alexeykudinkin commented on code in PR #5328:
URL: https://github.com/apache/hudi/pull/5328#discussion_r928092517
##########
hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/execution/bulkinsert/BulkInsertInternalPartitionerFactory.java:
##########
@@ -27,16 +28,18 @@
*/
public abstract class BulkInsertInternalPartitionerFactory {
- public static BulkInsertPartitioner get(BulkInsertSortMode sortMode) {
- switch (sortMode) {
+ public static BulkInsertPartitioner get(BulkInsertSortMode bulkInsertMode,
HoodieTableConfig tableConfig) {
Review Comment:
There are modes which have nothing to do with sorting (re-partitioning, for
ex), so long-term we should strip the sort part of it
##########
hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/execution/bulkinsert/RepartitioningBulkInsertPartitionerBase.java:
##########
@@ -0,0 +1,62 @@
+/*
+ * 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.function.SerializableFunctionUnchecked;
+import org.apache.hudi.common.table.HoodieTableConfig;
+import org.apache.hudi.table.BulkInsertPartitioner;
+import org.apache.spark.Partitioner;
+
+import java.io.Serializable;
+import java.util.Objects;
+
+/**
+ * Base class for any {@link BulkInsertPartitioner} implementation that does
re-partitioning,
+ * to better align "logical" (query-engine's partitioning of the incoming
dataset) w/ the table's
+ * "physical" partitioning
+ */
+public abstract class RepartitioningBulkInsertPartitionerBase<I> implements
BulkInsertPartitioner<I> {
+
+ protected final boolean isPartitionedTable;
+
+ public RepartitioningBulkInsertPartitionerBase(HoodieTableConfig
tableConfig) {
Review Comment:
Good call. I thought about it initially, but then decided that it's better
to abstract this handling w/in the partitioner rather than pushing it onto the
caller. LMK what you think.
##########
hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/execution/bulkinsert/RepartitioningBulkInsertPartitionerBase.java:
##########
@@ -0,0 +1,62 @@
+/*
+ * 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.function.SerializableFunctionUnchecked;
+import org.apache.hudi.common.table.HoodieTableConfig;
+import org.apache.hudi.table.BulkInsertPartitioner;
+import org.apache.spark.Partitioner;
+
+import java.io.Serializable;
+import java.util.Objects;
+
+/**
+ * Base class for any {@link BulkInsertPartitioner} implementation that does
re-partitioning,
+ * to better align "logical" (query-engine's partitioning of the incoming
dataset) w/ the table's
+ * "physical" partitioning
+ */
+public abstract class RepartitioningBulkInsertPartitionerBase<I> implements
BulkInsertPartitioner<I> {
+
+ protected final boolean isPartitionedTable;
+
+ public RepartitioningBulkInsertPartitionerBase(HoodieTableConfig
tableConfig) {
+ this.isPartitionedTable = tableConfig.getPartitionFields().map(pfs ->
pfs.length > 0).orElse(false);
+ }
+
+ protected static class PartitionPathRDDPartitioner extends Partitioner
implements Serializable {
+ private final SerializableFunctionUnchecked<Object, String>
partitionPathExtractor;
+ private final int numPartitions;
+
+ PartitionPathRDDPartitioner(SerializableFunctionUnchecked<Object, String>
partitionPathExtractor, int numPartitions) {
+ this.partitionPathExtractor = partitionPathExtractor;
+ this.numPartitions = numPartitions;
+ }
+
+ @Override
+ public int numPartitions() {
+ return numPartitions;
+ }
+
+ @SuppressWarnings("unchecked")
+ @Override
+ public int getPartition(Object o) {
+ return Math.abs(Objects.hash(partitionPathExtractor.apply(o))) %
numPartitions;
Review Comment:
Not sure i follow your train of thought: that's the whole idea of such
partitioners (parittion-sort and partitioner-no-sort) to be able to partition
the data to be better aligned with physical partitioning, right?
In case data is heavily skewed into most recent partition, it shouldn't be
handled with this partitioner.
##########
hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/execution/bulkinsert/RowCustomColumnsSortPartitioner.java:
##########
@@ -19,42 +19,69 @@
package org.apache.hudi.execution.bulkinsert;
import org.apache.hudi.common.model.HoodieRecord;
+import org.apache.hudi.common.table.HoodieTableConfig;
import org.apache.hudi.config.HoodieWriteConfig;
-import org.apache.hudi.table.BulkInsertPartitioner;
+import org.apache.spark.sql.Column;
import org.apache.spark.sql.Dataset;
import org.apache.spark.sql.Row;
+import scala.collection.JavaConverters;
import java.util.Arrays;
+import java.util.stream.Collectors;
+
+import static org.apache.hudi.common.util.ValidationUtils.checkState;
+import static
org.apache.hudi.execution.bulkinsert.RDDCustomColumnsSortPartitioner.getOrderByColumnNames;
/**
- * A partitioner that does sorting based on specified column values for each
spark partitions.
+ * A partitioner that does local sorting for each RDD partition based on the
tuple of
+ * values of the columns configured for ordering.
*/
-public class RowCustomColumnsSortPartitioner implements
BulkInsertPartitioner<Dataset<Row>> {
+public class RowCustomColumnsSortPartitioner extends
RepartitioningBulkInsertPartitionerBase<Dataset<Row>> {
+
+ private final String[] orderByColumnNames;
- private final String[] sortColumnNames;
+ public RowCustomColumnsSortPartitioner(HoodieWriteConfig config,
HoodieTableConfig tableConfig) {
+ super(tableConfig);
+ this.orderByColumnNames = getOrderByColumnNames(config);
- public RowCustomColumnsSortPartitioner(HoodieWriteConfig config) {
- this.sortColumnNames = getSortColumnName(config);
+ checkState(orderByColumnNames.length > 0);
}
- public RowCustomColumnsSortPartitioner(String[] columnNames) {
- this.sortColumnNames = columnNames;
+ public RowCustomColumnsSortPartitioner(String[] columnNames,
HoodieTableConfig tableConfig) {
+ super(tableConfig);
+ this.orderByColumnNames = columnNames;
+
+ checkState(orderByColumnNames.length > 0);
}
@Override
- public Dataset<Row> repartitionRecords(Dataset<Row> records, int
outputSparkPartitions) {
- final String[] sortColumns = this.sortColumnNames;
- return records.coalesce(outputSparkPartitions)
- .sortWithinPartitions(HoodieRecord.PARTITION_PATH_METADATA_FIELD,
sortColumns);
+ public Dataset<Row> repartitionRecords(Dataset<Row> dataset, int
outputSparkPartitions) {
+ Dataset<Row> repartitionedDataset;
+
+ // NOTE: In case of partitioned table even "global" ordering (across all
RDD partitions) could
+ // not change table's partitioning and therefore there's no point in
doing global sorting
+ // across "physical" partitions, and instead we can reduce total
amount of data being
+ // shuffled by doing do "local" sorting:
+ // - First, re-partitioning dataset such that "logical"
partitions are aligned w/
+ // "physical" ones
+ // - Sorting locally w/in RDD ("logical") partitions
+ //
+ // Non-partitioned tables will be globally sorted.
+ if (isPartitionedTable) {
+ repartitionedDataset = dataset.repartition(outputSparkPartitions, new
Column(HoodieRecord.PARTITION_PATH_METADATA_FIELD));
Review Comment:
It will if the dataset wasn't partitioned before, but it brings the benefits
of the properly sized files (b/c whole physical partition will be written by a
single executor)
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