openinx commented on a change in pull request #1185: URL: https://github.com/apache/iceberg/pull/1185#discussion_r478818385
########## File path: flink/src/main/java/org/apache/iceberg/flink/sink/IcebergFilesCommitter.java ########## @@ -0,0 +1,229 @@ +/* + * 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.iceberg.flink.sink; + +import java.util.Comparator; +import java.util.List; +import java.util.Map; +import java.util.NavigableMap; +import java.util.SortedMap; +import org.apache.flink.api.common.state.ListState; +import org.apache.flink.api.common.state.ListStateDescriptor; +import org.apache.flink.api.common.typeinfo.BasicTypeInfo; +import org.apache.flink.api.common.typeinfo.TypeInformation; +import org.apache.flink.api.java.typeutils.ListTypeInfo; +import org.apache.flink.runtime.state.StateInitializationContext; +import org.apache.flink.runtime.state.StateSnapshotContext; +import org.apache.flink.streaming.api.operators.AbstractStreamOperator; +import org.apache.flink.streaming.api.operators.BoundedOneInput; +import org.apache.flink.streaming.api.operators.OneInputStreamOperator; +import org.apache.flink.streaming.runtime.streamrecord.StreamRecord; +import org.apache.flink.table.runtime.typeutils.SortedMapTypeInfo; +import org.apache.hadoop.conf.Configuration; +import org.apache.iceberg.AppendFiles; +import org.apache.iceberg.DataFile; +import org.apache.iceberg.Snapshot; +import org.apache.iceberg.Table; +import org.apache.iceberg.flink.TableLoader; +import org.apache.iceberg.hadoop.SerializableConfiguration; +import org.apache.iceberg.relocated.com.google.common.base.Preconditions; +import org.apache.iceberg.relocated.com.google.common.collect.ImmutableList; +import org.apache.iceberg.relocated.com.google.common.collect.Lists; +import org.apache.iceberg.relocated.com.google.common.collect.Maps; +import org.apache.iceberg.types.Comparators; +import org.apache.iceberg.types.Types; +import org.slf4j.Logger; +import org.slf4j.LoggerFactory; + +class IcebergFilesCommitter extends AbstractStreamOperator<Void> + implements OneInputStreamOperator<DataFile, Void>, BoundedOneInput { + + private static final long serialVersionUID = 1L; + private static final long INITIAL_CHECKPOINT_ID = -1L; + + private static final Logger LOG = LoggerFactory.getLogger(IcebergFilesCommitter.class); + private static final String FLINK_JOB_ID = "flink.job-id"; + + // The max checkpoint id we've committed to iceberg table. As the flink's checkpoint is always increasing, so we could + // correctly commit all the data files whose checkpoint id is greater than the max committed one to iceberg table, for + // avoiding committing the same data files twice. This id will be attached to iceberg's meta when committing the + // iceberg transaction. + private static final String MAX_COMMITTED_CHECKPOINT_ID = "flink.max-committed-checkpoint-id"; + + // TableLoader to load iceberg table lazily. + private final TableLoader tableLoader; + private final SerializableConfiguration hadoopConf; + + // A sorted map to maintain the completed data files for each pending checkpointId (which have not been committed + // to iceberg table). We need a sorted map here because there's possible that few checkpoints snapshot failed, for + // example: the 1st checkpoint have 2 data files <1, <file0, file1>>, the 2st checkpoint have 1 data files + // <2, <file3>>. Snapshot for checkpoint#1 interrupted because of network/disk failure etc, while we don't expect + // any data loss in iceberg table. So we keep the finished files <1, <file0, file1>> in memory and retry to commit + // iceberg table when the next checkpoint happen. + private final NavigableMap<Long, List<DataFile>> dataFilesPerCheckpoint = Maps.newTreeMap(); Review comment: Yeah, I saw that it will archive all the finished data files into a manifest file and maintain only the manifest files in state backend. (https://github.com/apache/iceberg/pull/856/files#diff-0245903e25b2cace005c52b2c7b130bbR372) . For my understanding, that's a great point to handle the case that we fail to commit to iceberg table frequently (because we'v buffered all the data files in the manifest files rather than flink state backend), but I'm no sure whether it is a common case for most of users, the commit failure should be easily found if they separated the data files regions from the metastore region, others also use this way to maitain their data and meta ? or their states are enough to maintain those uncommitted data files ? If the commit failure is a common case, I'd happy to contribute to make those data files buffered in a manifest file. For now, I think we can make the simple state way go firstly. Does that make sense ? ---------------------------------------------------------------- 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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