hive-third-functions 包含了一些很有用的hive udf函数，特别是数组和json函数.
注意: hive-third-functions支持hive-0.11.0或更高版本.
目前, jdo2-api-2.3-ec.jar 在maven中央仓库中已经不可用, 因此我们不得不自己下载并安装到本地的maven库中. 命令如下：
wget http://www.datanucleus.org/downloads/maven2/javax/jdo/jdo2-api/2.3-ec/jdo2-api-2.3-ec.jar -O ~/jdo2-api-2.3-ec.jar
mvn install:install-file -DgroupId=javax.jdo -DartifactId=jdo2-api -Dversion=2.3-ec -Dpackaging=jar -Dfile=~/jdo2-api-2.3-ec.jar
cd ${project_home}
mvn clean package
如果你想跳过单元测试，可以这样运行：
cd ${project_home}
mvn clean package -DskipTests
命令执行完成后, 将会在target目录下生成hive-third-functions-${version}-shaded.jar文件.
你也可以直接在发布页下载打包好了最新版本 发布页.
当前最新的版本是
2.2.1
现在，我已经把hive-third-functions发布到maven中央仓库了。你可以在pom文件中增加如下dependency来使用它：
<dependency>
<groupId>com.github.aaronshan</groupId>
<artifactId>hive-third-functions</artifactId>
<version>2.2.1</version>
</dependency>
| 函数 | 描述 |
|---|---|
| pinyin(string) -> string | 将汉字转换为拼音 |
| md5(string) -> string | md5 哈希 |
| sha256(string) -> string | sha256 哈希 |
| 函数 | 描述 |
|---|---|
| array_contains(array<E>, E) -> boolean | 判断数组是否包含某个值. |
| array_equals(array<E>, array<E>) -> boolean | 判断两个数组是否相等. |
| array_intersect(array, array) -> array | 返回两个数组的交集. |
| array_max(array<E>) -> E | 返回数组中的最大值. |
| array_min(array<E>) -> E | 返回数组中的最小值. |
| array_join(array, delimiter, null_replacement) -> string | 使用给定的连接符来连接数组中的元素, null_replacement是一个可选项, 用来替代空值. |
| array_distinct(array) -> array | 移除数组中的重复元素. |
| array_position(array<E>, E) -> long | 返回给定元素在数组中第一次出现的位置 (如果没找到, 返回0). |
| array_remove(array<E>, E) -> array | 删除数组中的给定元素. |
| array_reverse(array) -> array | 反转一个数组. |
| array_sort(array) -> array | 对数组排序, 数组中的元素必需是可排序的. |
| array_concat(array, array) -> array | 连接两个数组. |
| array_value_count(array<E>, E) -> long | 统计数组中包含给定元素的个数. |
| array_slice(array, start, length) -> array | 对数组进行分片操作，start为正数从前开始分片, start为负数从后开始分片, 长度为指定的长度. |
| array_element_at(array<E>, index) -> E | 返回指定位置的数组元素. 如果索引位置 < 0, 则从尾部开始计数并返回. |
| array_shuffle(array) -> array | 对数组shuffle. |
| sequence(start, end) -> array | 生成数组序列. |
| sequence(start, end, step) -> array | 生成数组序列. |
| sequence(start_date_string, end_data_string, step) -> array | 生成日期数组序列. |
| 函数 | 描述 |
|---|---|
| map_build(x<K>, y<V>) -> map<K, V> | 根据指定的键/值对数组创建map. |
| map_concat(x<K, V>, y<K, V>) -> map<K,V> | 返回两个map的并集. 如果一个键在 x 和 y中同时出现, 那对应值来自y. |
| map_element_at(map<K, V>, key) -> V | 如果指定的key存在，返回对应的值, 否则返回 NULL . |
| map_equals(x<K, V>, y<K, V>) -> boolean | 判断map x 和 map y是否相等. |
| 函数 | 描述 |
|---|---|
| day_of_week(date_string | date) -> int | 一周的第几天,周一返回 1, 周日返回 7, 出错返回null. |
| day_of_year(date_string | date) -> int | 一年的第几天. 值的范围从 1 到 366. |
| zodiac_en(date_string | date) -> string | 将日期转换为星座英文 |
| zodiac_cn(date_string | date) -> string | 将日期转换为星座中文 |
| type_of_day(date_string | date) -> string | 获取日期的类型(1: 法定节假日, 2: 正常周末, 3: 正常工作日 4:攒假的工作日),错误返回-1. |
| 函数 | 描述 |
|---|---|
| json_array_get(json, jsonPath) -> array(varchar) | returns the element at the specified index into the json_array. The index is zero-based. |
