Please see this thread: http://search-hadoop.com/m/LgpTk2aVYgr/Hadoop+guava+upgrade&subj=Re+Time+to+address+the+Guava+version+problem
> On Jan 19, 2015, at 6:03 AM, Romi Kuntsman <r...@totango.com> wrote: > > I have recently encountered a similar problem with Guava version collision > with Hadoop. > > Isn't it more correct to upgrade Hadoop to use the latest Guava? Why are they > staying in version 11, does anyone know? > > Romi Kuntsman, Big Data Engineer > http://www.totango.com > >> On Wed, Jan 7, 2015 at 7:59 AM, Niranda Perera <niranda.per...@gmail.com> >> wrote: >> Hi Sean, >> >> I removed the hadoop dependencies from the app and ran it on the cluster. It >> gives a java.io.EOFException >> >> 15/01/07 11:19:29 INFO MemoryStore: ensureFreeSpace(177166) called with >> curMem=0, maxMem=2004174766 >> 15/01/07 11:19:29 INFO MemoryStore: Block broadcast_0 stored as values in >> memory (estimated size 173.0 KB, free 1911.2 MB) >> 15/01/07 11:19:29 INFO MemoryStore: ensureFreeSpace(25502) called with >> curMem=177166, maxMem=2004174766 >> 15/01/07 11:19:29 INFO MemoryStore: Block broadcast_0_piece0 stored as bytes >> in memory (estimated size 24.9 KB, free 1911.1 MB) >> 15/01/07 11:19:29 INFO BlockManagerInfo: Added broadcast_0_piece0 in memory >> on 10.100.5.109:43924 (size: 24.9 KB, free: 1911.3 MB) >> 15/01/07 11:19:29 INFO BlockManagerMaster: Updated info of block >> broadcast_0_piece0 >> 15/01/07 11:19:29 INFO SparkContext: Created broadcast 0 from hadoopFile at >> AvroRelation.scala:45 >> 15/01/07 11:19:29 INFO FileInputFormat: Total input paths to process : 1 >> 15/01/07 11:19:29 INFO SparkContext: Starting job: collect at >> SparkPlan.scala:84 >> 15/01/07 11:19:29 INFO DAGScheduler: Got job 0 (collect at >> SparkPlan.scala:84) with 2 output partitions (allowLocal=false) >> 15/01/07 11:19:29 INFO DAGScheduler: Final stage: Stage 0(collect at >> SparkPlan.scala:84) >> 15/01/07 11:19:29 INFO DAGScheduler: Parents of final stage: List() >> 15/01/07 11:19:29 INFO DAGScheduler: Missing parents: List() >> 15/01/07 11:19:29 INFO DAGScheduler: Submitting Stage 0 (MappedRDD[6] at map >> at SparkPlan.scala:84), which has no missing parents >> 15/01/07 11:19:29 INFO MemoryStore: ensureFreeSpace(4864) called with >> curMem=202668, maxMem=2004174766 >> 15/01/07 11:19:29 INFO MemoryStore: Block broadcast_1 stored as values in >> memory (estimated size 4.8 KB, free 1911.1 MB) >> 15/01/07 11:19:29 INFO MemoryStore: ensureFreeSpace(3481) called with >> curMem=207532, maxMem=2004174766 >> 15/01/07 11:19:29 INFO MemoryStore: Block broadcast_1_piece0 stored as bytes >> in memory (estimated size 3.4 KB, free 1911.1 MB) >> 15/01/07 11:19:29 INFO BlockManagerInfo: Added broadcast_1_piece0 in memory >> on 10.100.5.109:43924 (size: 3.4 KB, free: 1911.3 MB) >> 15/01/07 11:19:29 INFO BlockManagerMaster: Updated info of block >> broadcast_1_piece0 >> 15/01/07 11:19:29 INFO SparkContext: Created broadcast 1 from broadcast at >> DAGScheduler.scala:838 >> 15/01/07 11:19:29 INFO DAGScheduler: Submitting 2 missing tasks from Stage 0 >> (MappedRDD[6] at map at SparkPlan.scala:84) >> 15/01/07 11:19:29 INFO TaskSchedulerImpl: Adding task set 0.0 with 2 tasks >> 15/01/07 11:19:29 INFO TaskSetManager: Starting task 0.0 in stage 0.0 (TID >> 0, 10.100.5.109, PROCESS_LOCAL, 1340 bytes) >> 15/01/07 11:19:29 INFO TaskSetManager: Starting task 