danny0405 commented on code in PR #6737:
URL: https://github.com/apache/hudi/pull/6737#discussion_r990953008
##########
hudi-flink-datasource/hudi-flink/src/main/java/org/apache/hudi/sink/utils/Pipelines.java:
##########
@@ -316,9 +318,8 @@ public static DataStream<HoodieRecord>
rowDataToHoodieRecord(Configuration conf,
public static DataStream<Object> hoodieStreamWrite(Configuration conf,
DataStream<HoodieRecord> dataStream) {
if (OptionsResolver.isBucketIndexType(conf)) {
WriteOperatorFactory<HoodieRecord> operatorFactory =
BucketStreamWriteOperator.getFactory(conf);
- int bucketNum = conf.getInteger(FlinkOptions.BUCKET_INDEX_NUM_BUCKETS);
- String indexKeyFields = conf.getString(FlinkOptions.INDEX_KEY_FIELD);
- BucketIndexPartitioner<HoodieKey> partitioner = new
BucketIndexPartitioner<>(bucketNum, indexKeyFields);
+ dataStream = addBucketBootstrapIfNecessary(conf, dataStream);
+ Partitioner<HoodieKey> partitioner =
BucketIndexPartitioner.instance(conf);
Review Comment:
Can we avoid the sub-pipeline for buckets metadata initializing and move
them into the `ConsistentBucketStreamWriteFunction` ?
##########
hudi-flink-datasource/hudi-flink/src/main/java/org/apache/hudi/sink/bucket/BucketStreamWriteOperator.java:
##########
@@ -18,23 +18,40 @@
package org.apache.hudi.sink.bucket;
+import org.apache.hudi.configuration.FlinkOptions;
+import org.apache.hudi.exception.HoodieException;
+import org.apache.hudi.index.HoodieIndex;
import org.apache.hudi.sink.common.AbstractWriteOperator;
import org.apache.hudi.sink.common.WriteOperatorFactory;
import org.apache.flink.configuration.Configuration;
/**
* Operator for {@link BucketStreamWriteFunction}.
- *
- * @param <I> The input type
*/
-public class BucketStreamWriteOperator<I> extends AbstractWriteOperator<I> {
+public class BucketStreamWriteOperator {
- public BucketStreamWriteOperator(Configuration conf) {
- super(new BucketStreamWriteFunction<>(conf));
+ public static <I> WriteOperatorFactory<I> getFactory(Configuration conf) {
+ String bucketEngineType = conf.get(FlinkOptions.BUCKET_INDEX_ENGINE_TYPE);
+ if
(bucketEngineType.equalsIgnoreCase(HoodieIndex.BucketIndexEngineType.SIMPLE.name()))
{
+ return WriteOperatorFactory.instance(conf, new
SimpleBucketStreamWriteOperator<>(conf));
+ } else if
(bucketEngineType.equalsIgnoreCase(HoodieIndex.BucketIndexEngineType.CONSISTENT_HASHING.name()))
{
+ return WriteOperatorFactory.instance(conf, new
ConsistentBucketStreamWriteOperator<>(conf));
+ } else {
+ throw new HoodieException("Unknown bucket index engine type: " +
bucketEngineType);
+ }
}
- public static <I> WriteOperatorFactory<I> getFactory(Configuration conf) {
- return WriteOperatorFactory.instance(conf, new
BucketStreamWriteOperator<>(conf));
+ public static class SimpleBucketStreamWriteOperator<I> extends
AbstractWriteOperator<I> {
+ public SimpleBucketStreamWriteOperator(Configuration conf) {
+ super(new BucketStreamWriteFunction<>(conf));
+ }
}
+
+ public static class ConsistentBucketStreamWriteOperator<I> extends
AbstractWriteOperator<I> {
+ public ConsistentBucketStreamWriteOperator(Configuration conf) {
Review Comment:
Avoid to use inner clazz
##########
hudi-flink-datasource/hudi-flink/src/main/java/org/apache/hudi/sink/StreamWriteFunction.java:
##########
@@ -129,6 +137,7 @@ public void snapshotState() {
// it would check the validity.
