codope commented on code in PR #10352: URL: https://github.com/apache/hudi/pull/10352#discussion_r1456713128
########## hudi-spark-datasource/hudi-spark/src/test/scala/org/apache/hudi/functional/PartitionStatsIndexTestBase.scala: ########## @@ -0,0 +1,259 @@ +/* + * 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.hudi.functional + +import org.apache.hadoop.fs.Path +import org.apache.hudi.DataSourceWriteOptions._ +import org.apache.hudi.PartitionStatsIndexSupport +import org.apache.hudi.client.SparkRDDWriteClient +import org.apache.hudi.client.common.HoodieSparkEngineContext +import org.apache.hudi.common.config.{HoodieMetadataConfig, TypedProperties} +import org.apache.hudi.common.model.{ActionType, HoodieCommitMetadata, WriteOperationType} +import org.apache.hudi.common.table.timeline.{HoodieInstant, MetadataConversionUtils} +import org.apache.hudi.common.table.{HoodieTableConfig, HoodieTableMetaClient} +import org.apache.hudi.common.testutils.RawTripTestPayload.recordsToStrings +import org.apache.hudi.config.HoodieWriteConfig +import org.apache.hudi.metadata.HoodieBackedTableMetadata +import org.apache.hudi.testutils.HoodieSparkClientTestBase +import org.apache.hudi.util.JavaConversions +import org.apache.spark.sql.functions.{col, not} +import org.apache.spark.sql.{DataFrame, Row, SaveMode, SparkSession} +import org.junit.jupiter.api.Assertions.{assertEquals, assertTrue} +import org.junit.jupiter.api.{AfterEach, BeforeEach} + +import java.util.concurrent.atomic.AtomicInteger +import java.util.stream.Collectors +import scala.collection.JavaConverters._ +import scala.collection.{JavaConverters, mutable} + +/** + * Common test setup and validation methods for partition stats index testing. + */ +class PartitionStatsIndexTestBase extends HoodieSparkClientTestBase { + + var spark: SparkSession = _ + var instantTime: AtomicInteger = _ + val metadataOpts: Map[String, String] = Map( + HoodieMetadataConfig.ENABLE.key -> "true", + HoodieMetadataConfig.ENABLE_METADATA_INDEX_PARTITION_STATS.key -> "true" + ) + val commonOpts: Map[String, String] = Map( + "hoodie.insert.shuffle.parallelism" -> "4", + "hoodie.upsert.shuffle.parallelism" -> "4", + HoodieWriteConfig.TBL_NAME.key -> "hoodie_test", + RECORDKEY_FIELD.key -> "_row_key", + PARTITIONPATH_FIELD.key -> "partition", + PRECOMBINE_FIELD.key -> "timestamp", + HoodieTableConfig.POPULATE_META_FIELDS.key -> "true" + ) ++ metadataOpts + var mergedDfList: List[DataFrame] = List.empty + + @BeforeEach + override def setUp(): Unit = { + initPath() + initSparkContexts() + initFileSystem() + initTestDataGenerator() + + setTableName("hoodie_test") + initMetaClient() + + instantTime = new AtomicInteger(1) + + spark = sqlContext.sparkSession + } + + @AfterEach + override def tearDown(): Unit = { + cleanupResources() + } + + protected def getLatestMetaClient(enforce: Boolean): HoodieTableMetaClient = { + val lastInsant = String.format("%03d", new Integer(instantTime.incrementAndGet())) + if (enforce || metaClient.getActiveTimeline.lastInstant().get().getTimestamp.compareTo(lastInsant) < 0) { + println("Reloaded timeline") + metaClient.reloadActiveTimeline() + metaClient + } + metaClient + } + + protected def rollbackLastInstant(hudiOpts: Map[String, String]): HoodieInstant = { + val lastInstant = getLatestMetaClient(false).getActiveTimeline + .filter(JavaConversions.getPredicate(instant => instant.getAction != ActionType.rollback.name())) + .lastInstant().get() + if (getLatestCompactionInstant != getLatestMetaClient(false).getActiveTimeline.lastInstant() + && lastInstant.getAction != ActionType.replacecommit.name() + && lastInstant.getAction != ActionType.clean.name()) { + mergedDfList = mergedDfList.take(mergedDfList.size - 1) + } + val writeConfig = getWriteConfig(hudiOpts) + new SparkRDDWriteClient(new HoodieSparkEngineContext(jsc), writeConfig) + .rollback(lastInstant.getTimestamp) + + if (lastInstant.getAction != ActionType.clean.name()) { + assertEquals(ActionType.rollback.name(), getLatestMetaClient(true).getActiveTimeline.lastInstant().get().getAction) + } + lastInstant + } + + protected def executeFunctionNTimes[T](function0: Function0[T], n: Int): Unit = { + for (_ <- 1 to n) { + function0.apply() + } + } + + protected def deleteLastCompletedCommitFromDataAndMetadataTimeline(hudiOpts: Map[String, String]): Unit = { + val writeConfig = getWriteConfig(hudiOpts) + val lastInstant = getHoodieTable(metaClient, writeConfig).getCompletedCommitsTimeline.lastInstant().get() + val metadataTableMetaClient = getHoodieTable(metaClient, writeConfig).getMetadataTable.asInstanceOf[HoodieBackedTableMetadata].getMetadataMetaClient + val metadataTableLastInstant = metadataTableMetaClient.getCommitsTimeline.lastInstant().get() + assertTrue(fs.delete(new Path(metaClient.getMetaPath, lastInstant.getFileName), false)) + assertTrue(fs.delete(new Path(metadataTableMetaClient.getMetaPath, metadataTableLastInstant.getFileName), false)) + mergedDfList = mergedDfList.take(mergedDfList.size - 1) + } + + protected def deleteLastCompletedCommitFromTimeline(hudiOpts: Map[String, String]): Unit = { + val writeConfig = getWriteConfig(hudiOpts) + val lastInstant = getHoodieTable(metaClient, writeConfig).getCompletedCommitsTimeline.lastInstant().get() + assertTrue(fs.delete(new Path(metaClient.getMetaPath, lastInstant.getFileName), false)) + mergedDfList = mergedDfList.take(mergedDfList.size - 1) + } + + protected def getMetadataMetaClient(hudiOpts: Map[String, String]): HoodieTableMetaClient = { + getHoodieTable(metaClient, getWriteConfig(hudiOpts)).getMetadataTable.asInstanceOf[HoodieBackedTableMetadata].getMetadataMetaClient + } + + protected def getLatestCompactionInstant: org.apache.hudi.common.util.Option[HoodieInstant] = { + getLatestMetaClient(false).getActiveTimeline + .filter(JavaConversions.getPredicate(s => Option( + try { + val commitMetadata = MetadataConversionUtils.getHoodieCommitMetadata(metaClient, s) + .orElse(new HoodieCommitMetadata()) + commitMetadata + } catch { + case _: Exception => new HoodieCommitMetadata() + }) + .map(c => c.getOperationType == WriteOperationType.COMPACT) + .get)) + .lastInstant() + } + + protected def getLatestClusteringInstant: org.apache.hudi.common.util.Option[HoodieInstant] = { + getLatestMetaClient(false).getActiveTimeline.getCompletedReplaceTimeline.lastInstant() + } + + protected def doWriteAndValidateDataAndPartitionStats(hudiOpts: Map[String, String], + operation: String, + saveMode: SaveMode, + validate: Boolean = true): DataFrame = { + var latestBatch: mutable.Buffer[String] = null + if (operation == UPSERT_OPERATION_OPT_VAL) { + val instantTime = getInstantTime + val records = recordsToStrings(dataGen.generateUniqueUpdates(instantTime, 5)) + records.addAll(recordsToStrings(dataGen.generateInserts(instantTime, 5))) + latestBatch = records.asScala + } else if (operation == INSERT_OVERWRITE_OPERATION_OPT_VAL) { + latestBatch = recordsToStrings(dataGen.generateInsertsForPartition( + getInstantTime, 