1.0 in stage 0.0 (TID >> 1, 10.100.5.109, PROCESS_LOCAL, 1340 bytes) >> 15/01/07 11:19:29 WARN TaskSetManager: Lost task 1.0 in stage 0.0 (TID 1, >> 10.100.5.109): java.io.EOFException >> at >> java.io.ObjectInputStream$BlockDataInputStream.readFully(ObjectInputStream.java:2722) >> at java.io.ObjectInputStream.readFully(ObjectInputStream.java:1009) >> at >> org.apache.hadoop.io.DataOutputBuffer$Buffer.write(DataOutputBuffer.java:63) >> at org.apache.hadoop.io.DataOutputBuffer.write(DataOutputBuffer.java:101) >> at org.apache.hadoop.io.UTF8.readChars(UTF8.java:216) >> at org.apache.hadoop.io.UTF8.readString(UTF8.java:208) >> at org.apache.hadoop.mapred.FileSplit.readFields(FileSplit.java:87) >> at >> org.apache.hadoop.io.ObjectWritable.readObject(ObjectWritable.java:237) >> at org.apache.hadoop.io.ObjectWritable.readFields(ObjectWritable.java:66) >> at >> org.apache.spark.SerializableWritable$$anonfun$readObject$1.apply$mcV$sp(SerializableWritable.scala:43) >> at org.apache.spark.util.Utils$.tryOrIOException(Utils.scala:985) >> at >> org.apache.spark.SerializableWritable.readObject(SerializableWritable.scala:39) >> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) >> at >> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:39) >> at >> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:25) >> at java.lang.reflect.Method.invoke(Method.java:597) >> at java.io.ObjectStreamClass.invokeReadObject(ObjectStreamClass.java:969) >> at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1871) >> at >> java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1775) >> at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1327) >> at >> java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1969) >> at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1893) >> at >> java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1775) >> at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1327) >> at >> java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1969) >> at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1893) >> at >> java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1775) >> at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1327) >> at java.io.ObjectInputStream.readObject(ObjectInputStream.java:349) >> at >> org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:62) >> at >> org.apache.spark.serializer.JavaSerializerInstance.deserialize(JavaSerializer.scala:87) >> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:178) >> at >> java.util.concurrent.ThreadPoolExecutor$Worker.runTask(ThreadPoolExecutor.java:895) >> at >> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:918) >> at java.lang.Thread.run(Thread.java:662) >> >> >> I'm running the program using IDE. Not using spark-submit. Can we not submit >> an app straight from the IDE to the spark cluster? >> >> Cheers >> >>> On Tue, Jan 6, 2015 at 3:53 PM, Sean Owen <so...@cloudera.com> wrote: >>> Oh, are you actually bundling Hadoop in your app? that may be the problem. >>> If you're using stand-alone mode, why include Hadoop? In any event, Spark >>> and Hadoop are intended to be 'provided' dependencies in the app you send >>> to spark-submit. >>> >>>> On Tue, Jan 6, 2015 at 10:15 AM, Niranda Perera <niranda.per...