java.lang.VerifyError: Inconsistent stackmap frames at branch target 152

[alankala]

Environment - Scala 2.11.8, spark 2.1.0 (with spark-core_2.11, spark-streaming_2.11), spark-rabbitmq 0.5.1.

When I run my Spark Streaming job using spark-submit on my standalone spark instance , I get below error - 2017-01-09 12:32:17 ERROR Executor:91 - Exception in task 0.0 in stage 0.0 (TID 0) java.lang.VerifyError: Inconsistent stackmap frames at branch target 152 Exception Details: Location: akka/dispatch/Mailbox.processAllSystemMessages()V @152: getstatic Reason: Type top (current frame, locals[9]) is not assignable to 'akka/dispatch/sysmsg/SystemMessage' (stack map, locals[9]) Current Frame: bci: @131 flags: { } locals: { 'akka/dispatch/Mailbox', 'java/lang/InterruptedException', 'akka/dispatch/sysmsg/SystemMessage', top, 'akka/dispatch/Mailbox', 'java/lang/Throwable', 'java/lang/Throwable' } stack: { integer } Stackmap Frame: bci: @152 flags: { } locals: { 'akka/dispatch/Mailbox', 'java/lang/InterruptedException', 'akka/dispatch/sysmsg/SystemMessage', top, 'akka/dispatch/Mailbox', 'java/lang/Throwable', 'java/lang/Throwable', top, top, 'akka/dispatch/sysmsg/SystemMessage' } stack: { } Bytecode: 0x0000000: 014c 2ab2 0132 b601 35b6 0139 4db2 013e 0x0000010: 2cb6 0142 9900 522a b600 c69a 004b 2c4e 0x0000020: b201 3e2c b601 454d 2db9 0148 0100 2ab6 0x0000030: 0052 2db6 014b b801 0999 000e bb00 e759 0x0000040: 1301 4db7 010f 4cb2 013e 2cb6 0150 99ff 0x0000050: bf2a b600 c69a ffb8 2ab2 0132 b601 35b6 0x0000060: 0139 4da7 ffaa 2ab6 0052 b600 56b6 0154 0x0000070: b601 5a3a 04a7 0091 3a05 1905 3a06 1906 0x0000080: c100 e799 0015 1906 c000 e73a 0719 074c 0x0000090: b200 f63a 08a7 0071 b201 5f19 06b6 0163 0x00000a0: 3a0a 190a b601 6899 0006 1905 bf19 0ab6 0x00000b0: 016c c000 df3a 0b2a b600 52b6 0170 b601 0x00000c0: 76bb 000f 5919 0b2a b600 52b6 017a b601 0x00000d0: 80b6 0186 2ab6 018a bb01 8c59 b701 8e13 0x00000e0: 0190 b601 9419 09b6 0194 1301 96b6 0194 0x00000f0: 190b b601 99b6 0194 b601 9ab7 019d b601 0x0000100: a3b2 00f6 3a08 b201 3e2c b601 4299 0026 0x0000110: 2c3a 09b2 013e 2cb6 0145 4d19 09b9 0148 0x0000120: 0100 1904 2ab6 0052 b601 7a19 09b6 01a7 0x0000130: a7ff d62b c600 09b8 0109 572b bfb1
Exception Handler Table: bci [290, 307] => handler: 120 Stackmap Table: append_frame(@13,Object[#231],Object[#177]) append_frame(@71,Object[#177]) chop_frame(@102,1) full_frame(@120,{Object[#2],Object[#231],Object[#177],Top,Object[#2],Object[#177]},{Object[#223]}) full_frame(@152,{Object[#2],Object[#231],Object[#177],Top,Object[#2],Object[#223],Object[#223],Top,Top,Object[#177]},{}) append_frame(@173,Object[#357]) full_frame(@262,{Object[#2],Object[#231],Object[#177],Top,Object[#2]},{}) same_frame(@307) same_frame(@317)

at akka.dispatch.Mailboxes.<init>(Mailboxes.scala:33)
at akka.actor.ActorSystemImpl.<init>(ActorSystem.scala:628)
at akka.actor.ActorSystem$.apply(ActorSystem.scala:142)
at akka.actor.ActorSystem$.apply(ActorSystem.scala:109)
at akka.actor.ActorSystem$.apply(ActorSystem.scala:100)
at org.apache.spark.streaming.rabbitmq.receiver.RabbitMQReceiver.onStart(RabbitMQInputDStream.scala:57)
at org.apache.spark.streaming.receiver.ReceiverSupervisor.startReceiver(ReceiverSupervisor.scala:149)
at org.apache.spark.streaming.receiver.ReceiverSupervisor.start(ReceiverSupervisor.scala:131)
at org.apache.spark.streaming.scheduler.ReceiverTracker$ReceiverTrackerEndpoint$$anonfun$9.apply(ReceiverTracker.scala:607)
at org.apache.spark.streaming.scheduler.ReceiverTracker$ReceiverTrackerEndpoint$$anonfun$9.apply(ReceiverTracker.scala:597)
at org.apache.spark.SparkContext$$anonfun$34.apply(SparkContext.scala:2021)
at org.apache.spark.SparkContext$$anonfun$34.apply(SparkContext.scala:2021)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:99)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:282)
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)

I see this issue is also reported here - https://issues.apache.org/jira/browse/SPARK-16978.

I started to get this error when I upgraded from spark-rabbitmq_1.6 to latest version(0.5.1) and spark upgraded from spark-1.6.1 to spark-2.1.0

Below is my pom.xml file and if I remove the guava shade plugin, Streaming job runs fine. But I need this plugin.

<properties>
    <slf4j.version>1.7.7</slf4j.version>
    <log4j.version>1.2.17</log4j.version>
    <mapr.hbase.version>5.0.0-mapr</mapr.hbase.version>
    <guava.version>19.0</guava.version>
</properties>
....
<dependency>
        <groupId>com.google.guava</groupId>
        <artifactId>guava</artifactId>
        <version>${guava.version}</version>
 </dependency>
<dependency>
  <groupId>org.apache.spark</groupId>
  <artifactId>spark-core_2.11</artifactId>
  <version>2.1.0</version>
  <scope>provided</scope>
</dependency>
<dependency>
  <groupId>org.apache.spark</groupId>
  <artifactId>spark-streaming_2.11</artifactId>
  <version>2.1.0</version>
  <scope>provided</scope>
</dependency>
<dependency>
   <groupId>com.stratio.receiver</groupId>
   <artifactId>spark-rabbitmq</artifactId>
   <version>0.5.1</version>
 </dependency>
 </dependencies>
<build>
.....
.....
<plugin>
        <groupId>org.apache.maven.plugins</groupId>
        <artifactId>maven-shade-plugin</artifactId>
        <version>2.4.3</version>
        <executions>
            <execution>
                <phase>package</phase>
                <goals>
                    <goal>shade</goal>
                </goals>
                <configuration>
  <relocations>
  <relocation>
    <pattern>com.google</pattern>
    <shadedPattern>shadeio</shadedPattern>
   <includes>
      <include>com.google.**</include>
  </includes>
  </relocation>
</relocations>
<transformers>
                        <transformer implementation="org.apache.maven.plugins.shade.resource.ServicesResourceTransformer" />
                    </transformers>

Has anyone hit this issue before. If yes, how did you solve it.

Thanks Akhila.

[alankala]

Any suggestions?

[brijeshkec11]

I am also seeing the same issue with scala 2.11 and spark 2.0.1 Any suggestions?

[compae]

Now we update the akka version and the next weeks update the spark version to 2.1.0.

Do you have any update?