Github user mariobriggs commented on a diff in the pull request:
https://github.com/apache/spark/pull/10953#discussion_r51561776
--- Diff:
external/kafka-newapi/src/main/scala/org/apache/spark/streaming/kafka/newapi/KafkaRDD.scala
---
@@ -0,0 +1,237 @@
+/*
+ * 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.newapi
+
+import java.util.{Collections, Properties}
+
+import scala.collection.JavaConverters._
+import scala.collection.mutable.ArrayBuffer
+import scala.reflect.ClassTag
+
+import org.apache.kafka.clients.consumer.{ConsumerRecord, KafkaConsumer}
+import org.apache.kafka.common.TopicPartition
+
+import org.apache.spark.{Logging, Partition, SparkContext, TaskContext}
+import org.apache.spark.partial.{BoundedDouble, PartialResult}
+import org.apache.spark.rdd.RDD
+import org.apache.spark.streaming.kafka.newapi.KafkaCluster.LeaderOffset
+import org.apache.spark.util.NextIterator
+
+
+
+/**
+ * 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.html#configuration";>
+ * 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
+ */
+private[kafka]
+class KafkaRDD[K: ClassTag, V: ClassTag, R: ClassTag] private[spark] (
+ sc: SparkContext,
+ kafkaParams: Map[String, String],
+ val offsetRanges: Array[OffsetRange],
+ messageHandler: ConsumerRecord[K, V] => R
+ ) extends RDD[R](sc, Nil) with Logging with HasOffsetRanges {
+
+ private val KAFKA_DEFAULT_POLL_TIME: String = "0"
--- End diff --
U can reproduce the problem by running the test suites without setting this
- "spark.kafka.poll.time" -> "1000".
So problem basically is that we had implemented the situation when timeout
is too small (i.e. poll returns no data), as a recursive function call. So for
e.g. if it actually takes 700 ms for the kafkaClient to get the data from the
kakfaServer, then for that period of 700 ms, we are making continous recursive
function calls which cause a JVM stackoverflow.
I have issued a PR to your repo, where i reimplemented this functionality
using a imperative loop rather than a recursive function call
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