@gmail.com> >>>> wrote: >>>> Hi Sean, >>>> >>>> My mistake, Guava 11 dependency came from the hadoop-commons indeed. >>>> >>>> I'm running the following simple app in spark 1.2.0 standalone local >>>> cluster (2 workers) with Hadoop 1.2.1 >>>> >>>> public class AvroSparkTest { >>>> public static void main(String[] args) throws Exception { >>>> SparkConf sparkConf = new SparkConf() >>>> .setMaster("spark://niranda-ThinkPad-T540p:7077") >>>> //("local[2]") >>>> .setAppName("avro-spark-test"); >>>> >>>> JavaSparkContext sparkContext = new JavaSparkContext(sparkConf); >>>> JavaSQLContext sqlContext = new JavaSQLContext(sparkContext); >>>> JavaSchemaRDD episodes = AvroUtils.avroFile(sqlContext, >>>> >>>> "/home/niranda/projects/avro-spark-test/src/test/resources/episodes.avro"); >>>> episodes.printSchema(); >>>> episodes.registerTempTable("avroTable"); >>>> List<Row> result = sqlContext.sql("SELECT * FROM >>>> avroTable").collect(); >>>> >>>> for (Row row : result) { >>>> System.out.println(row.toString()); >>>> } >>>> } >>>> } >>>> >>>> As you pointed out, this error occurs while adding the hadoop dependency. >>>> this runs without a problem when the hadoop dependency is removed and the >>>> master is set to local[]. >>>> >>>> Cheers >>>> >>>>> On Tue, Jan 6, 2015 at 3:23 PM, Sean Owen <so...@cloudera.com> wrote: >>>>> -dev >>>>> >>>>> Guava was not downgraded to 11. That PR was not merged. It was part of a >>>>> discussion about, indeed, what to do about potential Guava version >>>>> conflicts. Spark uses Guava, but so does Hadoop, and so do user programs. >>>>> >>>>> Spark uses 14.0.1 in fact: >>>>> https://github.com/apache/spark/blob/master/pom.xml#L330 >>>>> >>>>> This is a symptom of conflict between Spark's Guava 14 and Hadoop's Guava >>>>> 11. See for example https://issues.apache.org/jira/browse/HIVE-7387 as >>>>> well. >>>>> >>>>> Guava is now shaded in Spark as of 1.2.0 (and 1.1.x?), so I would think a >>>>> lot of these problems are solved. As we've seen though, this one is >>>>> tricky. >>>>> >>>>> What's your Spark version? and what are you executing? what mode -- >>>>> standalone, YARN? What Hadoop version? >>>>> >>>>> >>>>>> On Tue, Jan 6, 2015 at 8:38 AM, Niranda Perera >>>>>> <niranda.per...@gmail.com> wrote: >>>>>> Hi, >>>>>> >>>>>> I have been running a simple Spark app on a local spark cluster and I >>>>>> came across this error. >>>>>> >>>>>> Exception in thread "main" java.lang.NoSuchMethodError: >>>>>> com.google.common.hash.HashFunction.hashInt(I)Lcom/google/common/hash/HashCode; >>>>>> at >>>>>> org.apache.spark.util.collection.OpenHashSet.org$apache$spark$util$collection$OpenHashSet$$hashcode(OpenHashSet.scala:261) >>>>>> at >>>>>> org.apache.spark.util.collection.OpenHashSet$mcI$sp.getPos$mcI$sp(OpenHashSet.scala:165) >>>>>> at >>>>>> org.apache.spark.util.collection.OpenHashSet$mcI$sp.contains$mcI$sp(OpenHashSet.scala:102) >>>>>> at >>>>>> org.apache.spark.util.SizeEstimator$$anonfun$visitArray$2.apply$mcVI$sp(SizeEstimator.scala:214) >>>>>> at scala.collection.immutable.Range.foreach$mVc$sp(Range.scala:141) >>>>>> at >>>>>> org.apache.spark.util.SizeEstimator$.visitArray(SizeEstimator.scala:210) >>>>>> at >>>>>> org.apache.spark.util.SizeEstimator$.visitSingleObject(SizeEstimator.scala:169) >>>>>> at >>>>>> org.apache.spark.util.SizeEstimator$.org$apache$spark$util$SizeEstimator$$estimate(SizeEstimator.scala:161) >>>>>> at >>>>>> org.apache.spark.util.SizeEstimator$.estimate(SizeEstimator.scala:155) >>>>>> at >>>>>> org.apache.spark.util.collection.SizeTracker$class.takeSample(SizeTracker.scala:78) >>>>>> at >>>>>> org.apache.spark.util.collection.SizeTracker$class.afterUpdate(SizeTracker.scala:70) >>>>>> at >>>>>> org.apache.spark.util.collection.SizeTrackingVector.