zh/table_design/indexes/Prefix_index_sort_key.md +++ b/docs/zh/table_design/indexes/Prefix_index_sort_key.md @@ -1,6 +1,7 @@ --- displayed_sidebar: docs keywords: ['suoyin'] +sidebar_position: 10 --- # 前缀索引和排序键 diff --git a/docs/zh/table_design/indexes/_category_.yml b/docs/zh/table_design/indexes/_category_.yml new file mode 100644 index 0000000000000..589bdbc9d3ad4 --- /dev/null +++ b/docs/zh/table_design/indexes/_category_.yml @@ -0,0 +1,6 @@ +position: 50 # float position is supported +label: '索引' +collapsible: true +collapsed: true +link: + type: generated-index diff --git a/docs/zh/table_design/indexes/indexes_overview.md b/docs/zh/table_design/indexes/indexes.md similarity index 100% rename from docs/zh/table_design/indexes/indexes_overview.md rename to docs/zh/table_design/indexes/indexes.md diff --git a/docs/zh/table_design/catalog_db_tbl.md b/docs/zh/table_design/table_design.md similarity index 99% rename from docs/zh/table_design/catalog_db_tbl.md rename to docs/zh/table_design/table_design.md index a9559ee5a64b6..17206031bd8d2 100644 --- a/docs/zh/table_design/catalog_db_tbl.md +++ b/docs/zh/table_design/table_design.md @@ -1,5 +1,6 @@ --- displayed_sidebar: docs +sidebar_position: 5 --- # Catalogs、databases 和 tables diff --git a/docs/zh/table_design/table_types/_category_.yml b/docs/zh/table_design/table_types/_category_.yml new file mode 100644 index 0000000000000..d8b8bb2f5e199 --- /dev/null +++ b/docs/zh/table_design/table_types/_category_.yml @@ -0,0 +1,7 @@ +position: 20 # float position is supported +label: '表类型' +collapsible: true +collapsed: true +link: + type: doc + id: table_types diff --git a/docs/zh/table_design/table_types/aggregate_table.md b/docs/zh/table_design/table_types/aggregate_table.md index 534b500c2667c..2e9abfa393aa8 100644 --- a/docs/zh/table_design/table_types/aggregate_table.md +++ b/docs/zh/table_design/table_types/aggregate_table.md @@ -1,5 +1,6 @@ --- displayed_sidebar: docs +sidebar_position: 40 --- # 聚合表 @@ -74,8 +75,8 @@ PROPERTIES ( > **注意** > -> - 建表时必须使用 `DISTRIBUTED BY HASH` 子句指定分桶键。分桶键的更多说明,请参见[分桶](../Data_distribution.md#分桶)。 -> - 自 2.5.7 版本起,StarRocks 支持在建表和新增分区时自动设置分桶数量 (BUCKETS),您无需手动设置分桶数量。更多信息,请参见 [设置分桶数量](../Data_distribution.md#设置分桶数量)。 +> - 建表时必须使用 `DISTRIBUTED BY HASH` 子句指定分桶键。分桶键的更多说明,请参见[分桶](../data_distribution/Data_distribution.md#分桶)。 +> - 自 2.5.7 版本起,StarRocks 支持在建表和新增分区时自动设置分桶数量 (BUCKETS),您无需手动设置分桶数量。更多信息,请参见 [设置分桶数量](../data_distribution/Data_distribution.md#设置分桶数量)。 ## 使用说明 diff --git a/docs/zh/table_design/table_types/duplicate_key_table.md b/docs/zh/table_design/table_types/duplicate_key_table.md index 0ff9bdc5fc9f4..8f1c80ee107fb 100644 --- a/docs/zh/table_design/table_types/duplicate_key_table.md +++ b/docs/zh/table_design/table_types/duplicate_key_table.md @@ -1,5 +1,6 @@ --- displayed_sidebar: docs +sidebar_position: 30 --- # 明细表 @@ -39,8 +40,8 @@ PROPERTIES ( > **注意** > -> - 建表时必须使用 `DISTRIBUTED BY HASH` 子句指定分桶键,否则建表失败。