amaliujia commented on code in PR #38468:
URL: https://github.com/apache/spark/pull/38468#discussion_r1018700003
##########
connector/connect/src/main/scala/org/apache/spark/sql/connect/service/SparkConnectStreamHandler.scala:
##########
@@ -114,10 +123,97 @@ 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 rows = dataframe.queryExecution.executedPlan.execute()
+ val numPartitions = rows.getNumPartitions
+ var numSent = 0
+
+ if (numPartitions > 0) {
+ type Batch = (Array[Byte], Long, Long)
+
+ val batches = rows.mapPartitionsInternal { iter =>
+ ArrowConverters
+ .toArrowBatchIterator(iter, schema, maxRecordsPerBatch, timeZoneId)
+ }
+
+ val signal = new Object
+ val partitions = Array.fill[Array[Batch]](numPartitions)(null)
+
+ val processPartition = (iter: Iterator[Batch]) => iter.toArray
+
+ val resultHandler = (partitionId: Int, partition: Array[Batch]) => {
+ signal.synchronized {
+ partitions(partitionId) = partition
+ signal.notify()
+ }
+ val i = 0 // Unit
+ }
+
+ spark.sparkContext.runJob(batches, processPartition, resultHandler)
+
+ var currentPartitionId = 0
+ while (currentPartitionId < numPartitions) {
+ val partition = signal.synchronized {
+ while (partitions(currentPartitionId) == null) {
+ signal.wait()
+ }
+ val partition = partitions(currentPartitionId)
+ partitions(currentPartitionId) = null
+ partition
+ }
+
+ // only send non-empty partitions
+ if (partition.nonEmpty && partition.exists(_._1.nonEmpty)) {
+ partition.foreach { case (bytes, count, size) =>
+ val response = proto.Response.newBuilder().setClientId(clientId)
+ val batch = proto.Response.ArrowBatch
+ .newBuilder()
+ .setRowCount(count)
+ .setUncompressedBytes(size)
+ .setCompressedBytes(bytes.length)
+ .setData(ByteString.copyFrom(bytes))
+ .build()
+ response.setArrowBatch(batch)
+ responseObserver.onNext(response.build())
+ }
+ numSent += 1
+ }
+
+ currentPartitionId += 1
+ }
+ }
+
+ // make sure at least 1 batch will be sent
+ if (numSent == 0) {
Review Comment:
+1.
with this we at least can get rid of the `Optional[Pandas]` from the API
interface.
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