rdblue commented on a change in pull request #23208: [SPARK-25530][SQL] data
source v2 API refactor (batch write)
URL: https://github.com/apache/spark/pull/23208#discussion_r247685011
##########
File path: sql/core/src/main/scala/org/apache/spark/sql/DataFrameWriter.scala
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@@ -241,33 +242,38 @@ final class DataFrameWriter[T] private[sql](ds:
Dataset[T]) {
assertNotBucketed("save")
- val cls = DataSource.lookupDataSource(source,
df.sparkSession.sessionState.conf)
- if (classOf[DataSourceV2].isAssignableFrom(cls)) {
- val source =
cls.getConstructor().newInstance().asInstanceOf[DataSourceV2]
- source match {
- case provider: BatchWriteSupportProvider =>
- val sessionOptions = DataSourceV2Utils.extractSessionConfigs(
- source,
- df.sparkSession.sessionState.conf)
- val options = sessionOptions ++ extraOptions
-
+ val session = df.sparkSession
+ val cls = DataSource.lookupDataSource(source, session.sessionState.conf)
+ if (classOf[TableProvider].isAssignableFrom(cls)) {
+ val provider =
cls.getConstructor().newInstance().asInstanceOf[TableProvider]
+ val sessionOptions = DataSourceV2Utils.extractSessionConfigs(
+ provider, session.sessionState.conf)
+ val options = sessionOptions ++ extraOptions
+ val dsOptions = new DataSourceOptions(options.asJava)
+ provider.getTable(dsOptions) match {
+ case table: SupportsBatchWrite =>
if (mode == SaveMode.Append) {
- val relation = DataSourceV2Relation.createRelationForWrite(source,
options)
+ val relation = DataSourceV2Relation.create(table, options)
runCommand(df.sparkSession, "save") {
AppendData.byName(relation, df.logicalPlan)
}
-
} else {
- val writer = provider.createBatchWriteSupport(
- UUID.randomUUID().toString,
- df.logicalPlan.output.toStructType,
- mode,
- new DataSourceOptions(options.asJava))
-
- if (writer.isPresent) {
- runCommand(df.sparkSession, "save") {
- WriteToDataSourceV2(writer.get, df.logicalPlan)
- }
+ val writeBuilder = table.newWriteBuilder(dsOptions)
+ .withQueryId(UUID.randomUUID().toString)
+ .withInputDataSchema(df.logicalPlan.schema)
+ writeBuilder match {
+ case s: SupportsSaveMode =>
+ val write = s.mode(mode).buildForBatch()
+ // It can only return null with `SupportsSaveMode`. We can
clean it up after
+ // removing `SupportsSaveMode`.
+ if (write != null) {
+ runCommand(df.sparkSession, "save") {
+ WriteToDataSourceV2(write, df.logicalPlan)
+ }
+ }
+
+ case _ => throw new AnalysisException(
+ s"data source ${table.name} does not support SaveMode")
Review comment:
The error should be that the source doesn't support the mode, not that it
doesn't support SaveMode generally.
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