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[HUDI-7040] Handle dropping of partition columns in BulkInsertDataInt…
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…ernalWriterHelper::write(...) (apache#10272)

Issue:
There are two configs which when set in a certain manner throws exceptions or asserts
1. Configs to disable populating metadata fields (for each row)
2. Configs to drop partition columns (to save storage space) from a row

With #1 and #2, partition paths cannot be deduced using partition columns (as the partition columns are dropped higher up the stack.
BulkInsertDataInternalWriterHelper::write(...) relied on metadata fields to extract partition path in such cases.
But with #1 it is not possible resulting in asserts/exceptions.

The fix is to push down the dropping of partition columns down the stack after partition path is computed.
The fix manipulates the raw 'InternalRow' row structure by only copying the relevent fields into a new 'InternalRow' structure.
Each row is processed individually to drop the partition columns and copy it a to new 'InternalRow'

Co-authored-by: Vinaykumar Bhat <[email protected]>
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@bhat-vinay @nsivabalan
2 people authored and nsivabalan committed Dec 18, 2023
1 parent 75d0623 commit 7909037
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Showing 6 changed files with 101 additions and 31 deletions.
4 changes: 4 additions & 0 deletions hudi-client/hudi-client-common/src/main/java/org/apache/hudi/config/HoodieWriteConfig.java
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Expand Up @@ -1345,6 +1345,10 @@ public boolean shouldAllowMultiWriteOnSameInstant() {
return getBoolean(ALLOW_MULTI_WRITE_ON_SAME_INSTANT_ENABLE);
}

public boolean shouldDropPartitionColumns() {
return getBoolean(HoodieTableConfig.DROP_PARTITION_COLUMNS);
}

public String getWriteStatusClassName() {
return getString(WRITE_STATUS_CLASS_NAME);
}
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34 changes: 33 additions & 1 deletion ...src/main/java/org/apache/hudi/table/action/commit/BulkInsertDataInternalWriterHelper.java
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Expand Up @@ -18,6 +18,7 @@

package org.apache.hudi.table.action.commit;

import org.apache.hudi.HoodieDatasetBulkInsertHelper;
import org.apache.hudi.client.WriteStatus;
import org.apache.hudi.common.model.HoodieRecord;
import org.apache.hudi.common.util.Option;
Expand All @@ -38,11 +39,16 @@
import java.io.IOException;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.HashSet;
import java.util.List;
import java.util.Map;
import java.util.Objects;
import java.util.Set;
import java.util.UUID;

import scala.collection.JavaConversions;
import scala.collection.JavaConverters;

/**
* Helper class for HoodieBulkInsertDataInternalWriter used by Spark datasource v2.
*/
Expand Down Expand Up @@ -124,7 +130,33 @@ public void write(InternalRow row) throws IOException {
lastKnownPartitionPath = partitionPath.clone();
}

handle.write(row);
boolean shouldDropPartitionColumns = writeConfig.shouldDropPartitionColumns();
if (shouldDropPartitionColumns) {
// Drop the partition columns from the row
// Using the deprecated JavaConversions to be compatible with scala versions < 2.12. Once hudi support for scala versions < 2.12 is
// stopped, can move this to JavaConverters.seqAsJavaList(...)
List<String> partitionCols = JavaConversions.<String>seqAsJavaList(HoodieDatasetBulkInsertHelper.getPartitionPathCols(this.writeConfig));
Set<Integer> partitionIdx = new HashSet<Integer>();
for (String col : partitionCols) {
partitionIdx.add(this.structType.fieldIndex(col));
}

// Relies on InternalRow::toSeq(...) preserving the column ordering based on the supplied schema
// Using the deprecated JavaConversions to be compatible with scala versions < 2.12.
List<Object> cols = JavaConversions.<Object>seqAsJavaList(row.toSeq(structType));
int idx = 0;
List<Object> newCols = new ArrayList<Object>();
for (Object o : cols) {
if (!partitionIdx.contains(idx)) {
newCols.add(o);
}
idx += 1;
}
InternalRow newRow = InternalRow.fromSeq(JavaConverters.<Object>asScalaIteratorConverter(newCols.iterator()).asScala().toSeq());
handle.write(newRow);
} else {
handle.write(row);
}
} catch (Throwable t) {
LOG.error("Global error thrown while trying to write records in HoodieRowCreateHandle ", t);
throw t;
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31 changes: 10 additions & 21 deletions ...ient/hudi-spark-client/src/main/scala/org/apache/hudi/HoodieDatasetBulkInsertHelper.scala
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Expand Up @@ -62,7 +62,6 @@ object HoodieDatasetBulkInsertHelper
def prepareForBulkInsert(df: DataFrame,
config: HoodieWriteConfig,
partitioner: BulkInsertPartitioner[Dataset[Row]],
shouldDropPartitionColumns: Boolean,
instantTime: String): Dataset[Row] = {
val populateMetaFields = config.populateMetaFields()
val schema = df.schema
Expand Down Expand Up @@ -128,16 +127,10 @@ object HoodieDatasetBulkInsertHelper
HoodieUnsafeUtils.createDataFrameFrom(df.sparkSession, prependedQuery)
}

val trimmedDF = if (shouldDropPartitionColumns) {
dropPartitionColumns(updatedDF, config)
} else {
updatedDF
}

val targetParallelism =
deduceShuffleParallelism(trimmedDF, config.getBulkInsertShuffleParallelism)
deduceShuffleParallelism(updatedDF, config.getBulkInsertShuffleParallelism)

partitioner.repartitionRecords(trimmedDF, targetParallelism)
partitioner.repartitionRecords(updatedDF, targetParallelism)
}

