Github user tdas commented on a diff in the pull request:
https://github.com/apache/spark/pull/17043#discussion_r103044757
--- Diff:
external/kafka-0-10-sql/src/main/scala/org/apache/spark/sql/kafka010/KafkaWriter.scala
---
@@ -0,0 +1,106 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.kafka010
+
+import java.{util => ju}
+
+import org.apache.spark.TaskContext
+import org.apache.spark.internal.Logging
+import org.apache.spark.sql.{AnalysisException, SparkSession}
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.catalyst.expressions._
+import org.apache.spark.sql.execution.{QueryExecution, SQLExecution}
+import org.apache.spark.sql.types.{BinaryType, StringType}
+import org.apache.spark.util.Utils
+
+private[kafka010] object KafkaWriter extends Logging {
+ val TOPIC_ATTRIBUTE_NAME: String = "topic"
+ val KEY_ATTRIBUTE_NAME: String = "key"
+ val VALUE_ATTRIBUTE_NAME: String = "value"
+
+ def write(
+ sparkSession: SparkSession,
+ queryExecution: QueryExecution,
+ kafkaParameters: ju.Map[String, Object],
+ topic: Option[String] = None): Unit = {
+ val schema = queryExecution.logical.output
+ schema.find(p => p.name == TOPIC_ATTRIBUTE_NAME).getOrElse(
+ if (topic == None) {
+ throw new AnalysisException(s"topic option required when no " +
+ s"'$TOPIC_ATTRIBUTE_NAME' attribute is present. Use the " +
+ s"${KafkaSourceProvider.TOPIC_OPTION_KEY} option for setting a
topic.")
+ } else {
+ Literal(topic.get, StringType)
+ }
+ ).dataType match {
+ case StringType => // good
+ case _ =>
+ throw new AnalysisException(s"Topic type must be a String")
+ }
+ schema.find(p => p.name == KEY_ATTRIBUTE_NAME).getOrElse(
+ Literal(null, StringType)
+ ).dataType match {
+ case StringType | BinaryType => // good
+ case _ =>
+ throw new AnalysisException(s"$KEY_ATTRIBUTE_NAME attribute type "
+
+ s"must be a String or BinaryType")
+ }
+ schema.find(p => p.name == VALUE_ATTRIBUTE_NAME).getOrElse(
+ throw new AnalysisException(s"Required attribute
'$VALUE_ATTRIBUTE_NAME' not found")
+ ).dataType match {
+ case StringType | BinaryType => // good
+ case _ =>
+ throw new AnalysisException(s"$VALUE_ATTRIBUTE_NAME attribute type
" +
+ s"must be a String or BinaryType")
+ }
+ SQLExecution.withNewExecutionId(sparkSession, queryExecution) {
+ sparkSession.sparkContext.runJob(queryExecution.toRdd,
+ (taskContext: TaskContext, iter: Iterator[InternalRow]) => {
+ executeTask(
+ iterator = iter,
+ producerConfiguration = kafkaParameters,
+ sparkStageId = taskContext.stageId(),
+ sparkPartitionId = taskContext.partitionId(),
+ sparkAttemptNumber = taskContext.attemptNumber(),
+ inputSchema = schema,
+ defaultTopic = topic)
+ })
+ }
+ }
+
+ /** Writes data out in a single Spark task. */
+ private def executeTask(
+ iterator: Iterator[InternalRow],
+ producerConfiguration: ju.Map[String, Object],
+ sparkStageId: Int,
--- End diff --
you are passing on stageId and partitionId just for logging?
that kind of logging is already done by spark. so i dont think there is any
need to added parameters just for logging.
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