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[HUDI-4320] Make sure HoodieStorageConfig.PARQUET_WRITE_LEGACY_FORMAT_ENABLED could be specified by the writer (#5970)

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Fixed sequence determining whether Parquet's legacy-format writing property should be overridden to only kick in when it has not been explicitly specified by the caller
This commit is contained in:
Alexey Kudinkin
2022-06-28 12:27:32 -07:00
committed by GitHub
parent efb9719018
commit ed823f1c6f
5 changed files with 89 additions and 54 deletions
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15
hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/util/DataTypeUtils.java
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@@ -126,24 +126,23 @@ public class DataTypeUtils {
}
/**
* Try to find current sparktype whether contains that DecimalType which's scale < Decimal.MAX_LONG_DIGITS().
*
* @param sparkType spark schema.
* @return found result.
* Checks whether provided {@link DataType} contains {@link DecimalType} whose scale is less than
* {@link Decimal#MAX_LONG_DIGITS()}
*/
public static boolean foundSmallPrecisionDecimalType(DataType sparkType) {
public static boolean hasSmallPrecisionDecimalType(DataType sparkType) {
if (sparkType instanceof StructType) {
StructField[] fields = ((StructType) sparkType).fields();
return Arrays.stream(fields).anyMatch(f -> foundSmallPrecisionDecimalType(f.dataType()));
return Arrays.stream(fields).anyMatch(f -> hasSmallPrecisionDecimalType(f.dataType()));
} else if (sparkType instanceof MapType) {
MapType map = (MapType) sparkType;
return foundSmallPrecisionDecimalType(map.keyType()) || foundSmallPrecisionDecimalType(map.valueType());
return hasSmallPrecisionDecimalType(map.keyType()) || hasSmallPrecisionDecimalType(map.valueType());
} else if (sparkType instanceof ArrayType) {
return foundSmallPrecisionDecimalType(((ArrayType) sparkType).elementType());
return hasSmallPrecisionDecimalType(((ArrayType) sparkType).elementType());
} else if (sparkType instanceof DecimalType) {
DecimalType decimalType = (DecimalType) sparkType;
return decimalType.precision() < Decimal.MAX_LONG_DIGITS();
}
return false;
}
}

46
hudi-spark-datasource/hudi-spark-common/src/main/java/org/apache/hudi/DataSourceUtils.java
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@@ -18,6 +18,9 @@
package org.apache.hudi;
import org.apache.avro.generic.GenericRecord;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hudi.client.HoodieReadClient;
import org.apache.hudi.client.HoodieWriteResult;
import org.apache.hudi.client.SparkRDDWriteClient;
@@ -45,10 +48,6 @@ import org.apache.hudi.hive.SlashEncodedDayPartitionValueExtractor;
import org.apache.hudi.sync.common.HoodieSyncConfig;
import org.apache.hudi.table.BulkInsertPartitioner;
import org.apache.hudi.util.DataTypeUtils;
import org.apache.avro.generic.GenericRecord;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.log4j.LogManager;
import org.apache.log4j.Logger;
import org.apache.spark.api.java.JavaRDD;
@@ -327,14 +326,39 @@ public class DataSourceUtils {
return hiveSyncConfig;
}
// Now by default ParquetWriteSupport will write DecimalType to parquet as int32/int64 when the scale of decimalType < Decimal.MAX_LONG_DIGITS(),
// but AvroParquetReader which used by HoodieParquetReader cannot support read int32/int64 as DecimalType.
// try to find current schema whether contains that DecimalType, and auto set the value of "hoodie.parquet.writelegacyformat.enabled"
public static void mayBeOverwriteParquetWriteLegacyFormatProp(Map<String, String> properties, StructType schema) {
if (DataTypeUtils.foundSmallPrecisionDecimalType(schema)
&& !Boolean.parseBoolean(properties.getOrDefault(HoodieStorageConfig.PARQUET_WRITE_LEGACY_FORMAT_ENABLED.key(), "false"))) {
/**
* Checks whether default value (false) of "hoodie.parquet.writelegacyformat.enabled" should be
* overridden in case:
*
* <ul>
* <li>Property has not been explicitly set by the writer</li>
* <li>Data schema contains {@code DecimalType} that would be affected by it</li>
* </ul>
*
* If both of the aforementioned conditions are true, will override the default value of the config
* (by essentially setting the value) to make sure that the produced Parquet data files could be
* read by {@code AvroParquetReader}
*
* @param properties properties specified by the writer
* @param schema schema of the dataset being written
*/
public static void tryOverrideParquetWriteLegacyFormatProperty(Map<String, String> properties, StructType schema) {
if (DataTypeUtils.hasSmallPrecisionDecimalType(schema)
&& properties.get(HoodieStorageConfig.PARQUET_WRITE_LEGACY_FORMAT_ENABLED.key()) == null) {
// ParquetWriteSupport writes DecimalType to parquet as INT32/INT64 when the scale of decimalType
// is less than {@code Decimal.MAX_LONG_DIGITS}, but {@code AvroParquetReader} which is used by
// {@code HoodieParquetReader} does not support DecimalType encoded as INT32/INT64 as.
//
// To work this problem around we're checking whether
// - Schema contains any decimals that could be encoded as INT32/INT64
// - {@code HoodieStorageConfig.PARQUET_WRITE_LEGACY_FORMAT_ENABLED} has not been explicitly
// set by the writer
//
// If both of these conditions are true, than we override the default value of {@code
// HoodieStorageConfig.PARQUET_WRITE_LEGACY_FORMAT_ENABLED} and set it to "true"
LOG.warn("Small Decimal Type found in the persisted schema, reverting default value of 'hoodie.parquet.writelegacyformat.enabled' to true");
properties.put(HoodieStorageConfig.PARQUET_WRITE_LEGACY_FORMAT_ENABLED.key(), "true");
LOG.warn("Small Decimal Type found in current schema, auto set the value of hoodie.parquet.writelegacyformat.enabled to true");
}
}
}

