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219
...park/paimon-spark-common/src/test/scala/org/apache/paimon/spark/PaimonCDCSourceTest.scala
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| /* | ||
| * Licensed to the Apache Software Foundation (ASF) under one | ||
| * or more contributor license agreements. See the NOTICE file | ||
| * distributed with this work for additional information | ||
| * regarding copyright ownership. The ASF licenses this file | ||
| * to you under the Apache License, Version 2.0 (the | ||
| * "License"); you may not use this file except in compliance | ||
| * with the License. You may obtain a copy of the License at | ||
| * | ||
| * http://www.apache.org/licenses/LICENSE-2.0 | ||
| * | ||
| * Unless required by applicable law or agreed to in writing, software | ||
| * distributed under the License is distributed on an "AS IS" BASIS, | ||
| * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| * See the License for the specific language governing permissions and | ||
| * limitations under the License. | ||
| */ | ||
| package org.apache.paimon.spark | ||
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| import org.apache.spark.sql.{Dataset, Row} | ||
| import org.apache.spark.sql.execution.streaming.MemoryStream | ||
| import org.apache.spark.sql.streaming.StreamTest | ||
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| class PaimonCDCSourceTest extends PaimonSparkTestBase with StreamTest { | ||
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| import testImplicits._ | ||
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| test("Paimon CDC Source: batch write and streaming read change-log with default scan mode") { | ||
| withTempDir { | ||
| checkpointDir => | ||
| val tableName = "T" | ||
| spark.sql(s"DROP TABLE IF EXISTS $tableName") | ||
| spark.sql(s""" | ||
| |CREATE TABLE $tableName (a INT, b STRING) | ||
| |TBLPROPERTIES ( | ||
| | 'primary-key'='a', | ||
| | 'write-mode'='change-log', | ||
| | 'bucket'='2', | ||
| | 'changelog-producer' = 'lookup') | ||
| |""".stripMargin) | ||
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| spark.sql(s"INSERT INTO $tableName VALUES (1, 'v_1')") | ||
| spark.sql(s"INSERT INTO $tableName VALUES (2, 'v_2')") | ||
| spark.sql(s"INSERT INTO $tableName VALUES (2, 'v_2_new')") | ||
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| val table = loadTable(tableName) | ||
| val location = table.location().getPath | ||
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| val readStream = spark.readStream | ||
| .format("paimon") | ||
| .option("read.readChangeLog", "true") | ||
| .load(location) | ||
| .writeStream | ||
| .format("memory") | ||
| .option("checkpointLocation", checkpointDir.getCanonicalPath) | ||
| .queryName("mem_table") | ||
| .outputMode("append") | ||
| .start() | ||
|
|
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| val currentResult = () => spark.sql("SELECT * FROM mem_table") | ||
| try { | ||
| readStream.processAllAvailable() | ||
| val expertResult1 = Row("+I", 1, "v_1") :: Row("+I", 2, "v_2_new") :: Nil | ||
| checkAnswer(currentResult(), expertResult1) | ||
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| spark.sql(s"INSERT INTO $tableName VALUES (1, 'v_1_new'), (3, 'v_3')") | ||
| readStream.processAllAvailable() | ||
| val expertResult2 = | ||
| Row("+I", 1, "v_1") :: Row("-U", 1, "v_1") :: Row("+U", 1, "v_1_new") :: Row( | ||
| "+I", | ||
| 2, | ||
| "v_2_new") :: Row("+I", 3, "v_3") :: Nil | ||
| checkAnswer(currentResult(), expertResult2) | ||
| } finally { | ||
| readStream.stop() | ||
| } | ||
| } | ||
| } | ||
|
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| test("Paimon CDC Source: batch write and streaming read change-log with scan.snapshot-id") { | ||
| withTempDir { | ||
| checkpointDir => | ||
| val tableName = "T" | ||
| spark.sql(s"DROP TABLE IF EXISTS $tableName") | ||
| spark.sql(s""" | ||
| |CREATE TABLE $tableName (a INT, b STRING) | ||
| |TBLPROPERTIES ( | ||
| | 'primary-key'='a', | ||
| | 'write-mode'='change-log', | ||
| | 'bucket'='2', | ||
| | 'changelog-producer' = 'lookup') | ||
| |""".stripMargin) | ||
|
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| spark.sql(s"INSERT INTO $tableName VALUES (1, 'v_1')") | ||
| spark.sql(s"INSERT INTO $tableName VALUES (2, 'v_2')") | ||
| spark.sql(s"INSERT INTO $tableName VALUES (2, 'v_2_new')") | ||
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| val table = loadTable(tableName) | ||
| val location = table.location().getPath | ||
