n3nash commented on a change in pull request #2263: URL: https://github.com/apache/hudi/pull/2263#discussion_r533626479
########## File path: hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/table/action/cluster/SparkRunClusteringCommitActionExecutor.java ########## @@ -0,0 +1,153 @@ +/* + * 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.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); + // read rdd from input groups in plan + JavaRDD<WriteStatus> writeStatuses = clusteringPlan.getInputGroups().stream() + .map(inputGroup -> runClusteringForGroup(inputGroup, clusteringPlan.getStrategy().getStrategyParams())) + .reduce((rdd1, rdd2) -> engineContext.union(rdd1, rdd2)).orElse(engineContext.emptyRDD()); + if (writeStatuses.isEmpty()) { + throw new HoodieClusteringException("Clustering plan produced 0 WriteStatus for " + instantTime + " #groups: " + clusteringPlan.getInputGroups().size()); + } + // merge all write status + HoodieWriteMetadata<JavaRDD<WriteStatus>> writeMetadata = buildWriteMetadata(writeStatuses); + updateIndexAndCommitIfNeeded(writeStatuses, writeMetadata); + if (!writeMetadata.getCommitMetadata().isPresent()) { + HoodieCommitMetadata commitMetadata = CommitUtils.buildMetadata(writeStatuses.map(WriteStatus::getStat).collect(), writeMetadata.getPartitionToReplaceFileIds(), + extraMetadata, operationType, getSchemaToStoreInCommit(), getCommitActionType()); + writeMetadata.setCommitMetadata(Option.of(commitMetadata)); + } + return writeMetadata; + } + + private JavaRDD<WriteStatus> runClusteringForGroup(HoodieClusteringGroup clusteringGroup, Map<String, String> strategyParams) { Review comment: Yes, like we discussed offline, we should have a config to limit the number of clustering groups to avoid someone setting wrong configs for things like maxDataPerGroup and then result in a large number of RDDs to be unioned. I think we should still do a quick test to see if there is any degradation due to union before we land this diff so we are aware. It should be as simple as writing a test case that loops over code TestUnionPerformance test for 10000 records long startTime = System.currentMillis(); RDD rdd = jsc.parallelize(Arrays.asList(record)) for (record in records) { rdd.union(jsc.parallelize(Arrays.asList(record))) } rdd.collect(); writeClient.bulkInsert(rdd); sout("time taken with union" + System.currentMillis - starttime) long startTime = System.currentMillis(); RDD rdd = jsc.parallelize(records) rdd.collect(); writeClient.bulkInsert(rdd); sout("time taken without union" + System.currentMillis - starttime) ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. 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