stream2000 commented on code in PR #10265:
URL: https://github.com/apache/hudi/pull/10265#discussion_r1418516658
##########
hudi-spark-datasource/hudi-spark3.3.x/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/Spark33LegacyHoodieParquetFileFormat.scala:
##########
@@ -120,9 +120,7 @@ class Spark33LegacyHoodieParquetFileFormat(private val
shouldAppendPartitionValu
val resultSchema = StructType(partitionSchema.fields ++
requiredSchema.fields)
val sqlConf = sparkSession.sessionState.conf
val enableOffHeapColumnVector = sqlConf.offHeapColumnVectorEnabled
- val enableVectorizedReader: Boolean =
Review Comment:
For reviewers: In Spark3.3+, we will use the following code to check if we
can do vecrized read:
```scala
override def supportBatch(sparkSession: SparkSession, schema: StructType):
Boolean = {
val conf = sparkSession.sessionState.conf
ParquetUtils.isBatchReadSupportedForSchema(conf, schema) &&
conf.wholeStageEnabled &&
!WholeStageCodegenExec.isTooManyFields(conf, schema)
}
```
So nested type can support vectorized read since Spark 3.3.
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