// wait for the buffer data flush out and request a new instant
flushRemaining(false);
+ this.updateStrategy.reset();
}
Review Comment:
Can we move all the consistent hashing bucket logic down to the sub-clazz ?
##########
hudi-client/hudi-client-common/src/main/java/org/apache/hudi/table/action/cluster/strategy/BaseConsistentHashingBucketClusteringPlanStrategy.java:
##########
@@ -0,0 +1,320 @@
+/*
+ * 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.strategy;
+
+import org.apache.hudi.avro.model.HoodieClusteringGroup;
+import org.apache.hudi.common.engine.HoodieEngineContext;
+import org.apache.hudi.common.fs.FSUtils;
+import org.apache.hudi.common.model.ConsistentHashingNode;
+import org.apache.hudi.common.model.FileSlice;
+import org.apache.hudi.common.model.HoodieConsistentHashingMetadata;
+import org.apache.hudi.common.model.HoodieFileFormat;
+import org.apache.hudi.common.model.HoodieRecordPayload;
+import org.apache.hudi.common.table.timeline.HoodieTimeline;
+import org.apache.hudi.common.table.view.TableFileSystemView;
+import org.apache.hudi.common.util.Option;
+import org.apache.hudi.common.util.StringUtils;
+import org.apache.hudi.common.util.ValidationUtils;
+import org.apache.hudi.common.util.collection.Triple;
+import org.apache.hudi.config.HoodieClusteringConfig;
+import org.apache.hudi.config.HoodieWriteConfig;
+import org.apache.hudi.exception.HoodieClusteringException;
+import org.apache.hudi.index.HoodieIndex;
+import org.apache.hudi.index.bucket.ConsistentBucketIdentifier;
+import org.apache.hudi.index.bucket.ConsistentBucketIndexUtils;
+import org.apache.hudi.table.HoodieTable;
+
+import org.apache.logging.log4j.LogManager;
+import org.apache.logging.log4j.Logger;
+
+import java.io.IOException;
+import java.util.ArrayList;
+import java.util.Collections;
+import java.util.Comparator;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+import java.util.stream.Collectors;
+import java.util.stream.IntStream;
+import java.util.stream.Stream;
+
+/**
+ * Clustering plan strategy specifically for consistent bucket index
+ */
+public class BaseConsistentHashingBucketClusteringPlanStrategy<T extends
HoodieRecordPayload, I, K, O>
+ extends PartitionAwareClusteringPlanStrategy<T, I, K, O> {
+
+ private static final Logger LOG =
LogManager.getLogger(BaseConsistentHashingBucketClusteringPlanStrategy.class);
+
+ public static final String METADATA_PARTITION_KEY =
"clustering.group.partition";
+ public static final String METADATA_CHILD_NODE_KEY =
"clustering.group.child.node";
+ public static final String METADATA_SEQUENCE_NUMBER_KEY =
"clustering.group.sequence.no";
+
+ public BaseConsistentHashingBucketClusteringPlanStrategy(HoodieTable table,
HoodieEngineContext engineContext,
+ HoodieWriteConfig
writeConfig) {
+ super(table, engineContext, writeConfig);
+ validate();
+ }
+
+ /**
+ * TODO maybe add config to force schedule the clustering. It could allow
clustering on partitions that are not doing write operation.
+ * Block clustering if there is any ongoing concurrent writers
+ *
+ * @return true if the schedule can proceed
+ */
+ @Override
+ public boolean checkPrecondition() {
+ HoodieTimeline timeline =
getHoodieTable().getActiveTimeline().getDeltaCommitTimeline().filterInflightsAndRequested();
+ if (!timeline.empty()) {
+ LOG.warn("When using consistent bucket, clustering cannot be scheduled
async if there are concurrent writers. "
+ + "Writer instant: " +
timeline.getInstants().collect(Collectors.toList()));
+ return false;
+ }
+ return true;
+ }
+
+ /**
+ * Generate candidate clustering file slices of the given partition.
+ * If there is inflight / requested clustering working on the partition,
then return empty list
+ * to ensure serialized update to the hashing metadata.