| json_array_length(json, jsonPath) -> array(varchar) | returns the array length of json (a string containing a JSON array). |
| json_array_extract(json, jsonPath) -> array(varchar) | extract json array by given jsonPath. |
| json_array_extract_scalar(json, jsonPath) -> array(varchar) | like json_array_extract, but returns the result value as a string (as opposed to being encoded as JSON). |
| json_extract(json, jsonPath) -> array(varchar) | extract json by given jsonPath. |
| json_extract_scalar(json, jsonPath) -> array(varchar) | like json_extract, but returns the result value as a string (as opposed to being encoded as JSON). |
| json_size(json, jsonPath) -> array(varchar) | like json_extract, but returns the size of the value. For objects or arrays, the size is the number of members, and the size of a scalar value is zero. |
| 函数 | 描述 |
|---|---|
| bit_count(x, bits) -> bigint | count the number of bits set in x (treated as bits-bit signed integer) in 2’s complement representation |
| bitwise_and(x, y) -> bigint | returns the bitwise AND of x and y in 2’s complement arithmetic. |
| bitwise_not(x) -> bigint | returns the bitwise NOT of x in 2’s complement arithmetic. |
| bitwise_or(x, y) -> bigint | returns the bitwise OR of x and y in 2’s complement arithmetic. |
| bitwise_xor(x, y) -> bigint | returns the bitwise XOR of x and y in 2’s complement arithmetic. |
| 函数 | 描述 |
|---|---|
| id_card_province(string) -> string | 从身份证号获取省份 |
| id_card_city(string) -> string | 从身份证号获取城市 |
| id_card_area(string) -> string | 从身份证号获取区/县 |
| id_card_birthday(string) -> string | 从身份证号获取生日 |
| id_card_gender(string) -> string | 从身份证号获取性别 |
| is_valid_id_card(string) -> boolean | 鉴定身份证号是否有效. |
| id_card_info(string) -> json | 获取身份证号信息. 包活省份、城市、区县等. |
| 函数 | 描述 |
|---|---|
| wgs_distance(double lat1, double lng1, double lat2, double lng2) -> double | 计算 WGS84坐标距离, 单位米. |
| gcj_to_bd(double,double) -> json | GCJ-02(火星坐标系) 转为 BD-09(百度坐标系), 谷歌、高德——>百度 |
| bd_to_gcj(double,double) -> json | BD-09(百度坐标系) 转为 GCJ-02(火星坐标系), 百度——>谷歌、高德 |
| wgs_to_gcj(double,double) -> json | WGS84(地球坐标系) 转为 GCJ02(火星坐标系) |
| gcj_to_wgs(double,double) -> json | GCJ02(火星坐标系) 转为 GPS84(地球坐标系), 输出的坐标精度在1到2米. |
| gcj_extract_wgs(double,double) -> json | GCJ02(火星坐标系) 转为 GPS84, 输出的坐标精度在0.5米. 但是计算比gcj_to_wgs耗时长. |
关于互联网地图坐标系的说明见: 当前互联网地图的坐标系现状
| 函数 | 描述 |
|---|---|
| url_encode(value) -> string | escapes value by encoding it so that it can be safely included in URL query parameter names and values |
| url_decode(value) -> string | unescape the URL encoded value. This function is the inverse of url_encode. |
| function | description |
|---|---|
| infinity() -> double | 获取正无穷常数 |
| is_finite(x) -> boolean | 判断x是否为有限数值 |
| is_infinite(x) -> boolean | 判断x是否为无穷数值 |
| is_nan(x) -> boolean | 判断x是否不是一个数值类型的变量 |
| nan() -> double | 获取一个表示NAN（not-a-number）的常数 |
| from_base(string, radix) -> bigint | 获取字面量的值，该值的基数为radix |
| to_base(x, radix) -> varchar | 返回x以radix为基数的字面量 |
| cosine_similarity(x, y) -> double | 返回两个稀疏向量的余弦相似度 |
将下面这些内容写入 ${HOME}/.hiverc 文件, 或者也可以按需在hive命令行环境中执行.
