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[flink] Replace legacy SourceFunction with v2 Source
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yunfengzhou-hub committed Nov 22, 2024
1 parent c3a7e3b commit 0bb8152
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Original file line number Diff line number Diff line change
Expand Up @@ -77,12 +77,12 @@
* pass the watermark recorded in the snapshot.
* </ol>
*/
public class MonitorFunction extends RichSourceFunction<Split>
public class MonitorSource extends RichSourceFunction<Split>
implements CheckpointedFunction, CheckpointListener {

private static final long serialVersionUID = 1L;

private static final Logger LOG = LoggerFactory.getLogger(MonitorFunction.class);
private static final Logger LOG = LoggerFactory.getLogger(MonitorSource.class);

private final ReadBuilder readBuilder;
private final long monitorInterval;
Expand All @@ -97,7 +97,7 @@ public class MonitorFunction extends RichSourceFunction<Split>
private transient ListState<Tuple2<Long, Long>> nextSnapshotState;
private transient TreeMap<Long, Long> nextSnapshotPerCheckpoint;

public MonitorFunction(
public MonitorSource(
ReadBuilder readBuilder, long monitorInterval, boolean emitSnapshotWatermark) {
this.readBuilder = readBuilder;
this.monitorInterval = monitorInterval;
Expand Down Expand Up @@ -238,7 +238,7 @@ public static DataStream<RowData> buildSource(
BucketMode bucketMode) {
SingleOutputStreamOperator<Split> singleOutputStreamOperator =
env.addSource(
new MonitorFunction(
new MonitorSource(
readBuilder, monitorInterval, emitSnapshotWatermark),
name + "-Monitor",
new JavaTypeInfo<>(Split.class))
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Original file line number Diff line number Diff line change
@@ -0,0 +1,277 @@
/*
* 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.paimon.flink.source.operator;

import org.apache.paimon.flink.utils.JavaTypeInfo;
import org.apache.paimon.table.BucketMode;
import org.apache.paimon.table.sink.ChannelComputer;
import org.apache.paimon.table.source.DataSplit;
import org.apache.paimon.table.source.EndOfScanException;
import org.apache.paimon.table.source.ReadBuilder;
import org.apache.paimon.table.source.Split;
import org.apache.paimon.table.source.StreamTableScan;

import org.apache.flink.api.common.state.CheckpointListener;
import org.apache.flink.api.common.state.ListState;
import org.apache.flink.api.common.state.ListStateDescriptor;
import org.apache.flink.api.common.typeinfo.TypeInformation;
import org.apache.flink.api.common.typeutils.TypeSerializer;
import org.apache.flink.api.common.typeutils.base.LongSerializer;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.api.java.typeutils.runtime.TupleSerializer;
import org.apache.flink.runtime.state.FunctionInitializationContext;
import org.apache.flink.runtime.state.FunctionSnapshotContext;
import org.apache.flink.streaming.api.checkpoint.CheckpointedFunction;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.datastream.SingleOutputStreamOperator;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.functions.source.RichSourceFunction;
import org.apache.flink.streaming.api.watermark.Watermark;
import org.apache.flink.table.data.RowData;
import org.apache.flink.util.Preconditions;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

import java.util.ArrayList;
import java.util.List;
import java.util.NavigableMap;
import java.util.OptionalLong;
import java.util.TreeMap;

import static org.apache.paimon.table.BucketMode.BUCKET_UNAWARE;

/**
* This is the single (non-parallel) monitoring task, it is responsible for:
*
* <ol>
* <li>Monitoring snapshots of the Paimon table.
* <li>Creating the {@link Split splits} corresponding to the incremental files
* <li>Assigning them to downstream tasks for further processing.
* </ol>
*
* <p>The splits to be read are forwarded to the downstream {@link ReadOperator} which can have
* parallelism greater than one.
*
* <p>Currently, there are two features that rely on this monitor:
*
* <ol>
* <li>Consumer-id: rely on this function to do aligned snapshot consumption, and ensure that all
* data in a snapshot is consumed within each checkpoint.
* <li>Snapshot-watermark: when there is no watermark definition, the default Paimon table will
* pass the watermark recorded in the snapshot.
* </ol>
*/
public class MonitorSource extends RichSourceFunction<Split>
implements CheckpointedFunction, CheckpointListener {

private static final long serialVersionUID = 1L;

private static final Logger LOG = LoggerFactory.getLogger(MonitorSource.class);

private final ReadBuilder readBuilder;
private final long monitorInterval;
private final boolean emitSnapshotWatermark;

private volatile boolean isRunning = true;

private transient StreamTableScan scan;
private transient SourceContext<Split> ctx;

private transient ListState<Long> checkpointState;
private transient ListState<Tuple2<Long, Long>> nextSnapshotState;
private transient TreeMap<Long, Long> nextSnapshotPerCheckpoint;

public MonitorSource(
ReadBuilder readBuilder, long monitorInterval, boolean emitSnapshotWatermark) {
this.readBuilder = readBuilder;
this.monitorInterval = monitorInterval;
this.emitSnapshotWatermark = emitSnapshotWatermark;
}

@Override
public void initializeState(FunctionInitializationContext context) throws Exception {
this.scan = readBuilder.newStreamScan();

this.checkpointState =
context.getOperatorStateStore()
.getListState(
new ListStateDescriptor<>(
"next-snapshot", LongSerializer.INSTANCE));