/**
Expand Down Expand Up @@ -243,21 +236,17 @@ object HoodieDatasetBulkInsertHelper
}
}

private def dropPartitionColumns(df: DataFrame, config: HoodieWriteConfig): DataFrame = {
val partitionPathFields = getPartitionPathFields(config).toSet
val nestedPartitionPathFields = partitionPathFields.filter(f => f.contains('.'))
if (nestedPartitionPathFields.nonEmpty) {
logWarning(s"Can not drop nested partition path fields: $nestedPartitionPathFields")
}

val partitionPathCols = (partitionPathFields -- nestedPartitionPathFields).toSeq

df.drop(partitionPathCols: _*)
}

private def getPartitionPathFields(config: HoodieWriteConfig): Seq[String] = {
val keyGeneratorClassName = config.getString(HoodieWriteConfig.KEYGENERATOR_CLASS_NAME)
val keyGenerator = ReflectionUtils.loadClass(keyGeneratorClassName, new TypedProperties(config.getProps)).asInstanceOf[BuiltinKeyGenerator]
keyGenerator.getPartitionPathFields.asScala
}

def getPartitionPathCols(config: HoodieWriteConfig): Seq[String] = {
val partitionPathFields = getPartitionPathFields(config).toSet
val nestedPartitionPathFields = partitionPathFields.filter(f => f.contains('.'))

return (partitionPathFields -- nestedPartitionPathFields).toSeq
}

}
3 changes: 1 addition & 2 deletions ...ommon/src/main/java/org/apache/hudi/commit/BaseDatasetBulkInsertCommitActionExecutor.java
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Expand Up @@ -95,8 +95,7 @@ public final HoodieWriteResult execute(Dataset<Row> records, boolean isTablePart
table = writeClient.initTable(getWriteOperationType(), Option.ofNullable(instantTime));

BulkInsertPartitioner<Dataset<Row>> bulkInsertPartitionerRows = getPartitioner(populateMetaFields, isTablePartitioned);
boolean shouldDropPartitionColumns = writeConfig.getBoolean(DataSourceWriteOptions.DROP_PARTITION_COLUMNS());
Dataset<Row> hoodieDF = HoodieDatasetBulkInsertHelper.prepareForBulkInsert(records, writeConfig, bulkInsertPartitionerRows, shouldDropPartitionColumns, instantTime);
Dataset<Row> hoodieDF = HoodieDatasetBulkInsertHelper.prepareForBulkInsert(records, writeConfig, bulkInsertPartitionerRows, instantTime);

preExecute();
HoodieWriteMetadata<JavaRDD<WriteStatus>> result = buildHoodieWriteMetadata(doExecute(hoodieDF, bulkInsertPartitionerRows.arePartitionRecordsSorted()));
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12 changes: 6 additions & 6 deletions ...udi-spark/src/test/java/org/apache/hudi/functional/TestHoodieDatasetBulkInsertHelper.java
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Expand Up @@ -131,7 +131,7 @@ private void testBulkInsertHelperFor(String keyGenClass, String recordKeyField)
List<Row> rows = DataSourceTestUtils.generateRandomRows(10);
Dataset<Row> dataset = sqlContext.createDataFrame(rows, structType);
Dataset<Row> result = HoodieDatasetBulkInsertHelper.prepareForBulkInsert(dataset, config,
new NonSortPartitionerWithRows(), false, "0000000001");
new NonSortPartitionerWithRows(), "0000000001");
StructType resultSchema = result.schema();

assertEquals(result.count(), 10);
Expand Down Expand Up @@ -175,7 +175,7 @@ public void testBulkInsertHelperNoMetaFields() {
.build();
Dataset<Row> dataset = sqlContext.createDataFrame(rows, structType);
Dataset<Row> result = HoodieDatasetBulkInsertHelper.prepareForBulkInsert(dataset, config,
new NonSortPartitionerWithRows(), false, "000001111");
new NonSortPartitionerWithRows(), "000001111");
StructType resultSchema = result.schema();

assertEquals(result.count(), 10);
Expand Down Expand Up @@ -212,7 +212,7 @@ public void testBulkInsertPreCombine(boolean enablePreCombine) {
rows.addAll(updates);
Dataset<Row> dataset = sqlContext.createDataFrame(rows, structType);
Dataset<Row> result = HoodieDatasetBulkInsertHelper.prepareForBulkInsert(dataset, config,
new NonSortPartitionerWithRows(), false, "000001111");
new NonSortPartitionerWithRows(), "000001111");
StructType resultSchema = result.schema();

