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[HUDI-4453] Fix schema to include partition columns in bootstrap operation #6676

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merged 3 commits into from Sep 28, 2022
Merged

[HUDI-4453] Fix schema to include partition columns in bootstrap operation #6676

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30d7455
[HUDI-4453] Fix schema to include partition columns in bootstrap oper…
yihua Sep 15, 2022
b79e74d
Turn off the type inference of partition column to consistent with ex…
yihua Sep 27, 2022
edf92e5
Add notes around partition column type inference
yihua Sep 27, 2022
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33 changes: 13 additions & 20 deletions ...nt/src/main/java/org/apache/hudi/client/bootstrap/HoodieSparkBootstrapSchemaProvider.java
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Expand Up @@ -18,15 +18,14 @@

package org.apache.hudi.client.bootstrap;

import org.apache.hadoop.conf.Configuration;
import org.apache.hudi.AvroConversionUtils;
import org.apache.hudi.avro.HoodieAvroUtils;
import org.apache.hudi.avro.model.HoodieFileStatus;
import org.apache.hudi.client.common.HoodieSparkEngineContext;
import org.apache.hudi.common.bootstrap.FileStatusUtils;
import org.apache.hudi.common.engine.HoodieEngineContext;
import org.apache.hudi.common.fs.FSUtils;
import org.apache.hudi.common.util.AvroOrcUtils;
import org.apache.hudi.common.util.ParquetUtils;
import org.apache.hudi.common.util.collection.Pair;
import org.apache.hudi.config.HoodieWriteConfig;
import org.apache.hudi.exception.HoodieException;
Expand All @@ -36,8 +35,6 @@
import org.apache.orc.OrcFile;
import org.apache.orc.Reader;
import org.apache.orc.TypeDescription;
import org.apache.parquet.schema.MessageType;
import org.apache.spark.sql.execution.datasources.parquet.ParquetToSparkSchemaConverter;
import org.apache.spark.sql.internal.SQLConf;
import org.apache.spark.sql.types.StructType;

Expand Down Expand Up @@ -72,26 +69,22 @@ protected Schema getBootstrapSourceSchema(HoodieEngineContext context, List<Pair
}

private static Schema getBootstrapSourceSchemaParquet(HoodieWriteConfig writeConfig, HoodieEngineContext context, Path filePath) {
Configuration hadoopConf = context.getHadoopConf().get();
MessageType parquetSchema = new ParquetUtils().readSchema(hadoopConf, filePath);

hadoopConf.set(
SQLConf.PARQUET_BINARY_AS_STRING().key(),
SQLConf.PARQUET_BINARY_AS_STRING().defaultValueString());
hadoopConf.set(
SQLConf.PARQUET_INT96_AS_TIMESTAMP().key(),
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SQLConf.PARQUET_INT96_AS_TIMESTAMP().defaultValueString());
hadoopConf.set(
SQLConf.CASE_SENSITIVE().key(),
SQLConf.CASE_SENSITIVE().defaultValueString());
ParquetToSparkSchemaConverter converter = new ParquetToSparkSchemaConverter(hadoopConf);

StructType sparkSchema = converter.convert(parquetSchema);
// NOTE: The type inference of partition column in the parquet table is turned off explicitly,
// to be consistent with the existing bootstrap behavior, where the partition column is String
// typed in Hudi table.
// TODO(HUDI-4932): add a config to allow type inference of partition column in bootstrap and
// support other types of partition column as well
((HoodieSparkEngineContext) context).getSqlContext()
.setConf(SQLConf.PARTITION_COLUMN_TYPE_INFERENCE(), false);
StructType parquetSchema = ((HoodieSparkEngineContext) context).getSqlContext().read()
.option("basePath", writeConfig.getBootstrapSourceBasePath())
.parquet(filePath.toString())
.schema();
String tableName = HoodieAvroUtils.sanitizeName(writeConfig.getTableName());
String structName = tableName + "_record";
String recordNamespace = "hoodie." + tableName;

return AvroConversionUtils.convertStructTypeToAvroSchema(sparkSchema, structName, recordNamespace);
return AvroConversionUtils.convertStructTypeToAvroSchema(parquetSchema, structName, recordNamespace);
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}

private static Schema getBootstrapSourceSchemaOrc(HoodieWriteConfig writeConfig, HoodieEngineContext context, Path filePath) {
Expand Down
2 changes: 1 addition & 1 deletion ...datasource/hudi-spark-common/src/main/scala/org/apache/hudi/HoodieBootstrapRelation.scala
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Expand Up @@ -146,7 +146,7 @@ class HoodieBootstrapRelation(@transient val _sqlContext: SQLContext,
if (fullSchema == null) {
logInfo("Inferring schema..")
val schemaResolver = new TableSchemaResolver(metaClient)
val tableSchema = TableSchemaResolver.appendPartitionColumns(schemaResolver.getTableAvroSchemaWithoutMetadataFields, metaClient.getTableConfig.getPartitionFields)
val tableSchema = schemaResolver.getTableAvroSchema(false)
dataSchema = AvroConversionUtils.convertAvroSchemaToStructType(tableSchema)
fullSchema = StructType(skeletonSchema.fields ++ dataSchema.fields)
}
Expand Down