zhangyue19921010 commented on code in PR #13365: URL: https://github.com/apache/hudi/pull/13365#discussion_r2166976796
########## hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/client/clustering/run/strategy/SparkBinaryCopyClusteringExecutionStrategy.java: ########## @@ -0,0 +1,188 @@ +/* + * 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.client.clustering.run.strategy; + +import org.apache.hudi.avro.model.HoodieClusteringPlan; +import org.apache.hudi.client.WriteStatus; +import org.apache.hudi.client.common.HoodieSparkEngineContext; +import org.apache.hudi.common.config.HoodieStorageConfig; +import org.apache.hudi.common.config.SerializableSchema; +import org.apache.hudi.common.data.HoodieData; +import org.apache.hudi.common.engine.HoodieEngineContext; +import org.apache.hudi.common.engine.TaskContextSupplier; +import org.apache.hudi.common.fs.FSUtils; +import org.apache.hudi.common.model.ClusteringGroupInfo; +import org.apache.hudi.common.model.HoodieFileGroupId; +import org.apache.hudi.common.util.Option; +import org.apache.hudi.config.HoodieWriteConfig; +import org.apache.hudi.data.HoodieJavaRDD; +import org.apache.hudi.io.HoodieBinaryCopyHandle; +import org.apache.hudi.io.BinaryCopyHandleFactory; +import org.apache.hudi.parquet.io.ParquetBinaryCopyChecker; +import org.apache.hudi.storage.StoragePath; +import org.apache.hudi.table.HoodieTable; +import org.apache.hudi.table.action.HoodieWriteMetadata; + +import org.apache.avro.Schema; +import org.apache.hadoop.conf.Configuration; +import org.apache.spark.api.java.JavaRDD; +import org.apache.spark.api.java.JavaSparkContext; +import org.slf4j.Logger; +import org.slf4j.LoggerFactory; + +import java.util.ArrayList; +import java.util.List; +import java.util.Map; +import java.util.stream.Collectors; +import java.util.stream.Stream; +import java.util.stream.StreamSupport; + +import static org.apache.hudi.common.model.HoodieFileFormat.PARQUET; +import static org.apache.hudi.common.model.HoodieTableType.COPY_ON_WRITE; +import static org.apache.hudi.config.HoodieClusteringConfig.PLAN_STRATEGY_SORT_COLUMNS; + +/** + * Clustering strategy to submit single spark jobs using streaming copy + * PAY ATTENTION!!! + * IN THIS STRATEGY + * 1. Only support clustering for cow table. + * 2. Sort function is not supported yet. + * 3. Each clustering group only has one task to write. + */ +public class SparkBinaryCopyClusteringExecutionStrategy<T> extends SparkSortAndSizeExecutionStrategy<T> { + + private static final Logger LOG = LoggerFactory.getLogger(SparkBinaryCopyClusteringExecutionStrategy.class); + + public SparkBinaryCopyClusteringExecutionStrategy( + HoodieTable table, + HoodieEngineContext engineContext, + HoodieWriteConfig writeConfig) { + super(table, engineContext, writeConfig); + } + + @Override + public HoodieWriteMetadata<HoodieData<WriteStatus>> performClustering( + HoodieClusteringPlan clusteringPlan, + Schema schema, + String instantTime) { + + List<ClusteringGroupInfo> clusteringGroupInfos = clusteringPlan.getInputGroups() + .stream() + .map(ClusteringGroupInfo::create) + .collect(Collectors.toList()); + if (!supportBinaryStreamCopy(clusteringGroupInfos, clusteringPlan.getStrategy().getStrategyParams())) { + LOG.info("Required conditions for binary stream copy are currently not satisfied, falling back to default clustering behavior"); + HoodieWriteConfig newConfig = HoodieWriteConfig.newBuilder().withProperties(writeConfig.getProps()) + .withStorageConfig(HoodieStorageConfig.newBuilder().parquetWriteLegacyFormat("false").build()).build(); + resetWriteConfig(newConfig); + return super.performClustering(clusteringPlan, schema, instantTime); + } + LOG.info("Required conditions are currently satisfied, enabling the optimization of using binary stream copy "); + + JavaSparkContext engineContext = HoodieSparkEngineContext.getSparkContext(getEngineContext()); + TaskContextSupplier taskContextSupplier = getEngineContext().getTaskContextSupplier(); + SerializableSchema serializableSchema = new SerializableSchema(schema); + boolean shouldPreserveMetadata = Option.ofNullable(clusteringPlan.getPreserveHoodieMetadata()).orElse(false); + JavaRDD<ClusteringGroupInfo> groupInfoJavaRDD = engineContext.parallelize(clusteringGroupInfos, clusteringGroupInfos.size()); + LOG.info("number of partitions for clustering " + groupInfoJavaRDD.getNumPartitions()); + JavaRDD<WriteStatus> writeStatusRDD = groupInfoJavaRDD + .mapPartitions(clusteringOps -> { + Iterable<ClusteringGroupInfo> clusteringOpsIterable = () -> clusteringOps; + return StreamSupport.stream(clusteringOpsIterable.spliterator(), false) + .flatMap(clusteringOp -> + runClusteringForGroup( + clusteringOp, + clusteringPlan.getStrategy().getStrategyParams(), + shouldPreserveMetadata, + serializableSchema, + taskContextSupplier, + instantTime)) + .iterator(); + }); + + HoodieWriteMetadata<HoodieData<WriteStatus>> writeMetadata = new HoodieWriteMetadata<>(); + writeMetadata.setWriteStatuses(HoodieJavaRDD.of(writeStatusRDD)); + return writeMetadata; + } + + /** + * Submit job to execute clustering for the group. + */ + private Stream<WriteStatus> runClusteringForGroup(ClusteringGroupInfo clusteringOps, Map<String, String> strategyParams, + boolean preserveHoodieMetadata, SerializableSchema schema, + TaskContextSupplier taskContextSupplier, String instantTime) { + List<WriteStatus> statuses = new ArrayList<>(); + List<HoodieFileGroupId> inputFileIds = clusteringOps.getOperations() + .stream() + .map(op -> new HoodieFileGroupId(op.getPartitionPath(), op.getFileId())) + .collect(Collectors.toList()); + List<StoragePath> inputFilePaths = clusteringOps.getOperations() + .stream() + .map(op -> new StoragePath(op.getDataFilePath())) + .collect(Collectors.toList()); + + BinaryCopyHandleFactory factory = new BinaryCopyHandleFactory(inputFilePaths); + HoodieBinaryCopyHandle handler = factory.create( + getWriteConfig(), + instantTime, + getHoodieTable(), + inputFileIds.get(0).getPartitionPath(), + FSUtils.createNewFileIdPfx(), + taskContextSupplier); + + handler.write(); + statuses.addAll(handler.close()); + return statuses.stream(); + } + + /** + * 1. Check Table type + * 2. Check bloom filter type code + * 3. Check Array Type Schema consistency affected by hoodie.parquet.writelegacyformat.enabled and spark.hadoop.parquet.avro.write-old-list-structure + * 4. Check Schema Optional or Required consistency for the same field + */ + public boolean supportBinaryStreamCopy(List<ClusteringGroupInfo> inputGroups, Map<String, String> strategyParams) { + if (getHoodieTable().getMetaClient().getTableType() != COPY_ON_WRITE) { + LOG.warn("Only support CoW table. Will fall back to common clustering execution strategy."); + return false; + } + Option<String[]> orderByColumnsOpt = + Option.ofNullable(strategyParams.get(PLAN_STRATEGY_SORT_COLUMNS.key())) + .map(listStr -> listStr.split(",")); + + if (orderByColumnsOpt.isPresent()) { + LOG.warn("Not support to sort input records. Will fall back to common clustering execution strategy."); + return false; + } + + JavaSparkContext engineContext = HoodieSparkEngineContext.getSparkContext(getEngineContext()); + + List<ParquetBinaryCopyChecker.ParquetFileInfo> fileStatus = engineContext.parallelize(inputGroups, inputGroups.size()) + .flatMap(group -> group.getOperations().iterator()) + .map(op -> { + String filePath = op.getDataFilePath(); + if (!filePath.endsWith(PARQUET.getFileExtension())) { + return new ParquetBinaryCopyChecker.ParquetFileInfo(false, null, null); Review Comment: Yes we need to fall back for not parquet format for now. -- 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. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
