Github user markgrover commented on a diff in the pull request:
https://github.com/apache/spark/pull/11863#discussion_r59956197
--- 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.AUTO_OFFSET_RESET_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)
--- End diff --
This is not a suggestion, just a note about something I noticed. We are not
namespacing property names to differentiate between the new and old consumer
API implementations. For example, a user can't tell just by looking at the
property name 'spark.streaming.kafka.consumer.poll.ms' if it applies to the old
implementation or the new implementation. And, may be that's ok and even
desirable if there are a good chunk of spark.streaming.kafka.* properties
that'd be shared between the two implementations. But, if not, it may not be a
bad idea to create a separate namespace for these properties.
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