+ *
+ * @return candidate file slices to be clustered (i.e., sort, bucket split
or merge)
+ */
+ @Override
+ protected Stream<FileSlice> getFileSlicesEligibleForClustering(String
partition) {
+ TableFileSystemView fileSystemView = getHoodieTable().getFileSystemView();
+ boolean isPartitionInClustering =
fileSystemView.getFileGroupsInPendingClustering().anyMatch(p ->
p.getLeft().getPartitionPath().equals(partition));
+ if (isPartitionInClustering) {
+ LOG.info("Partition: " + partition + " is already in clustering, skip");
+ return Stream.empty();
+ }
+
+ return super.getFileSlicesEligibleForClustering(partition);
+ }
+
+ @Override
+ protected Map<String, String> getStrategyParams() {
+ Map<String, String> params = new HashMap<>();
+ if
(!StringUtils.isNullOrEmpty(getWriteConfig().getClusteringSortColumns())) {
+ params.put(HoodieClusteringConfig.PLAN_STRATEGY_SORT_COLUMNS.key(),
getWriteConfig().getClusteringSortColumns());
+ }
+ return params;
+ }
+
+ /**
+ * Generate cluster group based on split, merge and sort rules
+ */
+ @Override
+ protected Stream<HoodieClusteringGroup>
buildClusteringGroupsForPartition(String partitionPath, List<FileSlice>
fileSlices) {
+ Option<HoodieConsistentHashingMetadata> metadata =
ConsistentBucketIndexUtils.loadMetadata(getHoodieTable().getMetaClient(),
partitionPath);
+ ValidationUtils.checkArgument(metadata.isPresent(), "Metadata is empty for
partition: " + partitionPath);
+ ConsistentBucketIdentifier identifier = new
ConsistentBucketIdentifier(metadata.get());
+
+ // Apply split rule
+ int splitSlot = getWriteConfig().getBucketIndexMaxNumBuckets() -
identifier.getNumBuckets();
+ Triple<List<HoodieClusteringGroup>, Integer, List<FileSlice>> splitResult =
+ buildSplitClusteringGroups(identifier, fileSlices, splitSlot);
+ List<HoodieClusteringGroup> ret = new ArrayList<>(splitResult.getLeft());
+
+ // Apply merge rule
+ int mergeSlot = identifier.getNumBuckets() -
getWriteConfig().getBucketIndexMinNumBuckets() + splitResult.getMiddle();
+ Triple<List<HoodieClusteringGroup>, Integer, List<FileSlice>> mergeResult =
+ buildMergeClusteringGroup(identifier, splitResult.getRight(),
mergeSlot);
+ ret.addAll(mergeResult.getLeft());
+
+ // Apply sort only to the remaining file groups
+ ret.addAll(mergeResult.getRight().stream().map(fs -> {
+ ConsistentHashingNode oldNode =
identifier.getBucketByFileId(fs.getFileId());
+ ConsistentHashingNode newNode = new
ConsistentHashingNode(oldNode.getValue(), FSUtils.createNewFileIdPfx(),
ConsistentHashingNode.NodeTag.REPLACE);
+ return HoodieClusteringGroup.newBuilder()
+ .setSlices(getFileSliceInfo(Collections.singletonList(fs)))
+ .setNumOutputFileGroups(1)
+ .setMetrics(buildMetrics(Collections.singletonList(fs)))
+ .setExtraMetadata(constructExtraMetadata(fs.getPartitionPath(),
Collections.singletonList(newNode), identifier.getMetadata().getSeqNo()))
+ .build();
+ }).collect(Collectors.toList()));
+
+ return ret.stream();
+ }
+
+ /**
+ * Generate clustering groups according to split rules.
+ * Currently, we always split bucket into two sub-buckets.
