Hi,
I may have seen this issue already...
What's the cluster manager? How do you spark-submit?
Jacek
On 7 Feb 2017 7:44 p.m., "dgoldenberg" <dgoldenberg...@gmail.com> wrote:
Hi,
Any reason why we might be getting this error? The code seems to work fine
in the non-distributed mode but the same code when run from a Spark job is
not able to get to Elastic.
Spark version: 2.0.1 built for Hadoop 2.4, Scala 2.11
Elastic version: 2.3.1
I've verified the Elastic hosts and the cluster name.
The spot in the code where this happens is:
ClusterHealthResponse clusterHealthResponse = client.admin().cluster()
.prepareHealth()
.setWaitForGreenStatus()
.setTimeout(TimeValue.timeValueSeconds(10))
.get();
Stack trace:
Driver stacktrace:
at
org.apache.spark.scheduler.DAGScheduler.org$apache$spark$
scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1454)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(
DAGScheduler.scala:1442)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(
DAGScheduler.scala:1441)
at
scala.collection.mutable.ResizableArray$class.foreach(
ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at
org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1441)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$
handleTaskSetFailed$1.apply(DAGScheduler.scala:811)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$
handleTaskSetFailed$1.apply(DAGScheduler.scala:811)
at scala.Option.foreach(Option.scala:257)
at
org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(
DAGScheduler.scala:811)
at
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.
doOnReceive(DAGScheduler.scala:1667)
at
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.
onReceive(DAGScheduler.scala:1622)
at
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.
onReceive(DAGScheduler.scala:1611)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:632)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1890)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1903)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1916)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1930)
at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1.apply(RDD.scala:902)
at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1.apply(RDD.scala:900)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(
RDDOperationScope.scala:151)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(
RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:358)
at org.apache.spark.rdd.RDD.foreachPartition(RDD.scala:900)
at
org.apache.spark.api.java.JavaRDDLike$class.foreachPartition(JavaRDDLike.
scala:218)
at
org.apache.spark.api.java.AbstractJavaRDDLike.foreachPartition(JavaRDDLike.
scala:45)
at com.myco.MyDriver$3.call(com.myco.MyDriver.java:214)
at com.myco.MyDriver$3.call(KafkaSparkStreamingDriver.java:201)
at
org.apache.spark.streaming.api.java.JavaDStreamLike$$
anonfun$foreachRDD$1.apply(JavaDStreamLike.scala:272)
at
org.apache.spark.streaming.api.java.JavaDStreamLike$$
anonfun$foreachRDD$1.apply(JavaDStreamLike.scala:272)
at
org.apache.spark.streaming.dstream.DStream$$anonfun$
foreachRDD$1$$anonfun$apply$mcV$sp$3.apply(DStream.scala:627)
at
org.apache.spark.streaming.dstream.DStream$$anonfun$
foreachRDD$1$$anonfun$apply$mcV$sp$3.apply(DStream.scala:627)
at
org.apache.spark.streaming.dstream.ForEachDStream$$
anonfun$1$$anonfun$apply$mcV$sp$1.apply$mcV$sp(ForEachDStream.scala:51)
at
org.apache.spark.streaming.dstream.ForEachDStream$$
anonfun$1$$anonfun$apply$mcV$sp$1.apply(ForEachDStream.scala:51)
at
org.apache.spark.streaming.dstream.ForEachDStream$$
anonfun$1$$anonfun$apply$mcV$sp$1.apply(ForEachDStream.scala:51)
at
org.apache.spark.streaming.dstream.DStream.createRDDWithLocalProperties(
DStream.scala:415)
at
org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply$mcV$sp(
ForEachDStream.scala:50)
at
org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply(
ForEachDStream.scala:50)
at
org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply(
ForEachDStream.scala:50)
at scala.util.Try$.apply(Try.scala:192)
at org.apache.spark.streaming.scheduler.Job.run(Job.scala:39)
at
org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.
apply$mcV$sp(JobScheduler.scala:247)
at
org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.
apply(JobScheduler.scala:247)
at
org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.
apply(JobScheduler.scala:247)
at scala.util.DynamicVariable.withValue(DynamicVariable.scala:58)
at
org.apache.spark.streaming.scheduler.JobScheduler$
JobHandler.run(JobScheduler.scala:246)
at
java.util.concurrent.ThreadPoolExecutor.runWorker(
ThreadPoolExecutor.java:1142)
at
java.util.concurrent.ThreadPoolExecutor$Worker.run(
ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Caused by: NoNodeAvailableException[None of the configured nodes are
available: [{#transport#-1}{XX.XXX.XXX.XX}{XX.XXX.XXX.XX:9300}]]
at
org.elasticsearch.client.transport.TransportClientNodesService.
ensureNodesAreAvailable(TransportClientNodesService.java:290)
at
org.elasticsearch.client.transport.TransportClientNodesService.execute(
TransportClientNodesService.java:207)
at
org.elasticsearch.client.transport.support.TransportProxyClient.execute(
TransportProxyClient.java:55)
at
org.elasticsearch.client.transport.TransportClient.
doExecute(TransportClient.java:288)
at
org.elasticsearch.client.support.AbstractClient.execute(AbstractClient.java:
359)
at
org.elasticsearch.client.support.AbstractClient$ClusterAdmin.execute(
AbstractClient.java:853)
at
org.elasticsearch.action.ActionRequestBuilder.execute(
ActionRequestBuilder.java:86)
at
org.elasticsearch.action.ActionRequestBuilder.execute(
ActionRequestBuilder.java:56)
at
org.elasticsearch.action.ActionRequestBuilder.get(
ActionRequestBuilder.java:64)
at com.myco.MyDriver.work()
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