nsivabalan commented on code in PR #9553: URL: https://github.com/apache/hudi/pull/9553#discussion_r1316520533
########## hudi-client/hudi-client-common/src/main/java/org/apache/hudi/client/utils/CommitMetadataUtils.java: ########## @@ -0,0 +1,220 @@ +/* + * 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.utils; + +import org.apache.hudi.common.config.SerializableConfiguration; +import org.apache.hudi.common.data.HoodiePairData; +import org.apache.hudi.common.engine.HoodieEngineContext; +import org.apache.hudi.common.fs.FSUtils; +import org.apache.hudi.common.function.SerializableBiFunction; +import org.apache.hudi.common.function.SerializableFunction; +import org.apache.hudi.common.function.SerializablePairFunction; +import org.apache.hudi.common.model.HoodieCommitMetadata; +import org.apache.hudi.common.model.HoodieDeltaWriteStat; +import org.apache.hudi.common.model.HoodieLogFile; +import org.apache.hudi.common.model.HoodieTableType; +import org.apache.hudi.common.model.HoodieWriteStat; +import org.apache.hudi.common.table.timeline.HoodieActiveTimeline; +import org.apache.hudi.common.util.Option; +import org.apache.hudi.common.util.StringUtils; +import org.apache.hudi.common.util.collection.Pair; +import org.apache.hudi.config.HoodieWriteConfig; +import org.apache.hudi.table.HoodieTable; +import org.apache.hudi.table.marker.WriteMarkers; +import org.apache.hudi.table.marker.WriteMarkersFactory; + +import org.apache.hadoop.conf.Configuration; +import org.apache.hadoop.fs.FileStatus; +import org.apache.hadoop.fs.FileSystem; +import org.apache.hadoop.fs.Path; + +import java.io.IOException; +import java.util.ArrayList; +import java.util.Collections; +import java.util.HashMap; +import java.util.HashSet; +import java.util.List; +import java.util.Map; +import java.util.Set; +import java.util.stream.Collectors; + +public class CommitMetadataUtils { + + /* In spark mor table, task retries may generate log files which are not included in write status. + * We need to add these to CommitMetadata so that it will be synced to MDT. + */ + public static HoodieCommitMetadata reconcileMetadataForMissingFiles(HoodieTable table, String commitActionType, String instantTime, + HoodieCommitMetadata commitMetadata, HoodieWriteConfig config, + HoodieEngineContext context, Configuration hadoopConf, String classNameForContext) throws IOException { + if (!table.getMetaClient().getTableConfig().getTableType().equals(HoodieTableType.MERGE_ON_READ) + || !commitActionType.equals(HoodieActiveTimeline.DELTA_COMMIT_ACTION)) { + return commitMetadata; + } + + WriteMarkers markers = WriteMarkersFactory.get(config.getMarkersType(), table, instantTime); + // if there is log files in this delta commit, we search any invalid log files generated by failed spark task + boolean hasLogFileInDeltaCommit = commitMetadata.getPartitionToWriteStats() + .values().stream().flatMap(List::stream) + .anyMatch(writeStat -> FSUtils.isLogFile(new Path(config.getBasePath(), writeStat.getPath()).getName())); + if (hasLogFileInDeltaCommit) { // skip for COW table + // get all log files generated by makers + Set<String> allLogFilesMarkerPath = new HashSet<>(markers.getAppendedLogPaths(context, config.getFinalizeWriteParallelism())); + Set<String> logFilesMarkerPath = new HashSet<>(); + allLogFilesMarkerPath.stream().filter(logFilePath -> !logFilePath.endsWith("cdc")).forEach(logFilePath -> logFilesMarkerPath.add(logFilePath)); + + // remove valid log files + for (Map.Entry<String, List<HoodieWriteStat>> partitionAndWriteStats : commitMetadata.getPartitionToWriteStats().entrySet()) { + for (HoodieWriteStat hoodieWriteStat : partitionAndWriteStats.getValue()) { + logFilesMarkerPath.remove(hoodieWriteStat.getPath()); + } + } + + // remaining are log files generated by retried spark task, let's generate write stat for them + if (logFilesMarkerPath.size() > 0) { + SerializableConfiguration serializableConfiguration = new SerializableConfiguration(hadoopConf); + context.setJobStatus(classNameForContext, "Preparing data for missing files to assit with generatin write stats"); + // populate partition -> map (fileId -> HoodieWriteStat) // we just need one write stat per fileID to fetch some info about + // the file slice of interest to populate WriteStat. + HoodiePairData<String, Map<String, HoodieWriteStat>> partitionToWriteStatHoodieData = getPartitionToFileIdToFilesMap(commitMetadata, context); + + String localBasePath = config.getBasePath(); + // populate partition -> map (fileId -> List <missing log file names>) + HoodiePairData<String, Map<String, List<String>>> partitionToMissingLogFilesHoodieData = + getPartitionToFileIdToMissingLogFileMap(localBasePath, logFilesMarkerPath, context, config.getFileListingParallelism()); + + // TODO: make one call per partition to fetch file sizes. + context.setJobStatus(classNameForContext, "Generating writeStat for missing log files"); + + // lets join both to generate write stats for missing log files + List<Pair<String, List<HoodieWriteStat>>> additionalLogFileWriteStat = partitionToWriteStatHoodieData + .join(partitionToMissingLogFilesHoodieData) Review Comment: if there is no data file produced i.e. if a file slice is not part of in memory WriteStatus, I don't think there could be a scenario where we find additional missing files. These missing files are created due to spark retries. and this is targetting a successful commit. So, I can't think of a scenario where in-memory write status does not have a file slice, while retries created them. for a partially failed commit, it could happen which our markers will handle it. but good point though. -- 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]
