[GitHub] [spark] grundprinzip commented on a diff in pull request #40160: [SPARK-41725][CONNECT] Eager Execution of DF.sql()

["grundprinzip (via GitHub)" <gi...@apache.org>]

grundprinzip commented on code in PR #40160:
URL: https://github.com/apache/spark/pull/40160#discussion_r1173683435


##########
connector/connect/server/src/main/scala/org/apache/spark/sql/connect/planner/SparkConnectPlanner.scala:
##########
@@ -1450,10 +1458,79 @@ class SparkConnectPlanner(val session: SparkSession) {
         handleWriteOperationV2(command.getWriteOperationV2)
       case proto.Command.CommandTypeCase.EXTENSION =>
         handleCommandPlugin(command.getExtension)
+      case proto.Command.CommandTypeCase.SQL_COMMAND =>
+        handleSqlCommand(command.getSqlCommand, clientId, responseObserver)
       case _ => throw new UnsupportedOperationException(s"$command not supported.")
     }
   }
 
+  def handleSqlCommand(
+      getSqlCommand: SqlCommand,
+      clientId: String,
+      responseObserver: StreamObserver[ExecutePlanResponse]): Unit = {
+    // Eagerly execute commands of the provided SQL string.
+    val df = session.sql(getSqlCommand.getSql, getSqlCommand.getArgsMap)
+    // Check if commands have been executed.
+    val isCommand = df.queryExecution.commandExecuted.isInstanceOf[CommandResult]
+    val rows = df.logicalPlan match {
+      case lr: LocalRelation => lr.data
+      case cr: CommandResult => cr.rows
+      case _ => Seq.empty
+    }
+
+    // Convert the results to Arrow.
+    val schema = df.schema
+    val maxRecordsPerBatch = session.sessionState.conf.arrowMaxRecordsPerBatch
+    val maxBatchSize = (SparkEnv.get.conf.get(CONNECT_GRPC_ARROW_MAX_BATCH_SIZE) * 0.7).toLong
+    val timeZoneId = session.sessionState.conf.sessionLocalTimeZone
+
+    // Convert the data.
+    val bytes = if (rows.isEmpty) {
+      ArrowConverters.createEmptyArrowBatch(schema, timeZoneId)
+    } else {
+      val batches = ArrowConverters.toBatchWithSchemaIterator(
+        rows.iterator,
+        schema,
+        maxRecordsPerBatch,
+        maxBatchSize,
+        timeZoneId)
+      assert(batches.size == 1)
+      batches.next()
+    }
+
+    // To avoid explicit handling of the result on the client, we build the expected input
+    // of the relation on the server. The client has to simply forward the result.
+    val result = SqlCommandResult.newBuilder()
+    if (isCommand) {
+      result.setRelation(
+        proto.Relation
+          .newBuilder()
+          .setLocalRelation(
+            proto.LocalRelation
+              .newBuilder()
+              .setData(ByteString.copyFrom(bytes))))
+    } else {
+      result.setRelation(
+        proto.Relation
+          .newBuilder()
+          .setSql(
+            proto.SQL
+              .newBuilder()
+              .setQuery(getSqlCommand.getSql)
+              .putAllArgs(getSqlCommand.getArgsMap)))
+    }
+    // Exactly one SQL Command Result Batch
+    responseObserver.onNext(
+      ExecutePlanResponse
+        .newBuilder()
+        .setClientId(clientId)
+        .setSqlCommandResult(result)
+        .build())
+
+    // Send Metrics
+    SparkConnectStreamHandler.sendMetricsToResponse(clientId, df)

Review Comment:
   Thanks
   



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