hvanhovell commented on code in PR #38468:
URL: https://github.com/apache/spark/pull/38468#discussion_r1015381686
##########
connector/connect/src/main/scala/org/apache/spark/sql/connect/service/SparkConnectStreamHandler.scala:
##########
@@ -117,10 +129,91 @@ class SparkConnectStreamHandler(responseObserver:
StreamObserver[Response]) exte
responseObserver.onNext(response.build())
}
- responseObserver.onNext(sendMetricsToResponse(clientId, rows))
+ responseObserver.onNext(sendMetricsToResponse(clientId, dataframe))
responseObserver.onCompleted()
}
+ def processRowsAsArrowBatches(clientId: String, dataframe: DataFrame): Unit
= {
+ val spark = dataframe.sparkSession
+ val schema = dataframe.schema
+ // TODO: control the batch size instead of max records
+ val maxRecordsPerBatch = spark.sessionState.conf.arrowMaxRecordsPerBatch
+ val timeZoneId = spark.sessionState.conf.sessionLocalTimeZone
+
+ SQLExecution.withNewExecutionId(dataframe.queryExecution,
Some("collectArrow")) {
+ val pool =
ThreadUtils.newDaemonSingleThreadExecutor("connect-collect-arrow")
+ val tasks = collection.mutable.ArrayBuffer.empty[Future[_]]
+ val rows = dataframe.queryExecution.executedPlan.execute()
+
+ if (rows.getNumPartitions > 0) {
+ val batches = rows.mapPartitionsInternal { iter =>
+ ArrowConverters
+ .toArrowBatchIterator(iter, schema, maxRecordsPerBatch, timeZoneId)
+ }
+
+ val processPartition = (iter: Iterator[(Array[Byte], Long, Long)]) =>
iter.toArray
+
+ val resultHandler = (partitionId: Int, taskResult: Array[(Array[Byte],
Long, Long)]) => {
Review Comment:
I think we should discuss client side ordering of results a bit more. My
main problem with this is is that it is unexpected behavior, undocumented
behavior (hint hint), and it puts more burden on the client (it needs to
reorder results and buffer them).
cc @HyukjinKwon @amaliujia @grundprinzip
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