stream2000 commented on code in PR #9199:
URL: https://github.com/apache/hudi/pull/9199#discussion_r1283899831
##########
hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/table/action/commit/BucketBulkInsertDataInternalWriterHelper.java:
##########
@@ -65,7 +71,6 @@ public void write(InternalRow row) throws IOException {
int bucketId = BucketIdentifier.getBucketId(String.valueOf(recordKey),
indexKeyFields, bucketNum);
Pair<UTF8String, Integer> fileId = Pair.of(partitionPath, bucketId);
if (lastFileId == null || !lastFileId.equals(fileId)) {
- LOG.info("Creating new file for partition path " + partitionPath);
Review Comment:
We will not always create a new file handle if we have already created one
for this partition so I delete this line. I will add it back to
`getBucketRowCreateHandle` when we do need to create a new handle.
##########
hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/client/clustering/run/strategy/SparkConsistentBucketClusteringExecutionStrategy.java:
##########
@@ -79,15 +94,19 @@ public HoodieData<WriteStatus>
performClusteringWithRecordsRDD(HoodieData<Hoodie
HoodieWriteConfig newConfig =
HoodieWriteConfig.newBuilder().withProps(props).build();
RDDConsistentBucketBulkInsertPartitioner<T> partitioner = new
RDDConsistentBucketBulkInsertPartitioner<>(getHoodieTable(), strategyParams,
preserveHoodieMetadata);
+ addHashingChildNodes(partitioner, extraMetadata);
+
+ return (HoodieData<WriteStatus>) SparkBulkInsertHelper.newInstance()
+ .bulkInsert(inputRecords, instantTime, getHoodieTable(), newConfig,
false, partitioner, true, numOutputGroups);
+ }
+
+ private void addHashingChildNodes(ConsistentHashingBucketInsertPartitioner
partitioner, Map<String, String> extraMetadata) {
try {
List<ConsistentHashingNode> nodes =
ConsistentHashingNode.fromJsonString(extraMetadata.get(BaseConsistentHashingBucketClusteringPlanStrategy.METADATA_CHILD_NODE_KEY));
Review Comment:
Will check the nodes is non-emtpy in `addHashingChildrenNodes`
##########
hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/execution/bulkinsert/ConsistentBucketIndexBulkInsertPartitionerWithRows.java:
##########
@@ -0,0 +1,154 @@
+/*
+ * 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.execution.bulkinsert;
+
+import org.apache.hudi.common.model.ConsistentHashingNode;
+import org.apache.hudi.common.model.HoodieConsistentHashingMetadata;
+import org.apache.hudi.common.model.HoodieTableType;
+import org.apache.hudi.common.util.Option;
+import org.apache.hudi.common.util.ValidationUtils;
+import org.apache.hudi.index.bucket.ConsistentBucketIdentifier;
+import org.apache.hudi.index.bucket.ConsistentBucketIndexUtils;
+import org.apache.hudi.index.bucket.HoodieSparkConsistentBucketIndex;
+import org.apache.hudi.keygen.BuiltinKeyGenerator;
+import org.apache.hudi.keygen.factory.HoodieSparkKeyGeneratorFactory;
+import org.apache.hudi.table.BulkInsertPartitioner;
+import org.apache.hudi.table.ConsistentHashingBucketInsertPartitioner;
+import org.apache.hudi.table.HoodieTable;
+
+import org.apache.spark.Partitioner;
+import org.apache.spark.api.java.JavaRDD;
+import org.apache.spark.sql.Dataset;
+import org.apache.spark.sql.Row;
+
+import java.util.ArrayList;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+import java.util.stream.Collectors;
+
+import scala.Tuple2;
+
+/**
+ * Bulk_insert partitioner of Spark row using consistent hashing bucket index.