+ *
+ * @param identifier bucket identifier
+ * @param fileSlices file slice candidate to be built as split clustering
groups
+ * @param splitSlot number of new bucket allowed to produce, in order to
constrain the upper bound of the total number of bucket
+ * @return list of clustering group, number of new buckets generated,
remaining file slice (that does not split)
+ */
+ protected Triple<List<HoodieClusteringGroup>, Integer, List<FileSlice>>
buildSplitClusteringGroups(
+ ConsistentBucketIdentifier identifier, List<FileSlice> fileSlices, int
splitSlot) {
+ List<HoodieClusteringGroup> retGroup = new ArrayList<>();
+ List<FileSlice> fsUntouched = new ArrayList<>();
+ long splitSize = getSplitSize();
+ int remainingSplitSlot = splitSlot;
+ for (FileSlice fs : fileSlices) {
+ boolean needSplit = fs.getTotalFileSize() > splitSize;
+ if (!needSplit || remainingSplitSlot == 0) {
+ fsUntouched.add(fs);
+ continue;
+ }
+
+ Option<List<ConsistentHashingNode>> nodes =
identifier.splitBucket(fs.getFileId());
+
+ // Bucket cannot be split
+ if (!nodes.isPresent()) {
+ fsUntouched.add(fs);
+ continue;
+ }
+
+ remainingSplitSlot--;
+ List<FileSlice> fsList = Collections.singletonList(fs);
+ retGroup.add(HoodieClusteringGroup.newBuilder()
+ .setSlices(getFileSliceInfo(fsList))
+ .setNumOutputFileGroups(2)
+ .setMetrics(buildMetrics(fsList))
+ .setExtraMetadata(constructExtraMetadata(fs.getPartitionPath(),
nodes.get(), identifier.getMetadata().getSeqNo()))
+ .build());
+ }
+ return Triple.of(retGroup, splitSlot - remainingSplitSlot, fsUntouched);
+ }
+
+ /**
+ * Generate clustering group according to merge rules
+ *
+ * @param identifier bucket identifier
+ * @param fileSlices file slice candidates to be built as merge clustering
groups
+ * @param mergeSlot number of bucket allowed to be merged, in order to
guarantee the lower bound of the total number of bucket
+ * @return list of clustering group, number of buckets merged (removed),
remaining file slice (that does not be merged)
+ */
+ protected Triple<List<HoodieClusteringGroup>, Integer, List<FileSlice>>
buildMergeClusteringGroup(
+ ConsistentBucketIdentifier identifier, List<FileSlice> fileSlices, int
mergeSlot) {
+ if (fileSlices.size() <= 1) {
+ return Triple.of(Collections.emptyList(), 0, fileSlices);
+ }
+
+ long mergeSize = getMergeSize();
+ int remainingMergeSlot = mergeSlot;
+ List<HoodieClusteringGroup> groups = new ArrayList<>();
+ boolean[] added = new boolean[fileSlices.size()];
+
+ fileSlices.sort(Comparator.comparingInt(a ->
identifier.getBucketByFileId(a.getFileId()).getValue()));
+ // In each round, we check if the ith file slice can be merged with its
predecessors and successors
+ for (int i = 0; i < fileSlices.size(); ++i) {
+ if (added[i] || fileSlices.get(i).getTotalFileSize() > mergeSize) {
+ continue;
+ }
+
+ // 0: startIdx, 1: endIdx
+ int[] rangeIdx = {i, i};
+ long totalSize = fileSlices.get(i).getTotalFileSize();
+ // Do backward check first (k == 0), and then forward check (k == 1)
+ for (int k = 0; k < 2; ++k) {
+ boolean forward = k == 1;
+ do {
+ int nextIdx = forward ? (rangeIdx[k] + 1 < fileSlices.size() ?