74
hudi-spark-datasource/hudi-spark/src/test/java/org/apache/hudi/TestDataSourceUtils.java
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@@ -18,6 +18,12 @@
package org.apache.hudi;
import org.apache.avro.Conversions;
import org.apache.avro.LogicalTypes;
import org.apache.avro.Schema;
import org.apache.avro.generic.GenericData;
import org.apache.avro.generic.GenericFixed;
import org.apache.avro.generic.GenericRecord;
import org.apache.hudi.avro.HoodieAvroUtils;
import org.apache.hudi.client.SparkRDDWriteClient;
import org.apache.hudi.common.config.TypedProperties;
@@ -27,21 +33,16 @@ import org.apache.hudi.common.model.WriteOperationType;
import org.apache.hudi.common.util.Option;
import org.apache.hudi.common.util.collection.ImmutablePair;
import org.apache.hudi.config.HoodieClusteringConfig;
import org.apache.hudi.config.HoodieStorageConfig;
import org.apache.hudi.config.HoodieWriteConfig;
import org.apache.hudi.exception.HoodieException;
import org.apache.hudi.execution.bulkinsert.RDDCustomColumnsSortPartitioner;
import org.apache.hudi.hive.HiveSyncConfig;
import org.apache.hudi.table.BulkInsertPartitioner;
import org.apache.avro.Conversions;
import org.apache.avro.LogicalTypes;
import org.apache.avro.Schema;
import org.apache.avro.generic.GenericData;
import org.apache.avro.generic.GenericFixed;
import org.apache.avro.generic.GenericRecord;
import org.apache.spark.api.java.JavaRDD;
import org.apache.spark.sql.Dataset;
import org.apache.spark.sql.Row;
import org.apache.spark.sql.types.DecimalType;
import org.apache.spark.sql.types.DecimalType$;
import org.apache.spark.sql.types.Metadata;
import org.apache.spark.sql.types.StructField;
@@ -51,7 +52,8 @@ import org.junit.jupiter.api.BeforeEach;
import org.junit.jupiter.api.Test;
import org.junit.jupiter.api.extension.ExtendWith;
import org.junit.jupiter.params.ParameterizedTest;
import org.junit.jupiter.params.provider.CsvSource;
import org.junit.jupiter.params.provider.Arguments;
import org.junit.jupiter.params.provider.MethodSource;
import org.junit.jupiter.params.provider.ValueSource;
import org.mockito.ArgumentCaptor;
import org.mockito.Captor;
@@ -61,11 +63,13 @@ import org.mockito.junit.jupiter.MockitoExtension;
import java.math.BigDecimal;
import java.time.LocalDate;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.Collections;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.stream.Stream;
import static org.apache.hudi.DataSourceUtils.mayBeOverwriteParquetWriteLegacyFormatProp;
import static org.apache.hudi.DataSourceUtils.tryOverrideParquetWriteLegacyFormatProperty;
import static org.apache.hudi.common.model.HoodieFileFormat.PARQUET;
import static org.apache.hudi.hive.ddl.HiveSyncMode.HMS;
import static org.hamcrest.CoreMatchers.containsString;
@@ -313,31 +317,39 @@ public class TestDataSourceUtils {
}
@ParameterizedTest
@CsvSource({"true, false", "true, true", "false, true", "false, false"})
public void testAutoModifyParquetWriteLegacyFormatParameter(boolean smallDecimal, boolean defaultWriteValue) {
// create test StructType
List<StructField> structFields = new ArrayList<>();
@MethodSource("testAutoModifyParquetWriteLegacyFormatParameterParams")
public void testAutoModifyParquetWriteLegacyFormatParameter(boolean smallDecimal, Boolean propValue, Boolean expectedPropValue) {
DecimalType decimalType;
if (smallDecimal) {
structFields.add(StructField.apply("d1", DecimalType$.MODULE$.apply(10, 2), false, Metadata.empty()));
decimalType = DecimalType$.MODULE$.apply(10, 2);
} else {
structFields.add(StructField.apply("d1", DecimalType$.MODULE$.apply(38, 10), false, Metadata.empty()));
decimalType = DecimalType$.MODULE$.apply(38, 10);
}
StructType structType = StructType$.MODULE$.apply(structFields);
// create write options
Map<String, String> options = new HashMap<>();
options.put("hoodie.parquet.writelegacyformat.enabled", String.valueOf(defaultWriteValue));
// start test
mayBeOverwriteParquetWriteLegacyFormatProp(options, structType);
StructType structType = StructType$.MODULE$.apply(
Arrays.asList(
StructField.apply("d1", decimalType, false, Metadata.empty())
)
);
// check result
boolean res = Boolean.parseBoolean(options.get("hoodie.parquet.writelegacyformat.enabled"));
if (smallDecimal) {
// should auto modify "hoodie.parquet.writelegacyformat.enabled" = "true".
assertEquals(true, res);
} else {
// should not modify the value of "hoodie.parquet.writelegacyformat.enabled".
assertEquals(defaultWriteValue, res);
}
Map<String, String> options = propValue != null
? Collections.singletonMap(HoodieStorageConfig.PARQUET_WRITE_LEGACY_FORMAT_ENABLED.key(), String.valueOf(propValue))
: new HashMap<>();
tryOverrideParquetWriteLegacyFormatProperty(options, structType);
Boolean finalPropValue =
Option.ofNullable(options.get(HoodieStorageConfig.PARQUET_WRITE_LEGACY_FORMAT_ENABLED.key()))
.map(Boolean::parseBoolean)
.orElse(null);
assertEquals(expectedPropValue, finalPropValue);
}
private static Stream<Arguments> testAutoModifyParquetWriteLegacyFormatParameterParams() {
return Arrays.stream(new Object[][] {
{true, null, true}, {false, null, null},
{true, false, false}, {true, true, true},
{false, true, true}, {false, false, false}
}).map(Arguments::of);
}
}