add jar ${jar_location_dir}/hive-third-functions-${version}-shaded.jar
create temporary function array_contains as 'com.github.aaronshan.functions.array.UDFArrayContains';
create temporary function array_equals as 'com.github.aaronshan.functions.array.UDFArrayEquals';
create temporary function array_intersect as 'com.github.aaronshan.functions.array.UDFArrayIntersect';
create temporary function array_max as 'com.github.aaronshan.functions.array.UDFArrayMax';
create temporary function array_min as 'com.github.aaronshan.functions.array.UDFArrayMin';
create temporary function array_join as 'com.github.aaronshan.functions.array.UDFArrayJoin';
create temporary function array_distinct as 'com.github.aaronshan.functions.array.UDFArrayDistinct';
create temporary function array_position as 'com.github.aaronshan.functions.array.UDFArrayPosition';
create temporary function array_remove as 'com.github.aaronshan.functions.array.UDFArrayRemove';
create temporary function array_reverse as 'com.github.aaronshan.functions.array.UDFArrayReverse';
create temporary function array_sort as 'com.github.aaronshan.functions.array.UDFArraySort';
create temporary function array_concat as 'com.github.aaronshan.functions.array.UDFArrayConcat';
create temporary function array_value_count as 'com.github.aaronshan.functions.array.UDFArrayValueCount';
create temporary function array_slice as 'com.github.aaronshan.functions.array.UDFArraySlice';
create temporary function array_element_at as 'com.github.aaronshan.functions.array.UDFArrayElementAt';
create temporary function array_shuffle as 'com.github.aaronshan.functions.array.UDFArrayShuffle';
create temporary function sequence as 'com.github.aaronshan.functions.array.UDFSequence';
create temporary function array_value_count as 'com.github.aaronshan.functions.array.UDFArrayValueCount';
create temporary function bit_count as 'com.github.aaronshan.functions.bitwise.UDFBitCount';
create temporary function bitwise_and as 'com.github.aaronshan.functions.bitwise.UDFBitwiseAnd';
create temporary function bitwise_not as 'com.github.aaronshan.functions.bitwise.UDFBitwiseNot';
create temporary function bitwise_or as 'com.github.aaronshan.functions.bitwise.UDFBitwiseOr';
create temporary function bitwise_xor as 'com.github.aaronshan.functions.bitwise.UDFBitwiseXor';
create temporary function map_build as 'com.github.aaronshan.functions.map.UDFMapBuild';
create temporary function map_concat as 'com.github.aaronshan.functions.map.UDFMapConcat';
create temporary function map_element_at as 'com.github.aaronshan.functions.map.UDFMapElementAt';
create temporary function map_equals as 'com.github.aaronshan.functions.map.UDFMapEquals';
create temporary function day_of_week as 'com.github.aaronshan.functions.date.UDFDayOfWeek';
create temporary function day_of_year as 'com.github.aaronshan.functions.date.UDFDayOfYear';
create temporary function type_of_day as 'com.github.aaronshan.functions.date.UDFTypeOfDay';
create temporary function zodiac_cn as 'com.github.aaronshan.functions.date.UDFZodiacSignCn';
create temporary function zodiac_en as 'com.github.aaronshan.functions.date.UDFZodiacSignEn';
create temporary function pinyin as 'com.github.aaronshan.functions.string.UDFChineseToPinYin';
create temporary function md5 as 'com.github.aaronshan.functions.string.UDFMd5';
create temporary function sha256 as 'com.github.aaronshan.functions.string.UDFSha256';
create temporary function codepoint as 'com.github.aaronshan.functions.string.UDFCodePoint';
create temporary function hamming_distance as 'com.github.aaronshan.functions.string.UDFStringHammingDistance';
create temporary function levenshtein_distance as 'com.github.aaronshan.functions.string.UDFStringLevenshteinDistance';
create temporary function normalize as 'com.github.aaronshan.functions.string.UDFStringNormalize';
create temporary function strpos as 'com.github.aaronshan.functions.string.UDFStringPosition';
create temporary function split_to_map as 'com.github.aaronshan.functions.string.UDFStringSplitToMap';