分桶键的更多说明,请参见[分桶](../Data_distribution.md#分桶)。 -> - 自 2.5.7 版本起,StarRocks 支持在建表和新增分区时自动设置分桶数量 (BUCKETS),您无需手动设置分桶数量。更多信息,请参见 [设置分桶数量](../Data_distribution.md#设置分桶数量)。 +> - 建表时必须使用 `DISTRIBUTED BY HASH` 子句指定分桶键,否则建表失败。分桶键的更多说明,请参见[分桶](../data_distribution/Data_distribution.md#分桶)。 +> - 自 2.5.7 版本起,StarRocks 支持在建表和新增分区时自动设置分桶数量 (BUCKETS),您无需手动设置分桶数量。更多信息,请参见 [设置分桶数量](../data_distribution/Data_distribution.md#设置分桶数量)。 ## 使用说明 @@ -50,7 +51,6 @@ PROPERTIES ( > 如果未指定,则默认选择表的前三列作为排序键。 - 明细表中的排序键可以为部分或全部维度列。 - - 建表时,支持为指标列创建 BITMAP、Bloom Filter 等索引。 ## 下一步 diff --git a/docs/zh/table_design/table_types/primary_key_table.md b/docs/zh/table_design/table_types/primary_key_table.md index e665b288a138d..6b2856cae95c1 100644 --- a/docs/zh/table_design/table_types/primary_key_table.md +++ b/docs/zh/table_design/table_types/primary_key_table.md @@ -1,6 +1,7 @@ --- displayed_sidebar: docs keywords: ['zhujian'] +sidebar_position: 20 --- # 主键表 @@ -103,7 +104,7 @@ DISTRIBUTED BY HASH (order_id) 并且自 3.0 起主键表解耦了主键和排序键,因此您可以选择经常作为查询过滤条件的列去构成排序键。假设经常根据订单日期和商户组合维度查询商品销售情况,则您可以通过 `ORDER BY (dt,merchant_id)` 指定排序键为 `dt` 和 `merchant_id` 。 -注意,如果您使用了[数据分布策略](../Data_distribution.md),由于目前主键表要求主键必须包括分区列和分桶列,假设采用的数据分布策略是将 `dt` 作为分区列并且 `merchant_id` 作为哈希分桶列,则主键还需要包括 `dt` 和 `merchant_id`。 +注意,如果您使用了[数据分布策略](../data_distribution/Data_distribution.md),由于目前主键表要求主键必须包括分区列和分桶列,假设采用的数据分布策略是将 `dt` 作为分区列并且 `merchant_id` 作为哈希分桶列,则主键还需要包括 `dt` 和 `merchant_id`。 综上所述,该订单表的建表语句可以为: diff --git a/docs/zh/table_design/table_types/table_capabilities.md b/docs/zh/table_design/table_types/table_capabilities.md index 45677cf048e8d..180eb843a6f43 100644 --- a/docs/zh/table_design/table_types/table_capabilities.md +++ b/docs/zh/table_design/table_types/table_capabilities.md @@ -1,5 +1,6 @@ --- displayed_sidebar: docs +sidebar_position: 10 --- # 各类表的能力对比 diff --git a/docs/zh/table_design/table_types/unique_key_table.md b/docs/zh/table_design/table_types/unique_key_table.md index 5293586e7eeb1..edae1a5c24ade 100644 --- a/docs/zh/table_design/table_types/unique_key_table.md +++ b/docs/zh/table_design/table_types/unique_key_table.md @@ -1,5 +1,6 @@ --- displayed_sidebar: docs +sidebar_position: 50 --- # 更新表 @@ -55,8 +56,8 @@ PROPERTIES ( > **注意** > -> - 建表时必须使用 `DISTRIBUTED BY HASH` 子句指定分桶键。分桶键的更多说明,请参见[分桶](../Data_distribution.md#分桶)。 -> - 自 2.5.7 版本起,StarRocks 支持在建表和新增分区时自动设置分桶数量 (BUCKETS),您无需手动设置分桶数量。更多信息,请参见 [设置分桶数量](../Data_distribution.md#设置分桶数量)。 +> - 建表时必须使用 `DISTRIBUTED BY HASH` 子句指定分桶键。分桶键的更多说明,请参见[分桶](../data_distribution/Data_distribution.md#分桶)。 +> - 自 2.5.7 版本起,StarRocks 支持在建表和新增分区时自动设置分桶数量 (BUCKETS),您无需手动设置分桶数量。更多信息,请参见 [设置分桶数量](../data_distribution/Data_distribution.md#设置分桶数量)。 ## 使用说明