alexeykudinkin commented on code in PR #5708:
URL: https://github.com/apache/hudi/pull/5708#discussion_r927259929
##########
hudi-spark-datasource/hudi-spark-common/src/main/scala/org/apache/hudi/HoodieBaseRelation.scala:
##########
@@ -564,42 +538,57 @@ abstract class HoodieBaseRelation(val sqlContext:
SQLContext,
// we have to eagerly initialize all of the readers even though only
one specific to the type
// of the file being read will be used. This is required to avoid
serialization of the whole
// relation (containing file-index for ex) and passing it to the
executor
- val reader = tableBaseFileFormat match {
- case HoodieFileFormat.PARQUET =>
- HoodieDataSourceHelper.buildHoodieParquetReader(
- sparkSession = spark,
- dataSchema = dataSchema.structTypeSchema,
- partitionSchema = partitionSchema,
- requiredSchema = requiredSchema.structTypeSchema,
- filters = filters,
- options = options,
- hadoopConf = hadoopConf,
- // We're delegating to Spark to append partition values to every row
only in cases
- // when these corresponding partition-values are not persisted w/in
the data file itself
- appendPartitionValues = shouldExtractPartitionValuesFromPartitionPath
- )
+ val (read: (PartitionedFile => Iterator[InternalRow]), schema: StructType)
=
+ tableBaseFileFormat match {
+ case HoodieFileFormat.PARQUET =>
+ (
+ HoodieDataSourceHelper.buildHoodieParquetReader(
+ sparkSession = spark,
+ dataSchema = dataSchema.structTypeSchema,
+ partitionSchema = partitionSchema,
+ requiredSchema = requiredSchema.structTypeSchema,
+ filters = filters,
+ options = options,
+ hadoopConf = hadoopConf,
+ // We're delegating to Spark to append partition values to every
row only in cases
+ // when these corresponding partition-values are not persisted
w/in the data file itself
+ appendPartitionValues =
shouldExtractPartitionValuesFromPartitionPath
+ ),
+ // Since partition values by default are omitted, and not
persisted w/in data-files by Spark,
+ // data-file readers (such as [[ParquetFileFormat]]) have to
inject partition values while reading
+ // the data. As such, actual full schema produced by such reader
is composed of
+ // a) Prepended partition column values
+ // b) Data-file schema (projected or not)
+ StructType(partitionSchema.fields ++
requiredSchema.structTypeSchema.fields)
Review Comment:
It was actually a typo -- partition columns are actually appended (Spark's
ParquetFileFormat has it incorrectly
[here](https://github.com/apache/spark/blob/master/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFileFormat.scala#L237)
##########
hudi-spark-datasource/hudi-spark-common/src/main/scala/org/apache/hudi/HoodieBaseRelation.scala:
##########
@@ -564,42 +538,57 @@ abstract class HoodieBaseRelation(val sqlContext:
SQLContext,
// we have to eagerly initialize all of the readers even though only
one specific to the type
// of the file being read will be used. This is required to avoid
serialization of the whole
// relation (containing file-index for ex) and passing it to the
executor
- val reader = tableBaseFileFormat match {
- case HoodieFileFormat.PARQUET =>
- HoodieDataSourceHelper.buildHoodieParquetReader(
- sparkSession = spark,
- dataSchema = dataSchema.structTypeSchema,
- partitionSchema = partitionSchema,
- requiredSchema = requiredSchema.structTypeSchema,
- filters = filters,
- options = options,
- hadoopConf = hadoopConf,
- // We're delegating to Spark to append partition values to every row
only in cases
- // when these corresponding partition-values are not persisted w/in
the data file itself
- appendPartitionValues = shouldExtractPartitionValuesFromPartitionPath
- )
+ val (read: (PartitionedFile => Iterator[InternalRow]), schema: StructType)
=
+ tableBaseFileFormat match {
+ case HoodieFileFormat.PARQUET =>
+ (
+ HoodieDataSourceHelper.buildHoodieParquetReader(
+ sparkSession = spark,
+ dataSchema = dataSchema.structTypeSchema,
+ partitionSchema = partitionSchema,
+ requiredSchema = requiredSchema.structTypeSchema,
+ filters = filters,
+ options = options,
+ hadoopConf = hadoopConf,
+ // We're delegating to Spark to append partition values to every
row only in cases
+ // when these corresponding partition-values are not persisted
w/in the data file itself
+ appendPartitionValues =
shouldExtractPartitionValuesFromPartitionPath
+ ),
+ // Since partition values by default are omitted, and not
persisted w/in data-files by Spark,
+ // data-file readers (such as [[ParquetFileFormat]]) have to
inject partition values while reading
+ // the data. As such, actual full schema produced by such reader
is composed of
+ // a) Prepended partition column values
+ // b) Data-file schema (projected or not)
+ StructType(partitionSchema.fields ++
requiredSchema.structTypeSchema.fields)
Review Comment:
It was actually a typo -- partition columns are actually appended (Spark's
ParquetFileFormat has it incorrectly
[here](https://github.com/apache/spark/blob/master/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFileFormat.scala#L237))
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