create temporary function split_to_multimap as 'com.github.aaronshan.functions.string.UDFStringSplitToMultimap';
create temporary function json_array_get as 'com.github.aaronshan.functions.json.UDFJsonArrayGet';
create temporary function json_array_length as 'com.github.aaronshan.functions.json.UDFJsonArrayLength';
create temporary function json_array_extract as 'com.github.aaronshan.functions.json.UDFJsonArrayExtract';
create temporary function json_array_extract_scalar as 'com.github.aaronshan.functions.json.UDFJsonArrayExtractScalar';
create temporary function json_extract as 'com.github.aaronshan.functions.json.UDFJsonExtract';
create temporary function json_extract_scalar as 'com.github.aaronshan.functions.json.UDFJsonExtractScalar';
create temporary function json_size as 'com.github.aaronshan.functions.json.UDFJsonSize';
create temporary function id_card_province as 'com.github.aaronshan.functions.card.UDFChinaIdCardProvince';
create temporary function id_card_city as 'com.github.aaronshan.functions.card.UDFChinaIdCardCity';
create temporary function id_card_area as 'com.github.aaronshan.functions.card.UDFChinaIdCardArea';
create temporary function id_card_birthday as 'com.github.aaronshan.functions.card.UDFChinaIdCardBirthday';
create temporary function id_card_gender as 'com.github.aaronshan.functions.card.UDFChinaIdCardGender';
create temporary function is_valid_id_card as 'com.github.aaronshan.functions.card.UDFChinaIdCardValid';
create temporary function id_card_info as 'com.github.aaronshan.functions.card.UDFChinaIdCardInfo';
create temporary function wgs_distance as 'com.github.aaronshan.functions.geo.UDFGeoWgsDistance';
create temporary function gcj_to_bd as 'com.github.aaronshan.functions.geo.UDFGeoGcjToBd';
create temporary function bd_to_gcj as 'com.github.aaronshan.functions.geo.UDFGeoBdToGcj';
create temporary function wgs_to_gcj as 'com.github.aaronshan.functions.geo.UDFGeoWgsToGcj';
create temporary function gcj_to_wgs as 'com.github.aaronshan.functions.geo.UDFGeoGcjToWgs';
create temporary function gcj_extract_wgs as 'com.github.aaronshan.functions.geo.UDFGeoGcjExtractWgs';
create temporary function url_encode as 'com.github.aaronshan.functions.url.UDFUrlEncode';
create temporary function url_decode as 'com.github.aaronshan.functions.url.UDFUrlDecode';
create temporary function infinity as 'com.github.aaronshan.functions.math.UDFMathInfinity';
create temporary function is_finite as 'com.github.aaronshan.functions.math.UDFMathIsFinite';
create temporary function is_infinite as 'com.github.aaronshan.functions.math.UDFMathIsInfinite';
create temporary function nan as 'com.github.aaronshan.functions.math.UDFMathNaN';
create temporary function is_nan as 'com.github.aaronshan.functions.math.UDFMathIsNaN';
create temporary function from_base as 'com.github.aaronshan.functions.math.UDFMathFromBase';
create temporary function to_base as 'com.github.aaronshan.functions.math.UDFMathToBase';
create temporary function cosine_similarity as 'com.github.aaronshan.functions.math.UDFMathCosineSimilarity';
create temporary function normal_cdf as 'com.github.aaronshan.functions.math.UDFMathNormalCdf';
create temporary function inverse_normal_cdf as 'com.github.aaronshan.functions.math.UDFMathInverseNormalCdf';
create temporary function regexp_extract as 'com.github.aaronshan.functions.regexp.UDFRe2JRegexpExtract';
create temporary function regexp_extract_all as 'com.github.aaronshan.functions.regexp.UDFRe2JRegexpExtractAll';
create temporary function regexp_like as 'com.github.aaronshan.functions.regexp.UDFRe2JRegexpLike';
create temporary function regexp_replace as 'com.github.aaronshan.functions.regexp.UDFRe2JRegexpReplace';
create temporary function regexp_split as 'com.github.aaronshan.functions.regexp.UDFRe2JRegexpSplit';
你可以在hive的命令杭中使用下面的语句来查看函数的细节.
hive> describe function zodiac_cn;
zodiac_cn(date) - from the input date string or separate month and day arguments, returns the sing of the Zodiac.
或者
hive> describe function extended zodiac_cn;
zodiac_cn(date) - from the input date string or separate month and day arguments, returns the sing of the Zodiac.
