Github user koeninger commented on a diff in the pull request:
https://github.com/apache/spark/pull/11863#discussion_r62284776
--- Diff:
external/kafka-beta/src/main/scala/org/apache/spark/streaming/kafka/KafkaRDD.scala
---
@@ -0,0 +1,259 @@
+/*
+ * 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 scala.collection.mutable.ArrayBuffer
+import scala.reflect.{classTag, ClassTag}
+
+import org.apache.kafka.clients.consumer.{ ConsumerConfig, ConsumerRecord }
+import org.apache.kafka.common.TopicPartition
+
+import org.apache.spark.{Partition, SparkContext, SparkException,
TaskContext}
+import org.apache.spark.internal.Logging
+import org.apache.spark.partial.{BoundedDouble, PartialResult}
+import org.apache.spark.rdd.RDD
+import org.apache.spark.scheduler.ExecutorCacheTaskLocation
+import org.apache.spark.storage.StorageLevel
+
+/**
+ * A batch-oriented interface for consuming from Kafka.
+ * Starting and ending offsets are specified in advance,
+ * so that you can control exactly-once semantics.
+ * @param kafkaParams Kafka
+ * <a
href="http://kafka.apache.org/documentation.htmll#newconsumerconfigs";>
+ * configuration parameters</a>. Requires "bootstrap.servers" to be set
+ * with Kafka broker(s) specified in host1:port1,host2:port2 form.
+ * @param offsetRanges offset ranges that define the Kafka data belonging
to this RDD
+ */
+
+class KafkaRDD[
+ K: ClassTag,
+ V: ClassTag] private[spark] (
+ sc: SparkContext,
+ val kafkaParams: ju.Map[String, Object],
+ val offsetRanges: Array[OffsetRange],
+ val preferredHosts: ju.Map[TopicPartition, String]
+) extends RDD[ConsumerRecord[K, V]](sc, Nil) with Logging with
HasOffsetRanges {
+
+ assert("none" ==
+
kafkaParams.get(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG).asInstanceOf[String],
+ ConsumerConfig.AUTO_OFFSET_RESET_CONFIG +
+ " must be set to none for executor kafka params, else messages may
not match offsetRange")
+
+ assert(false ==
+
kafkaParams.get(ConsumerConfig.ENABLE_AUTO_COMMIT_CONFIG).asInstanceOf[Boolean],
+ ConsumerConfig.ENABLE_AUTO_COMMIT_CONFIG +
+ " must be set to false for executor kafka params, else offsets may
commit before processing")
+
+ // TODO is it necessary to have separate configs for initial poll time
vs ongoing poll time?
+ private val pollTimeout =
conf.getLong("spark.streaming.kafka.consumer.poll.ms", 256)
+ private val cacheInitialCapacity =
+ conf.getInt("spark.streaming.kafka.consumer.cache.initialCapacity", 16)
+ private val cacheMaxCapacity =
+ conf.getInt("spark.streaming.kafka.consumer.cache.maxCapacity", 64)
--- End diff --
The cache size is user configurable. The way getPreferredLocations is
structured should keep the cache from thrashing too badly as long as the cache
size is proportional to the number of total partitions / number of executors.
I know it sucks that it's a connection per partition rather than a connection
per broker, but with the way the consumer is designed, there isn't an easy way
around that (unlike the old simple consumer).
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