Github user marmbrus commented on a diff in the pull request:
https://github.com/apache/spark/pull/17308#discussion_r114841111
--- Diff:
external/kafka-0-10-sql/src/main/scala/org/apache/spark/sql/kafka010/CachedKafkaProducer.scala
---
@@ -0,0 +1,70 @@
+/*
+ * 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 scala.collection.mutable
+
+import org.apache.kafka.clients.producer.KafkaProducer
+
+import org.apache.spark.internal.Logging
+
+private[kafka010] object CachedKafkaProducer extends Logging {
+
+ private val cacheMap = new mutable.HashMap[Int,
KafkaProducer[Array[Byte], Array[Byte]]]()
+
+ private def createKafkaProducer(
+ producerConfiguration: ju.HashMap[String, Object]):
KafkaProducer[Array[Byte], Array[Byte]] = {
+ val kafkaProducer: KafkaProducer[Array[Byte], Array[Byte]] =
+ new KafkaProducer[Array[Byte], Array[Byte]](producerConfiguration)
+ cacheMap.put(producerConfiguration.hashCode(), kafkaProducer)
--- End diff --
Yeah, I don't think this is a good key for the hashmap. There could be
collisions. We should either assign a unique ID to the sink and thread that
through, or come up with some way to canoncicalize the set of parameters that
create the sink. The latter might better since you could maybe reuse the same
producer for more than one query.
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