4
hudi-spark-datasource/hudi-spark2/src/main/java/org/apache/hudi/internal/DefaultSource.java
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@@ -36,7 +36,7 @@ import org.apache.spark.sql.types.StructType;
import java.util.Map;
import java.util.Optional;
import static org.apache.hudi.DataSourceUtils.mayBeOverwriteParquetWriteLegacyFormatProp;
import static org.apache.hudi.DataSourceUtils.tryOverrideParquetWriteLegacyFormatProperty;
/**
* DataSource V2 implementation for managing internal write logic. Only called internally.
@@ -69,7 +69,7 @@ public class DefaultSource extends BaseDefaultSource implements DataSourceV2,
HoodieTableConfig.POPULATE_META_FIELDS.defaultValue());
Map<String, String> properties = options.asMap();
// Auto set the value of "hoodie.parquet.writelegacyformat.enabled"
mayBeOverwriteParquetWriteLegacyFormatProp(properties, schema);
tryOverrideParquetWriteLegacyFormatProperty(properties, schema);
// 1st arg to createHoodieConfig is not really required to be set. but passing it anyways.
HoodieWriteConfig config = DataSourceUtils.createHoodieConfig(options.get(HoodieWriteConfig.AVRO_SCHEMA_STRING.key()).get(), path, tblName, properties);
boolean arePartitionRecordsSorted = HoodieInternalConfig.getBulkInsertIsPartitionRecordsSorted(

4
hudi-spark-datasource/hudi-spark3-common/src/main/java/org/apache/hudi/spark3/internal/DefaultSource.java
View File

@@ -34,7 +34,7 @@ import org.apache.spark.sql.util.CaseInsensitiveStringMap;
import java.util.HashMap;
import java.util.Map;
import static org.apache.hudi.DataSourceUtils.mayBeOverwriteParquetWriteLegacyFormatProp;
import static org.apache.hudi.DataSourceUtils.tryOverrideParquetWriteLegacyFormatProperty;
/**
* DataSource V2 implementation for managing internal write logic. Only called internally.
@@ -59,7 +59,7 @@ public class DefaultSource extends BaseDefaultSource implements TableProvider {
// Create a new map as the properties is an unmodifiableMap on Spark 3.2.0
Map<String, String> newProps = new HashMap<>(properties);
// Auto set the value of "hoodie.parquet.writelegacyformat.enabled"
mayBeOverwriteParquetWriteLegacyFormatProp(newProps, schema);
tryOverrideParquetWriteLegacyFormatProperty(newProps, schema);
// 1st arg to createHoodieConfig is not really required to be set. but passing it anyways.
HoodieWriteConfig config = DataSourceUtils.createHoodieConfig(newProps.get(HoodieWriteConfig.AVRO_SCHEMA_STRING.key()), path, tblName, newProps);
return new HoodieDataSourceInternalTable(instantTime, config, schema, getSparkSession(),