cloud-fan commented on a change in pull request #23714:
[SPARK-26744][SQL]Support schema validation in FileDataSourceV2 framework
URL: https://github.com/apache/spark/pull/23714#discussion_r256791027
##########
File path:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/FileScan.scala
##########
@@ -18,22 +18,29 @@ package org.apache.spark.sql.execution.datasources.v2
import org.apache.hadoop.fs.Path
-import org.apache.spark.sql.SparkSession
+import org.apache.spark.sql.{AnalysisException, SparkSession}
import org.apache.spark.sql.execution.PartitionedFileUtil
import org.apache.spark.sql.execution.datasources._
import org.apache.spark.sql.sources.v2.reader.{Batch, InputPartition, Scan}
-import org.apache.spark.sql.types.StructType
+import org.apache.spark.sql.types.{DataType, StructType}
abstract class FileScan(
sparkSession: SparkSession,
- fileIndex: PartitioningAwareFileIndex) extends Scan with Batch {
+ fileIndex: PartitioningAwareFileIndex,
+ readSchema: StructType) extends Scan with Batch {
/**
* Returns whether a file with `path` could be split or not.
*/
def isSplitable(path: Path): Boolean = {
false
}
+ /**
+ * Returns whether this format supports the given [[DataType]] in write path.
+ * By default all data types are supported.
+ */
+ def supportDataType(dataType: DataType): Boolean = true
Review comment:
per discussion, this is an implementation in file source, not an API. It's
internal so we don't need java here.
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