Github user tdas commented on a diff in the pull request:
https://github.com/apache/spark/pull/11863#discussion_r68147554
--- Diff:
external/kafka-0-10/src/main/scala/org/apache/spark/streaming/kafka/CachedKafkaConsumer.scala
---
@@ -0,0 +1,184 @@
+/*
+ * 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.streaming.kafka
+
+import java.{ util => ju }
+
+import org.apache.kafka.clients.consumer.{ ConsumerConfig, ConsumerRecord,
KafkaConsumer }
+import org.apache.kafka.common.TopicPartition
+
+import org.apache.spark.SparkConf
+import org.apache.spark.internal.Logging
+
+
+/**
+ * Consumer of single topicpartition, intended for cached reuse.
+ * Underlying consumer is not threadsafe, so neither is this,
+ * but processing the same topicpartition and group id in multiple threads
is usually bad anyway.
+ */
+private[kafka]
+class CachedKafkaConsumer[K, V] private(
+ val groupId: String,
+ val topic: String,
+ val partition: Int,
+ val kafkaParams: ju.Map[String, Object]) extends Logging {
+
+ assert(groupId == kafkaParams.get(ConsumerConfig.GROUP_ID_CONFIG),
+ "groupId used for cache key must match the groupId in kafkaParams")
+
+ val topicPartition = new TopicPartition(topic, partition)
+
+ protected val consumer = {
+ val c = new KafkaConsumer[K, V](kafkaParams)
+ val tps = new ju.ArrayList[TopicPartition]()
+ tps.add(topicPartition)
+ c.assign(tps)
+ c
+ }
+
+ // TODO if the buffer was kept around as a random-access structure,
+ // could possibly optimize re-calculating of an RDD in the same batch
+ protected var buffer = ju.Collections.emptyList[ConsumerRecord[K,
V]]().iterator
+ protected var nextOffset = -2L
+
+ def close(): Unit = consumer.close()
+
+ /**
+ * Get the record for the given offset, waiting up to timeout ms if IO
is necessary.
+ * Sequential forward access will use buffers, but random access will be
horribly inefficient.
+ */
+ def get(offset: Long, timeout: Long): ConsumerRecord[K, V] = {
+ log.debug(s"Get $groupId $topic $partition nextOffset $nextOffset
requested $offset")
+ if (offset != nextOffset) {
+ log.info(s"Initial fetch for $groupId $topic $partition $offset")
+ seek(offset)
+ poll(timeout)
+ }
+
+ if (!buffer.hasNext()) { poll(timeout) }
+ assert(buffer.hasNext(),
+ s"Failed to get records for $groupId $topic $partition $offset after
polling for $timeout")
+ var record = buffer.next()
+
+ if (record.offset != offset) {
+ log.info(s"Buffer miss for $groupId $topic $partition $offset")
+ seek(offset)
+ poll(timeout)
+ assert(buffer.hasNext(),
+ s"Failed to get records for $groupId $topic $partition $offset
after polling for $timeout")
+ record = buffer.next()
+ assert(record.offset == offset,
+ s"Got wrong record for $groupId $topic $partition even after
seeking to offset $offset")
+ }
+
+ nextOffset = offset + 1
+ record
+ }
+
+ private def seek(offset: Long): Unit = {
+ log.debug(s"Seeking to $topicPartition $offset")
+ consumer.seek(topicPartition, offset)
+ }
+
+ private def poll(timeout: Long): Unit = {
+ val p = consumer.poll(timeout)
+ val r = p.records(topicPartition)
+ log.debug(s"Polled ${p.partitions()} ${r.size}")
+ buffer = r.iterator
+ }
+
+}
+
+private[kafka]
+object CachedKafkaConsumer extends Logging {
+
+ private case class CacheKey(groupId: String, topic: String, partition:
Int)
+
+ // Don't want to depend on guava, don't want a cleanup thread, use a
simple LinkedHashMap
+ private var cache: ju.LinkedHashMap[CacheKey, CachedKafkaConsumer[_, _]]
= null
+
+ /** Must be called before get, once per JVM, to configure the cache.
Further calls are ignored */
+ def init(
+ initialCapacity: Int,
--- End diff --
wrong indentation.
---
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