$plus$eq(SizeTrackingVector.scala:31) >>>>>> at >>>>>> org.apache.spark.storage.MemoryStore.unrollSafely(MemoryStore.scala:249) >>>>>> at >>>>>> org.apache.spark.storage.MemoryStore.putIterator(MemoryStore.scala:136) >>>>>> at >>>>>> org.apache.spark.storage.MemoryStore.putIterator(MemoryStore.scala:114) >>>>>> at >>>>>> org.apache.spark.storage.BlockManager.doPut(BlockManager.scala:787) >>>>>> at >>>>>> org.apache.spark.storage.BlockManager.putIterator(BlockManager.scala:638) >>>>>> at >>>>>> org.apache.spark.storage.BlockManager.putSingle(BlockManager.scala:992) >>>>>> at >>>>>> org.apache.spark.broadcast.TorrentBroadcast.writeBlocks(TorrentBroadcast.scala:98) >>>>>> at >>>>>> org.apache.spark.broadcast.TorrentBroadcast.<init>(TorrentBroadcast.scala:84) >>>>>> at >>>>>> org.apache.spark.broadcast.TorrentBroadcastFactory.newBroadcast(TorrentBroadcastFactory.scala:34) >>>>>> at >>>>>> org.apache.spark.broadcast.TorrentBroadcastFactory.newBroadcast(TorrentBroadcastFactory.scala:29) >>>>>> at >>>>>> org.apache.spark.broadcast.BroadcastManager.newBroadcast(BroadcastManager.scala:62) >>>>>> at org.apache.spark.SparkContext.broadcast(SparkContext.scala:945) >>>>>> at org.apache.spark.SparkContext.hadoopFile(SparkContext.scala:695) >>>>>> at >>>>>> com.databricks.spark.avro.AvroRelation.buildScan$lzycompute(AvroRelation.scala:45) >>>>>> at >>>>>> com.databricks.spark.avro.AvroRelation.buildScan(AvroRelation.scala:44) >>>>>> at >>>>>> org.apache.spark.sql.sources.DataSourceStrategy$.apply(DataSourceStrategy.scala:56) >>>>>> at >>>>>> org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:58) >>>>>> at >>>>>> org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:58) >>>>>> at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371) >>>>>> at >>>>>> org.apache.spark.sql.catalyst.planning.QueryPlanner.apply(QueryPlanner.scala:59) >>>>>> at >>>>>> org.apache.spark.sql.SQLContext$QueryExecution.sparkPlan$lzycompute(SQLContext.scala:418) >>>>>> at >>>>>> org.apache.spark.sql.SQLContext$QueryExecution.sparkPlan(SQLContext.scala:416) >>>>>> at >>>>>> org.apache.spark.sql.SQLContext$QueryExecution.executedPlan$lzycompute(SQLContext.scala:422) >>>>>> at >>>>>> org.apache.spark.sql.SQLContext$QueryExecution.executedPlan(SQLContext.scala:422) >>>>>> at org.apache.spark.sql.SchemaRDD.collect(SchemaRDD.scala:444) >>>>>> at >>>>>> org.apache.spark.sql.api.java.JavaSchemaRDD.collect(JavaSchemaRDD.scala:114) >>>>>> >>>>>> >>>>>> While looking into this I found out that Guava was downgraded to version >>>>>> 11 in this PR. >>>>>> https://github.com/apache/spark/pull/1610 >>>>>> >>>>>> In this PR OpenHashSet.scala:261 line hashInt has been changed to >>>>>> hashLong. >>>>>> But when I actually run my app, "java.lang.NoSuchMethodError: >>>>>> com.google.common.hash.HashFunction.hashInt" error occurs, >>>>>> which is understandable because hashInt is not available before Guava 12. >>>>>> >>>>>> So, I''m wondering why this occurs? >>>>>> >>>>>> Cheers >>>>>> -- >>>>>> Niranda Perera >>>> >>>> >>>> >>>> -- >>>> Niranda >> >> >> >> -- >> Niranda >