5, dataGen.getPartitionPaths.last)).asScala + } else { + latestBatch = recordsToStrings(dataGen.generateInserts(getInstantTime, 5)).asScala + } + val latestBatchDf = spark.read.json(spark.sparkContext.parallelize(latestBatch, 2)) + latestBatchDf.cache() + latestBatchDf.write.format("org.apache.hudi") + .options(hudiOpts) + .option(OPERATION.key, operation) + .mode(saveMode) + .save(basePath) + val deletedDf = calculateMergedDf(latestBatchDf, operation) + deletedDf.cache() + if (validate) { + validateDataAndPartitionStats(deletedDf) + } + deletedDf.unpersist() + latestBatchDf + } + + /** + * @return [[DataFrame]] that should not exist as of the latest instant; used for non-existence validation. + */ + protected def calculateMergedDf(latestBatchDf: DataFrame, operation: String): DataFrame = { + val prevDfOpt = mergedDfList.lastOption + if (prevDfOpt.isEmpty) { + mergedDfList = mergedDfList :+ latestBatchDf + sparkSession.emptyDataFrame + } else { + if (operation == INSERT_OVERWRITE_TABLE_OPERATION_OPT_VAL) { + mergedDfList = mergedDfList :+ latestBatchDf + // after insert_overwrite_table, all previous snapshot's records should be deleted from RLI + prevDfOpt.get + } else if (operation == INSERT_OVERWRITE_OPERATION_OPT_VAL) { + val overwrittenPartitions = latestBatchDf.select("partition") + .collectAsList().stream().map[String](JavaConversions.getFunction[Row, String](r => r.getString(0))).collect(Collectors.toList[String]) + val prevDf = prevDfOpt.get + val latestSnapshot = prevDf + .filter(not(col("partition").isInCollection(overwrittenPartitions))) + .union(latestBatchDf) + mergedDfList = mergedDfList :+ latestSnapshot + + // after insert_overwrite (partition), all records in the overwritten partitions should be deleted from RLI + prevDf.filter(col("partition").isInCollection(overwrittenPartitions)) + } else { + val prevDf = prevDfOpt.get + val prevDfOld = prevDf.join(latestBatchDf, prevDf("_row_key") === latestBatchDf("_row_key") + && prevDf("partition") === latestBatchDf("partition"), "leftanti") + val latestSnapshot = prevDfOld.union(latestBatchDf) + mergedDfList = mergedDfList :+ latestSnapshot + sparkSession.emptyDataFrame + } + } + } + + private def getInstantTime: String = { + String.format("%03d", new Integer(instantTime.incrementAndGet())) + } + + protected def getWriteConfig(hudiOpts: Map[String, String]): HoodieWriteConfig = { + val props = TypedProperties.fromMap(JavaConverters.mapAsJavaMapConverter(hudiOpts).asJava) + HoodieWriteConfig.newBuilder() + .withProps(props) + .withPath(basePath) + .build() + } + + protected def validateDataAndPartitionStats(inputDf: DataFrame = sparkSession.emptyDataFrame): Unit = { + metaClient = HoodieTableMetaClient.reload(metaClient) + val readDf = spark.read.format("hudi").load(basePath) + val partitionStatsIndex = new PartitionStatsIndexSupport( + spark, + inputDf.schema, + HoodieMetadataConfig.newBuilder().enable(true).withMetadataIndexPartitionStats(true).build(), + metaClient) + val partitionStats = partitionStatsIndex.loadColumnStatsIndexRecords(List("partition"), shouldReadInMemory = true).collectAsList() + assertEquals(0, partitionStats.size()) + val prevDf = mergedDfList.last.drop("tip_history") + val nonMatchingRecords = readDf.drop("_hoodie_commit_time", "_hoodie_commit_seqno", "_hoodie_record_key", Review Comment: yeah there is.. reusing that now. -- This is an automated message from the Apache Git Service. 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