rangeIdx[k] + 1 : 0) : (rangeIdx[k] >= 1 ? rangeIdx[k] - 1 : fileSlices.size()
- 1);
+ boolean isNeighbour =
identifier.getBucketByFileId(fileSlices.get(nextIdx).getFileId()) ==
identifier.getFormerBucket(fileSlices.get(rangeIdx[k]).getFileId());
+ /**
+ * Merge condition:
+ * 1. there is still slot to merge bucket
+ * 2. the previous file slices is not merged
+ * 3. the previous file slice and current file slice are neighbour
in the hash ring
+ * 4. Both the total file size up to now and the previous file slice
size are smaller than merge size threshold
+ */
+ if (remainingMergeSlot == 0 || added[nextIdx] || !isNeighbour ||
totalSize > mergeSize || fileSlices.get(nextIdx).getTotalFileSize() >
mergeSize) {
+ break;
+ }
+
+ // Mark preIdx as merge candidate
+ totalSize += fileSlices.get(nextIdx).getTotalFileSize();
+ rangeIdx[k] = nextIdx;
+ remainingMergeSlot--;
+ } while (rangeIdx[k] != i);
+ }
+
+ int startIdx = rangeIdx[0];
+ int endIdx = rangeIdx[1];
+ if (endIdx == i && startIdx == i) {
+ continue;
+ }
+
+ // Construct merge group if there is at least two file slices
+ List<FileSlice> fs = new ArrayList<>();
+ while (true) {
+ added[startIdx] = true;
+ fs.add(fileSlices.get(startIdx));
+ if (startIdx == endIdx) {
+ break;
+ }
+ startIdx = startIdx + 1 < fileSlices.size() ? startIdx + 1 : 0;
+ }
+
+ groups.add(HoodieClusteringGroup.newBuilder()
+ .setSlices(getFileSliceInfo(fs))
+ .setNumOutputFileGroups(1)
+ .setMetrics(buildMetrics(fs))
+ .setExtraMetadata(
+ constructExtraMetadata(
+ fs.get(0).getPartitionPath(),
+
identifier.mergeBucket(fs.stream().map(FileSlice::getFileId).collect(Collectors.toList())),
+ identifier.getMetadata().getSeqNo()))
+ .build());
+ }
+
+ // Collect file slices that are not involved in merge
+ List<FileSlice> fsUntouched = IntStream.range(0,
fileSlices.size()).filter(i -> !added[i])
+ .mapToObj(fileSlices::get).collect(Collectors.toList());
+
+ return Triple.of(groups, mergeSlot - remainingMergeSlot, fsUntouched);
+ }
+
+ /**
+ * Construct extra metadata for clustering group
+ */
+ private Map<String, String> constructExtraMetadata(String partition,
List<ConsistentHashingNode> nodes, int seqNo) {
+ Map<String, String> extraMetadata = new HashMap<>();
+ try {
+ extraMetadata.put(METADATA_PARTITION_KEY, partition);
+ extraMetadata.put(METADATA_CHILD_NODE_KEY,
ConsistentHashingNode.toJsonString(nodes));
+ extraMetadata.put(METADATA_SEQUENCE_NUMBER_KEY, Integer.toString(seqNo));
+ } catch (IOException e) {
+ LOG.error("Failed to construct extra metadata, partition: " + partition
+ ", nodes:" + nodes);
+ throw new HoodieClusteringException("Failed to construct extra metadata,
partition: " + partition + ", nodes:" + nodes);
+ }
+ return extraMetadata;
+ }
+
+ private long getSplitSize() {
+ HoodieFileFormat format =
getHoodieTable().getMetaClient().getTableConfig().getBaseFileFormat();
+ return (long) (getWriteConfig().getMaxFileSize(format) *
getWriteConfig().getBucketSplitThreshold());
+ }
+
+ private long getMergeSize() {
+ HoodieFileFormat format =
getHoodieTable().getMetaClient().getTableConfig().getBaseFileFormat();
Review Comment:
getSplitSize -> getSplitThresholdSize
getMergeSize -> getMergeThresholdSize
##########
hudi-client/hudi-client-common/src/main/java/org/apache/hudi/table/action/cluster/update/strategy/UpdateStrategy.java:
##########
@@ -50,4 +52,12 @@ public UpdateStrategy(HoodieEngineContext engineContext,
HoodieTable table, Set<
*/
public abstract Pair<I, Set<HoodieFileGroupId>> handleUpdate(I
taggedRecordsRDD);
+ /**
+ * Check the update records to the file group in clustering with given file
group id
+ * NOTE: used in flink engine
+ */
+ public Pair<I, List<HoodieFileGroupId>> handleUpdate(HoodieFileGroupId
fileId, I records) {
+ throw new UnsupportedOperationException("Unsupported");
Review Comment:
Can we avoid this, shouldn't the `records` already take the file group id ?
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