@SuppressWarnings("unchecked")
final Class<Tuple2<Long, Long>> typedTuple =
(Class<Tuple2<Long, Long>>) (Class<?>) Tuple2.class;
this.nextSnapshotState =
context.getOperatorStateStore()
.getListState(
new ListStateDescriptor<>(
"next-snapshot-per-checkpoint",
new TupleSerializer<>(
typedTuple,
new TypeSerializer[] {
LongSerializer.INSTANCE, LongSerializer.INSTANCE
})));

this.nextSnapshotPerCheckpoint = new TreeMap<>();

if (context.isRestored()) {
LOG.info("Restoring state for the {}.", getClass().getSimpleName());

List<Long> retrievedStates = new ArrayList<>();
for (Long entry : this.checkpointState.get()) {
retrievedStates.add(entry);
}

// given that the parallelism of the function is 1, we can only have 1 retrieved items.
Preconditions.checkArgument(
retrievedStates.size() <= 1,
getClass().getSimpleName() + " retrieved invalid state.");

if (retrievedStates.size() == 1) {
this.scan.restore(retrievedStates.get(0));
}

for (Tuple2<Long, Long> tuple2 : nextSnapshotState.get()) {
nextSnapshotPerCheckpoint.put(tuple2.f0, tuple2.f1);
}
} else {
LOG.info("No state to restore for the {}.", getClass().getSimpleName());
}
}

@Override
public void snapshotState(FunctionSnapshotContext ctx) throws Exception {
this.checkpointState.clear();
Long nextSnapshot = this.scan.checkpoint();
if (nextSnapshot != null) {
this.checkpointState.add(nextSnapshot);
this.nextSnapshotPerCheckpoint.put(ctx.getCheckpointId(), nextSnapshot);
}

List<Tuple2<Long, Long>> nextSnapshots = new ArrayList<>();
this.nextSnapshotPerCheckpoint.forEach((k, v) -> nextSnapshots.add(new Tuple2<>(k, v)));
this.nextSnapshotState.update(nextSnapshots);

if (LOG.isDebugEnabled()) {
LOG.debug("{} checkpoint {}.", getClass().getSimpleName(), nextSnapshot);
}
}

@SuppressWarnings("BusyWait")
@Override
public void run(SourceContext<Split> ctx) throws Exception {
this.ctx = ctx;
while (isRunning) {
boolean isEmpty;
synchronized (ctx.getCheckpointLock()) {
if (!isRunning) {
return;
}
try {
List<Split> splits = scan.plan().splits();
isEmpty = splits.isEmpty();
splits.forEach(ctx::collect);

if (emitSnapshotWatermark) {
Long watermark = scan.watermark();
if (watermark != null) {
ctx.emitWatermark(new Watermark(watermark));
}
}
} catch (EndOfScanException esf) {
LOG.info("Catching EndOfStreamException, the stream is finished.");
return;
}
}

if (isEmpty) {
Thread.sleep(monitorInterval);
}
}
}

@Override
public void notifyCheckpointComplete(long checkpointId) {
NavigableMap<Long, Long> nextSnapshots =
nextSnapshotPerCheckpoint.headMap(checkpointId, true);
OptionalLong max = nextSnapshots.values().stream().mapToLong(Long::longValue).max();
max.ifPresent(scan::notifyCheckpointComplete);
nextSnapshots.clear();
}

@Override
public void cancel() {
// this is to cover the case where cancel() is called before the run()
if (ctx != null) {
synchronized (ctx.getCheckpointLock()) {
isRunning = false;
}
} else {
isRunning = false;
}
}

public static DataStream<RowData> buildSource(
StreamExecutionEnvironment env,
String name,
TypeInformation<RowData> typeInfo,
ReadBuilder readBuilder,
long monitorInterval,
boolean emitSnapshotWatermark,
boolean shuffleBucketWithPartition,
BucketMode bucketMode) {
SingleOutputStreamOperator<Split> singleOutputStreamOperator =
env.addSource(
new MonitorSource(
readBuilder, monitorInterval, emitSnapshotWatermark),
name + "-Monitor",
new JavaTypeInfo<>(Split.class))
.forceNonParallel();

DataStream<Split> sourceDataStream =
bucketMode == BUCKET_UNAWARE
? shuffleUnwareBucket(singleOutputStreamOperator)
: shuffleNonUnwareBucket(
singleOutputStreamOperator, shuffleBucketWithPartition);

return sourceDataStream.transform(
name + "-Reader", typeInfo, new ReadOperator(readBuilder));
}

private static DataStream<Split> shuffleUnwareBucket(
SingleOutputStreamOperator<Split> singleOutputStreamOperator) {
return singleOutputStreamOperator.rebalance();
}

private static DataStream<Split> shuffleNonUnwareBucket(
SingleOutputStreamOperator<Split> singleOutputStreamOperator,
boolean shuffleBucketWithPartition) {
return singleOutputStreamOperator.partitionCustom(
(key, numPartitions) -> {
if (shuffleBucketWithPartition) {
return ChannelComputer.select(key.f0, key.f1, numPartitions);
}
return ChannelComputer.select(key.f1, numPartitions);
},
split -> {
DataSplit dataSplit = (DataSplit) split;
return Tuple2.of(dataSplit.partition(), dataSplit.bucket());
});
}
}
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