n3nash commented on a change in pull request #2263: URL: https://github.com/apache/hudi/pull/2263#discussion_r535652862
########## File path: hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/table/action/cluster/SparkRunClusteringCommitActionExecutor.java ########## @@ -0,0 +1,159 @@ +/* + * 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.table.action.cluster; + +import org.apache.avro.Schema; +import org.apache.avro.generic.IndexedRecord; +import org.apache.hadoop.fs.Path; +import org.apache.hudi.avro.HoodieAvroUtils; +import org.apache.hudi.avro.model.HoodieClusteringGroup; +import org.apache.hudi.avro.model.HoodieClusteringPlan; +import org.apache.hudi.client.SparkTaskContextSupplier; +import org.apache.hudi.client.WriteStatus; +import org.apache.hudi.client.common.HoodieEngineContext; +import org.apache.hudi.client.common.HoodieSparkEngineContext; +import org.apache.hudi.common.model.HoodieCommitMetadata; +import org.apache.hudi.common.model.HoodieKey; +import org.apache.hudi.common.model.HoodieRecord; +import org.apache.hudi.common.model.HoodieRecordPayload; +import org.apache.hudi.common.model.WriteOperationType; +import org.apache.hudi.common.table.log.HoodieFileSliceReader; +import org.apache.hudi.common.table.log.HoodieMergedLogRecordScanner; +import org.apache.hudi.common.table.timeline.HoodieInstant; +import org.apache.hudi.common.table.timeline.HoodieTimeline; +import org.apache.hudi.common.util.ClusteringUtils; +import org.apache.hudi.common.util.CommitUtils; +import org.apache.hudi.common.util.Option; +import org.apache.hudi.common.util.ReflectionUtils; +import org.apache.hudi.common.util.collection.Pair; +import org.apache.hudi.config.HoodieWriteConfig; +import org.apache.hudi.exception.HoodieClusteringException; +import org.apache.hudi.io.IOUtils; +import org.apache.hudi.io.storage.HoodieFileReader; +import org.apache.hudi.io.storage.HoodieFileReaderFactory; +import org.apache.hudi.table.HoodieTable; +import org.apache.hudi.table.action.HoodieWriteMetadata; +import org.apache.hudi.table.action.cluster.strategy.RunClusteringStrategy; +import org.apache.hudi.table.action.commit.BaseSparkCommitActionExecutor; +import org.apache.log4j.LogManager; +import org.apache.log4j.Logger; +import org.apache.spark.api.java.JavaRDD; +import org.apache.spark.api.java.JavaSparkContext; + +import java.io.IOException; +import java.util.Collection; +import java.util.List; +import java.util.Map; +import java.util.concurrent.CompletableFuture; +import java.util.stream.Collectors; + +public class SparkRunClusteringCommitActionExecutor<T extends HoodieRecordPayload<T>> + extends BaseSparkCommitActionExecutor<T> { + + private static final Logger LOG = LogManager.getLogger(SparkRunClusteringCommitActionExecutor.class); + private final HoodieClusteringPlan clusteringPlan; + + public SparkRunClusteringCommitActionExecutor(HoodieEngineContext context, + HoodieWriteConfig config, HoodieTable table, + String instantTime) { + super(context, config, table, instantTime, WriteOperationType.CLUSTER); + this.clusteringPlan = ClusteringUtils.getClusteringPlan(table.getMetaClient(), HoodieTimeline.getReplaceCommitRequestedInstant(instantTime)) + .map(Pair::getRight).orElseThrow(() -> new HoodieClusteringException("Unable to read clustering plan for instant: " + instantTime)); + } + + @Override + public HoodieWriteMetadata<JavaRDD<WriteStatus>> execute() { + HoodieInstant instant = HoodieTimeline.getReplaceCommitRequestedInstant(instantTime); + // Mark instant as clustering inflight + table.getActiveTimeline().transitionReplaceRequestedToInflight(instant, Option.empty()); + table.getMetaClient().reloadActiveTimeline(); + + JavaSparkContext engineContext = HoodieSparkEngineContext.getSparkContext(context); + // run clustering for each group async and collect WriteStatus + JavaRDD<WriteStatus> writeStatusRDD = clusteringPlan.getInputGroups().stream() + .map(inputGroup -> runClusteringForGroupAsync(inputGroup, clusteringPlan.getStrategy().getStrategyParams())) + .map(CompletableFuture::join) + .reduce((rdd1, rdd2) -> rdd1.union(rdd2)).orElse(engineContext.emptyRDD()); + if (writeStatusRDD.isEmpty()) { + throw new HoodieClusteringException("Clustering plan produced 0 WriteStatus for " + instantTime + " #groups: " + clusteringPlan.getInputGroups().size()); + } + + HoodieWriteMetadata<JavaRDD<WriteStatus>> writeMetadata = buildWriteMetadata(writeStatusRDD); + updateIndexAndCommitIfNeeded(writeStatusRDD, writeMetadata); + if (!writeMetadata.getCommitMetadata().isPresent()) { + HoodieCommitMetadata commitMetadata = CommitUtils.buildMetadata(writeStatusRDD.map(WriteStatus::getStat).collect(), writeMetadata.getPartitionToReplaceFileIds(), + extraMetadata, operationType, getSchemaToStoreInCommit(), getCommitActionType()); + writeMetadata.setCommitMetadata(Option.of(commitMetadata)); + } + return writeMetadata; + } + + private CompletableFuture<JavaRDD<WriteStatus>> runClusteringForGroupAsync(HoodieClusteringGroup clusteringGroup, Map<String, String> strategyParams) { + CompletableFuture<JavaRDD<WriteStatus>> writeStatusesFuture = CompletableFuture.supplyAsync(() -> { + JavaSparkContext jsc = HoodieSparkEngineContext.getSparkContext(context); + JavaRDD<HoodieRecord<? extends HoodieRecordPayload>> inputRecords = jsc.parallelize(clusteringGroup.getSlices(), clusteringGroup.getSlices().size()).map(sliceInfo -> { + long maxMemoryPerCompaction = IOUtils.getMaxMemoryPerCompaction(new SparkTaskContextSupplier(), config.getProps()); + LOG.info("MaxMemoryPerCompaction run as part of clustering => " + maxMemoryPerCompaction); + try { + Schema readerSchema = HoodieAvroUtils.addMetadataFields(new Schema.Parser().parse(config.getSchema())); + HoodieFileReader<? extends IndexedRecord> baseFileReader = HoodieFileReaderFactory.getFileReader(table.getHadoopConf(), new Path(sliceInfo.getDataFilePath())); + HoodieMergedLogRecordScanner scanner = new HoodieMergedLogRecordScanner(table.getMetaClient().getFs(), Review comment: @satishkotha I see the new one looks messy, if the runtime/difference in performance is the same for MergedScanner and no memory overhead of FileSlices without any log files, let's keep your other implementation with MergedScanner for both. 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