+ */
+public class ConsistentBucketIndexBulkInsertPartitionerWithRows
+ implements BulkInsertPartitioner<Dataset<Row>>,
ConsistentHashingBucketInsertPartitioner {
+
+ private final HoodieTable table;
+
+ private final String indexKeyFields;
+
+ private final List<String> fileIdPfxList = new ArrayList<>();
+ private final Map<String, List<ConsistentHashingNode>> hashingChildrenNodes;
+
+ private Map<String, ConsistentBucketIdentifier> partitionToIdentifier;
+
+ private final Option<BuiltinKeyGenerator> keyGeneratorOpt;
+
+ private Map<String, Map<String, Integer>> partitionToFileIdPfxIdxMap;
+
+ private final RowRecordKeyExtractor extractor;
+
+ public ConsistentBucketIndexBulkInsertPartitionerWithRows(HoodieTable table,
boolean populateMetaFields) {
+ this.indexKeyFields = table.getConfig().getBucketIndexHashField();
+ this.table = table;
+ this.hashingChildrenNodes = new HashMap<>();
+ if (!populateMetaFields) {
+ this.keyGeneratorOpt =
HoodieSparkKeyGeneratorFactory.getKeyGenerator(table.getConfig().getProps());
+ } else {
+ this.keyGeneratorOpt = Option.empty();
+ }
+ this.extractor =
RowRecordKeyExtractor.getRowRecordKeyExtractor(populateMetaFields,
keyGeneratorOpt);
+
ValidationUtils.checkArgument(table.getMetaClient().getTableType().equals(HoodieTableType.MERGE_ON_READ),
+ "Consistent hash bucket index doesn't support CoW table");
+ }
+
+ private ConsistentBucketIdentifier getBucketIdentifier(String partition) {
+ HoodieSparkConsistentBucketIndex index =
(HoodieSparkConsistentBucketIndex) table.getIndex();
+ HoodieConsistentHashingMetadata metadata =
ConsistentBucketIndexUtils.loadOrCreateMetadata(this.table, partition,
index.getNumBuckets());
+ if (hashingChildrenNodes.containsKey(partition)) {
+ metadata.setChildrenNodes(hashingChildrenNodes.get(partition));
+ }
+ return new ConsistentBucketIdentifier(metadata);
+ }
+
+ @Override
+ public Dataset<Row> repartitionRecords(Dataset<Row> rows, int
outputPartitions) {
+ JavaRDD<Row> rowJavaRDD = rows.toJavaRDD();
+ prepareRepartition(rowJavaRDD);
+ Partitioner partitioner = new Partitioner() {
+ @Override
+ public int getPartition(Object key) {
+ return (int) key;
+ }
+
+ @Override
+ public int numPartitions() {
+ return fileIdPfxList.size();
+ }
+ };
+
+ return rows.sparkSession().createDataFrame(rowJavaRDD
+ .mapToPair(row -> new Tuple2<>(getBucketId(row), row))
+ .partitionBy(partitioner)
+ .values(), rows.schema());
+ }
+
+ /**
+ * Prepare consistent hashing metadata for repartition
+ *
+ * @param rows input records
+ */
+ private void prepareRepartition(JavaRDD<Row> rows) {
+ this.partitionToIdentifier = initializeBucketIdentifier(rows);
+ this.partitionToFileIdPfxIdxMap =
ConsistentBucketIndexUtils.generatePartitionToFileIdPfxIdxMap(partitionToIdentifier);
+ partitionToIdentifier.values().forEach(identifier -> {
+
fileIdPfxList.addAll(identifier.getNodes().stream().map(ConsistentHashingNode::getFileIdPrefix).collect(Collectors.toList()));
+ });
+ }
+
+ /**
+ * Initialize hashing metadata of input records. The metadata of all related
partitions will be loaded, and
+ * the mapping from partition to its bucket identifier is constructed.
+ */
+ private Map<String, ConsistentBucketIdentifier>
initializeBucketIdentifier(JavaRDD<Row> rows) {
+ return
rows.map(this.extractor::getPartitionPath).distinct().collect().stream()
+ .collect(Collectors.toMap(p -> p, this::getBucketIdentifier));
+ }
+
+ @Override
+ public void addHashingChildrenNodes(String partition,
List<ConsistentHashingNode> nodes) {
+ ValidationUtils.checkState(nodes.stream().noneMatch(n -> n.getTag() ==
ConsistentHashingNode.NodeTag.NORMAL),
Review Comment:
`Normal` nodes are read from metadata in file system, while `REPLACE` and
`DELETE` nodes are read from consistent hashing resizing plan. Here we are
adding nodes read from clustering plan to the hash metadata so all nodes must
not be `NORMAL`
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