Example:
> select zodiac_cn(date_string) from src;
> select zodiac_cn(month, day) from src;
select pinyin('中国') => zhongguo
select md5('aaronshan') => 95686bc0483262afe170b550dd4544d1
select sha256('aaronshan') => d16bb375433ad383169f911afdf45e209eabfcf047ba1faebdd8f6a0b39e0a32
select day_of_week('2016-07-12') => 2
select day_of_year('2016-01-01') => 1
select type_of_day('2016-10-01') => 1
select type_of_day('2016-07-16') => 2
select type_of_day('2016-07-15') => 3
select type_of_day('2016-09-18') => 4
select zodiac_cn('1989-01-08') => 魔羯座
select zodiac_en('1989-01-08') => Capricorn
select array_contains(array(16,12,18,9), 12) => true
select array_equals(array(16,12,18,9), array(16,12,18,9)) => true
select array_intersect(array(16,12,18,9,null), array(14,9,6,18,null)) => [null,9,18]
select array_max(array(16,13,12,13,18,16,9,18)) => 18
select array_min(array(16,12,18,9)) => 9
select array_join(array(16,12,18,9,null), '#','=') => 16#12#18#9#=
select array_distinct(array(16,13,12,13,18,16,9,18)) => [9,12,13,16,18]
select array_position(array(16,13,12,13,18,16,9,18), 13) => 2
select array_remove(array(16,13,12,13,18,16,9,18), 13) => [16,12,18,16,9,18]
select array_reverse(array(16,12,18,9)) => [9,18,12,16]
select array_sort(array(16,13,12,13,18,16,9,18)) => [9,12,13,13,16,16,18,18]
select array_concat(array(16,12,18,9,null), array(14,9,6,18,null)) => [16,12,18,9,null,14,9,6,18,null]
select array_value_count(array(16,13,12,13,18,16,9,18), 13) => 2
select array_slice(array(16,13,12,13,18,16,9,18), -2, 3) => [9,18]
select array_element_at(array(16,13,12,13,18,16,9,18), -1) => 18
select array_shuffle(array(16,12,18,9))
select sequence(1, 5) => [1, 2, 3, 4, 5]
select sequence(5, 1) => [5, 4, 3, 2, 1]
select sequence(1, 9, 4) => [1, 5, 9]
select sequence('2016-04-12 00:00:00', '2016-04-14 00:00:00', 24*3600*1000) => ['2016-04-12 00:00:00', '2016-04-13 00:00:00', '2016-04-14 00:00:00']
select map_build(array('key1','key2'), array(16,12)) => {"key1":16,"key2":12}
select map_concat(map_build(array('key1','key2'), array(16,12)), map_build(array('key1','key3'), array(17,18))) => {"key1":17,"key2":12,"key3":18}
select map_element_at(map_build(array('key1','key2'), array(16,12)), 'key1') => 16
select map_equals(map_build(array('key1','key2'), array(16,12)), map_build(array('key1','key2'), array(16,12))) => true
select id_card_info('110101198901084517') => {"valid":true,"area":"东城区","province":"北京市","gender":"男","city":"北京市"}
select json_array_get("[{\"a\":{\"b\":\"13\"}}, {\"a\":{\"b\":\"18\"}}, {\"a\":{\"b\":\"12\"}}]", 1); => {"a":{"b":"18"}}
select json_array_get('["a", "b", "c"]', 0); => a
select json_array_get('["a", "b", "c"]', 1); => b
select json_array_get('["c", "b", "a"]', -1); => a
select json_array_get('["c", "b", "a"]', -2); => b
select json_array_get('[]', 0); => null
select json_array_get('["a", "b", "c"]', 10); => null
select json_array_get('["c", "b", "a"]', -10); => null
select json_array_length("[{\"a\":{\"b\":\"13\"}}, {\"a\":{\"b\":\"18\"}}, {\"a\":{\"b\":\"12\"}}]"); => 3
select json_array_extract("[{\"a\":{\"b\":\"13\"}}, {\"a\":{\"b\":\"18\"}}, {\"a\":{\"b\":\"12\"}}]", "$.a.b"); => ["\"13\"","\"18\"","\"12\""]
select json_array_extract_scalar("[{\"a\":{\"b\":\"13\"}}, {\"a\":{\"b\":\"18\"}}, {\"a\":{\"b\":\"12\"}}]", "$.a.b") => ["13","18","12"]
select json_extract("{\"a\":{\"b\":\"12\"}}", "$.a.b"); => "12"
select json_extract_scalar("{\"a\":{\"b\":\"12\"}}", "$.a.b") => 12
select json_extract_scalar('[1, 2, 3]', '$[2]');
select json_extract_scalar(json, '$.store.book[0].author');
select json_size('{"x": {"a": 1, "b": 2}}', '$.x'); => 2
select json_size('{"x": [1, 2, 3]}', '$.x'); => 3
select json_size('{"x": {"a": 1, "b": 2}}', '$.x.a'); => 0
select gcj_to_bd(39.915, 116.404) => {"lng":116.41036949371029,"lat":39.92133699351022}
select bd_to_gcj(39.915, 116.404) => {"lng":116.39762729119315,"lat":39.90865673957631}
select wgs_to_gcj(39.915, 116.404) => {"lng":116.41024449916938,"lat":39.91640428150164}
select gcj_to_wgs(39.915, 116.404) => {"lng":116.39775550083061,"lat":39.91359571849836}
select gcj_extract_wgs(39.915, 116.404) => {"lng":116.39775549316407,"lat":39.913596801757805}
select url_encode('http://shanruifeng.cc/') => http%3A%2F%2Fshanruifeng.cc%2F
select cosine_similarity(map_build(array['a'], array[1.0]), map_build(array['a'], array[2.0])); => 1.0