assertEquals(result.count(), enablePreCombine ? 10 : 15);
Expand Down Expand Up @@ -316,7 +316,7 @@ public void testNoPropsSet() {
Dataset<Row> dataset = sqlContext.createDataFrame(rows, structType);
try {
Dataset<Row> preparedDF = HoodieDatasetBulkInsertHelper.prepareForBulkInsert(dataset, config,
new NonSortPartitionerWithRows(), false, "000001111");
new NonSortPartitionerWithRows(), "000001111");
preparedDF.count();
fail("Should have thrown exception");
} catch (Exception e) {
Expand All @@ -328,7 +328,7 @@ public void testNoPropsSet() {
dataset = sqlContext.createDataFrame(rows, structType);
try {
Dataset<Row> preparedDF = HoodieDatasetBulkInsertHelper.prepareForBulkInsert(dataset, config,
new NonSortPartitionerWithRows(), false, "000001111");
new NonSortPartitionerWithRows(), "000001111");
preparedDF.count();
fail("Should have thrown exception");
} catch (Exception e) {
Expand All @@ -340,7 +340,7 @@ public void testNoPropsSet() {
dataset = sqlContext.createDataFrame(rows, structType);
try {
Dataset<Row> preparedDF = HoodieDatasetBulkInsertHelper.prepareForBulkInsert(dataset, config,
new NonSortPartitionerWithRows(), false, "000001111");
new NonSortPartitionerWithRows(), "000001111");
preparedDF.count();
fail("Should have thrown exception");
} catch (Exception e) {
Expand Down
48 changes: 47 additions & 1 deletion ...spark-datasource/hudi-spark/src/test/scala/org/apache/hudi/TestHoodieSparkSqlWriter.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -39,7 +39,7 @@ import org.apache.spark.sql._
import org.apache.spark.sql.functions.{expr, lit}
import org.apache.spark.sql.hudi.HoodieSparkSessionExtension
import org.apache.spark.sql.hudi.command.SqlKeyGenerator
import org.junit.jupiter.api.Assertions.{assertEquals, assertFalse, assertTrue, fail}
import org.junit.jupiter.api.Assertions.{assertEquals, assertFalse, assertNotNull, assertNull, assertTrue, fail}
import org.junit.jupiter.api.{AfterEach, BeforeEach, Test}
import org.junit.jupiter.params.ParameterizedTest
import org.junit.jupiter.params.provider.Arguments.arguments
Expand Down Expand Up @@ -365,6 +365,52 @@ class TestHoodieSparkSqlWriter {
testBulkInsertWithSortMode(BulkInsertSortMode.NONE, populateMetaFields)
}

@Test
def testBulkInsertForDropPartitionColumn(): Unit = {
//create a new table
val tableName = "trips_table"
val basePath = "file:///tmp/trips_table"
val columns = Seq("ts", "uuid", "rider", "driver", "fare", "city")
val data =
Seq((1695159649087L, "334e26e9-8355-45cc-97c6-c31daf0df330", "rider-A", "driver-K", 19.10, "san_francisco"),
(1695091554788L, "e96c4396-3fad-413a-a942-4cb36106d721", "rider-C", "driver-M", 27.70, "san_francisco"),
(1695046462179L, "9909a8b1-2d15-4d3d-8ec9-efc48c536a00", "rider-D", "driver-L", 33.90, "san_francisco"),
(1695516137016L, "e3cf430c-889d-4015-bc98-59bdce1e530c", "rider-F", "driver-P", 34.15, "sao_paulo"),
(1695115999911L, "c8abbe79-8d89-47ea-b4ce-4d224bae5bfa", "rider-J", "driver-T", 17.85, "chennai"));

var inserts = spark.createDataFrame(data).toDF(columns: _*)
inserts.write.format("hudi").
option(DataSourceWriteOptions.PARTITIONPATH_FIELD.key(), "city").
option(HoodieWriteConfig.TABLE_NAME, tableName).
option("hoodie.datasource.write.recordkey.field", "uuid").
option("hoodie.datasource.write.precombine.field", "rider").
option("hoodie.datasource.write.operation", "bulk_insert").
option("hoodie.datasource.write.hive_style_partitioning", "true").
option("hoodie.populate.meta.fields", "false").
option("hoodie.datasource.write.drop.partition.columns", "true").
mode(SaveMode.Overwrite).
save(basePath)

// Ensure the partition column (i.e 'city') can be read back
val tripsDF = spark.read.format("hudi").load(basePath)
tripsDF.show()
tripsDF.select("city").foreach(row => {
assertNotNull(row)
})

// Peek into the raw parquet file and ensure partition column is not written to the file
val partitions = Seq("city=san_francisco", "city=chennai", "city=sao_paulo")
val partitionPaths = new Array[String](3)
for (i <- partitionPaths.indices) {
partitionPaths(i) = String.format("%s/%s/*", basePath, partitions(i))
}
val rawFileDf = spark.sqlContext.read.parquet(partitionPaths(0), partitionPaths(1), partitionPaths(2))
rawFileDf.show()
rawFileDf.select("city").foreach(row => {
assertNull(row.get(0))
})
}

/**
* Test case for disable and enable meta fields.
*/
Expand Down

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