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| val readStream = spark.readStream | ||
| .format("paimon") | ||
| .option("read.readChangeLog", "true") | ||
| .option("scan.mode", "from-snapshot") | ||
| .option("scan.snapshot-id", 1) | ||
| .load(location) | ||
| .writeStream | ||
| .format("memory") | ||
| .option("checkpointLocation", checkpointDir.getCanonicalPath) | ||
| .queryName("mem_table") | ||
| .outputMode("append") | ||
| .start() | ||
|
|
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| val currentResult = () => spark.sql("SELECT * FROM mem_table") | ||
| try { | ||
| readStream.processAllAvailable() | ||
| val expertResult1 = Row("+I", 1, "v_1") :: Row("+I", 2, "v_2") :: Row( | ||
| "-U", | ||
| 2, | ||
| "v_2") :: Row("+U", 2, "v_2_new") :: Nil | ||
| checkAnswer(currentResult(), expertResult1) | ||
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| spark.sql(s"INSERT INTO $tableName VALUES (1, 'v_1_new'), (3, 'v_3')") | ||
| readStream.processAllAvailable() | ||
| val expertResult2 = | ||
| Row("+I", 1, "v_1") :: Row("-U", 1, "v_1") :: Row("+U", 1, "v_1_new") :: Row( | ||
| "+I", | ||
| 2, | ||
| "v_2") :: Row("-U", 2, "v_2") :: Row("+U", 2, "v_2_new") :: Row("+I", 3, "v_3") :: Nil | ||
| checkAnswer(currentResult(), expertResult2) | ||
| } finally { | ||
| readStream.stop() | ||
| } | ||
| } | ||
| } | ||
|
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| test("Paimon CDC Source: streaming write and streaming read change-log") { | ||
| withTempDirs { | ||
| (checkpointDir1, checkpointDir2) => | ||
| val tableName = "T" | ||
| spark.sql(s"DROP TABLE IF EXISTS $tableName") | ||
| spark.sql(s""" | ||
| |CREATE TABLE $tableName (a INT, b STRING) | ||
| |TBLPROPERTIES ( | ||
| | 'primary-key'='a', | ||
| | 'write-mode'='change-log', | ||
| | 'bucket'='2', | ||
| | 'changelog-producer' = 'lookup') | ||
| |""".stripMargin) | ||
|
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| val table = loadTable(tableName) | ||
| val location = table.location().getPath | ||
|
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| // streaming write | ||
| val inputData = MemoryStream[(Int, String)] | ||
| val writeStream = inputData | ||
| .toDS() | ||
| .toDF("a", "b") | ||
| .writeStream | ||
| .option("checkpointLocation", checkpointDir1.getCanonicalPath) | ||
| .foreachBatch { | ||
| (batch: Dataset[Row], _: Long) => | ||
| batch.write.format("paimon").mode("append").save(location) | ||
| } | ||
| .start() | ||
|
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| // streaming read | ||
| val readStream = spark.readStream | ||
| .format("paimon") | ||
| .option("read.readChangeLog", "true") | ||
| .option("scan.mode", "from-snapshot") | ||
| .option("scan.snapshot-id", 1) | ||
| .load(location) | ||
| .writeStream | ||
| .format("memory") | ||
| .option("checkpointLocation", checkpointDir2.getCanonicalPath) | ||
| .queryName("mem_table") | ||
| .outputMode("append") | ||
| .start() | ||
|
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| val currentResult = () => spark.sql("SELECT * FROM mem_table") | ||
| try { | ||
| inputData.addData((1, "v_1")) | ||
| writeStream.processAllAvailable() | ||
| readStream.processAllAvailable() | ||
| val expertResult1 = Row("+I", 1, "v_1") :: Nil | ||
| checkAnswer(currentResult(), expertResult1) | ||
|
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| inputData.addData((2, "v_2")) | ||
| writeStream.processAllAvailable() | ||
| readStream.processAllAvailable() | ||
| val expertResult2 = Row("+I", 1, "v_1") :: Row("+I", 2, "v_2") :: Nil | ||
| checkAnswer(currentResult(), expertResult2) | ||
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| inputData.addData((2, "v_2_new")) | ||
| writeStream.processAllAvailable() | ||
| readStream.processAllAvailable() | ||
| val expertResult3 = Row("+I", 1, "v_1") :: Row("+I", 2, "v_2") :: Row( | ||
| "-U", | ||
| 2, | ||
| "v_2") :: Row("+U", 2, "v_2_new") :: Nil | ||
| checkAnswer(currentResult(), expertResult3) | ||
|
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| inputData.addData((1, "v_1_new"), (3, "v_3")) | ||
| writeStream.processAllAvailable() | ||
| readStream.processAllAvailable() | ||
| val expertResult4 = | ||
| Row("+I", 1, "v_1") :: Row("-U", 1, "v_1") :: Row("+U", 1, "v_1_new") :: Row( | ||
| "+I", | ||
| 2, | ||
| "v_2") :: Row("-U", 2, "v_2") :: Row("+U", 2, "v_2_new") :: Row("+I", 3, "v_3") :: Nil | ||
| checkAnswer(currentResult(), expertResult4) | ||
| } finally { | ||
| readStream.stop() | ||
| } | ||
| } | ||
| } | ||
|
|
||
| } |