"IPs are not equal" error when starting H2OContext with Spark Context about sparkling-water HOT 7 CLOSED

Hi @tranlm
can I please ask what version of sparkling-water you're using ? We fixed the problem you're having in this issue https://0xdata.atlassian.net/browse/SW-119. So in order to avoid this problem you should use sparkling water version 1.6.3 and higher, I recommend the latest release 1.6.5

from sparkling-water.

Ahh. I see. I'm currently using 1.6.1. Will upgrade to 1.6.5. Thanks for the quick response!

from sparkling-water.

No worries, if you have other questions/problems, let us know!

Kuba

from sparkling-water.

Hi Jakubhava,
I tried to run pysparkling using jupyter and I got the following error.

An error occurred while calling z:org.apache.spark.h2o.JavaH2OContext.getOrCreate.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 1.0 failed 4 times, most recent failure: Lost task 0.3 in stage 1.0 (TID 14, 172.20.1.159): java.lang.AssertionError: assertion failed: SpreadRDD failure - IPs are not equal: (0,172.20.1.155,-1) != (1, 172.20.1.159)
at scala.Predef$.assert(Predef.scala:170)
at org.apache.spark.h2o.backends.internal.InternalBackendUtils$$anonfun$7.apply(InternalBackendUtils.scala:101)
at org.apache.spark.h2o.backends.internal.InternalBackendUtils$$anonfun$7.apply(InternalBackendUtils.scala:100)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
at scala.collection.Iterator$class.foreach(Iterator.scala:893)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:59)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:104)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:48)
at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:310)
at scala.collection.AbstractIterator.to(Iterator.scala:1336)
at scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:302)
at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1336)
at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:289)
at scala.collection.AbstractIterator.toArray(Iterator.scala:1336)
at org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$13.apply(RDD.scala:912)
at org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$13.apply(RDD.scala:912)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1899)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1899)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70)
at org.apache.spark.scheduler.Task.run(Task.scala:86)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
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)

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:1873)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1886)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1899)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1913)
at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:912)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:358)
at org.apache.spark.rdd.RDD.collect(RDD.scala:911)
at org.apache.spark.h2o.backends.internal.InternalBackendUtils$class.startH2O(InternalBackendUtils.scala:163)
at org.apache.spark.h2o.backends.internal.InternalBackendUtils$.startH2O(InternalBackendUtils.scala:262)
at org.apache.spark.h2o.backends.internal.InternalH2OBackend.init(InternalH2OBackend.scala:99)
at org.apache.spark.h2o.H2OContext.init(H2OContext.scala:100)
at org.apache.spark.h2o.H2OContext$.getOrCreate(H2OContext.scala:275)
at org.apache.spark.h2o.H2OContext.getOrCreate(H2OContext.scala)
at org.apache.spark.h2o.JavaH2OContext.getOrCreate(JavaH2OContext.java:195)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:237)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:280)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:214)
at java.lang.Thread.run(Thread.java:745)
Caused by: java.lang.AssertionError: assertion failed: SpreadRDD failure - IPs are not equal: (0,172.20.1.155,-1) != (1, 172.20.1.159)
at scala.Predef$.assert(Predef.scala:170)
at org.apache.spark.h2o.backends.internal.InternalBackendUtils$$anonfun$7.apply(InternalBackendUtils.scala:101)
at org.apache.spark.h2o.backends.internal.InternalBackendUtils$$anonfun$7.apply(InternalBackendUtils.scala:100)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
at scala.collection.Iterator$class.foreach(Iterator.scala:893)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:59)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:104)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:48)
at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:310)
at scala.collection.AbstractIterator.to(Iterator.scala:1336)
at scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:302)
at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1336)
at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:289)
at scala.collection.AbstractIterator.toArray(Iterator.scala:1336)
at org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$13.apply(RDD.scala:912)
at org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$13.apply(RDD.scala:912)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1899)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1899)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70)
at org.apache.spark.scheduler.Task.run(Task.scala:86)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
... 1 more

Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist-packages/pysparkling/context.py", line 124, in getOrCreate
jhc = jvm.org.apache.spark.h2o.JavaH2OContext.getOrCreate(jsc, selected_conf._jconf)
File "/opt/spark/python/lib/py4j-0.10.3-src.zip/py4j/java_gateway.py", line 1133, in call
answer, self.gateway_client, self.target_id, self.name)
File "/opt/spark/python/lib/pyspark.zip/pyspark/sql/utils.py", line 63, in deco
return f(*a, **kw)
File "/opt/spark/python/lib/py4j-0.10.3-src.zip/py4j/protocol.py", line 319, in get_return_value
format(target_id, ".", name), value)
Py4JJavaError: An error occurred while calling z:org.apache.spark.h2o.JavaH2OContext.getOrCreate.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 1.0 failed 4 times, most recent failure: Lost task 0.3 in stage 1.0 (TID 14, 172.20.1.159): java.lang.AssertionError: assertion failed: SpreadRDD failure - IPs are not equal: (0,172.20.1.155,-1) != (1, 172.20.1.159)
at scala.Predef$.assert(Predef.scala:170)
at org.apache.spark.h2o.backends.internal.InternalBackendUtils$$anonfun$7.apply(InternalBackendUtils.scala:101)
at org.apache.spark.h2o.backends.internal.InternalBackendUtils$$anonfun$7.apply(InternalBackendUtils.scala:100)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
at scala.collection.Iterator$class.foreach(Iterator.scala:893)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:59)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:104)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:48)
at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:310)
at scala.collection.AbstractIterator.to(Iterator.scala:1336)
at scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:302)
at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1336)
at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:289)
at scala.collection.AbstractIterator.toArray(Iterator.scala:1336)
at org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$13.apply(RDD.scala:912)
at org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$13.apply(RDD.scala:912)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1899)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1899)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70)
at org.apache.spark.scheduler.Task.run(Task.scala:86)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
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)

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:1873)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1886)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1899)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1913)
at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:912)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:358)
at org.apache.spark.rdd.RDD.collect(RDD.scala:911)
at org.apache.spark.h2o.backends.internal.InternalBackendUtils$class.startH2O(InternalBackendUtils.scala:163)
at org.apache.spark.h2o.backends.internal.InternalBackendUtils$.startH2O(InternalBackendUtils.scala:262)
at org.apache.spark.h2o.backends.internal.InternalH2OBackend.init(InternalH2OBackend.scala:99)
at org.apache.spark.h2o.H2OContext.init(H2OContext.scala:100)
at org.apache.spark.h2o.H2OContext$.getOrCreate(H2OContext.scala:275)
at org.apache.spark.h2o.H2OContext.getOrCreate(H2OContext.scala)
at org.apache.spark.h2o.JavaH2OContext.getOrCreate(JavaH2OContext.java:195)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:237)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:280)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:214)
at java.lang.Thread.run(Thread.java:745)
Caused by: java.lang.AssertionError: assertion failed: SpreadRDD failure - IPs are not equal: (0,172.20.1.155,-1) != (1, 172.20.1.159)
at scala.Predef$.assert(Predef.scala:170)
at org.apache.spark.h2o.backends.internal.InternalBackendUtils$$anonfun$7.apply(InternalBackendUtils.scala:101)
at org.apache.spark.h2o.backends.internal.InternalBackendUtils$$anonfun$7.apply(InternalBackendUtils.scala:100)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
at scala.collection.Iterator$class.foreach(Iterator.scala:893)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:59)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:104)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:48)
at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:310)
at scala.collection.AbstractIterator.to(Iterator.scala:1336)
at scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:302)
at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1336)
at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:289)
at scala.collection.AbstractIterator.toArray(Iterator.scala:1336)
at org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$13.apply(RDD.scala:912)
at org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$13.apply(RDD.scala:912)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1899)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1899)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70)
at org.apache.spark.scheduler.Task.run(Task.scala:86)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
... 1 more

from sparkling-water.

Hi @swatisaini, thanks for the report. Please let me know your Sparkling Water version, Spark version and deployment mode ( local, YARN, standalone ). Also if you can, share the commands which you used to start Sparkling Water and all other relevant Sparkling Water configuration ( such as configuration to SparkConf, H2OConf ). Without these I'm not able to reason about the problem

from sparkling-water.

Hi Jakubhava,
I'm using spark 2.0.2 and with mesos. And following is the piece of code which i'm running.
from pysparkling import *
hc = H2OContext.getOrCreate(spark)

from sparkling-water.

Hi there,

I am also getting this issue, running

Spark: 2.2
Sparklin Water: 2.2.2
Deployment: Standalone Spark Cluster

Starting h20 with:

import org.apache.spark.h2o._

   val sparkSession = SparkSession
      .builder()
      .master("spark://spark.address:7077")
      .config("spark.executor.memory", "32G")
      .config("spark.executor.cores", "5")
      .config("spark.cores.max", "40")
      .config("spark.ext.h2o.nthreads", "40")  
      .config("spark.scheduler.minRegisteredResourcesRatio", "1")  
      .config("spark.jars", "/Users/app-1.0-SNAPSHOT-jar-with-dependencies.jar")
      .getOrCreate()

val h2oContext = H2OContext.getOrCreate(sparkSession)

from sparkling-water.