I am using Spark 2.1.1 in Java and elasticsearch-spark-20_2.11 (version 5.3.2) in order to write data in Elasticsearch.I create JavaStreamingContext which I then set to await termination, so the application should always retrieve new data.
After I read the stream, I split it into RDDs and for each one I apply SQL aggregations and then write it to Elasticsearch as follows:
recordStream.foreachRDD(rdd -> {
if (rdd.count() > 0) {
/*
* Create RDD from JSON
*/
Dataset<Row> df = spark.read().json(rdd.rdd());
df.createOrReplaceTempView("data");
df.cache();
/*
* Apply the aggregations
*/
Dataset aggregators = spark.sql(ORDER_TYPE_DB);
JavaEsSparkSQL.saveToEs(aggregators.toDF(), "order_analytics/record");
aggregators = spark.sql(ORDER_CUSTOMER_DB);
JavaEsSparkSQL.saveToEs(aggregators.toDF(), "customer_analytics/record");
}
});
This works fine the first time data is read and inserted to Elasticsearch, but when more data are retrieved by the stream, I get the following error:
org.elasticsearch.hadoop.EsHadoopIllegalArgumentException: Cannot detect ES version - typically this happens if the network/Elasticsearch cluster is not accessible or when targeting a WAN/Cloud instance without the proper setting 'es.nodes.wan.only'
at org.elasticsearch.hadoop.rest.InitializationUtils.discoverEsVersion(InitializationUtils.java:250)
at org.elasticsearch.hadoop.rest.RestService.createWriter(RestService.java:546)
at org.elasticsearch.spark.rdd.EsRDDWriter.write(EsRDDWriter.scala:58)
at org.elasticsearch.spark.sql.EsSparkSQL$$anonfun$saveToEs$1.apply(EsSparkSQL.scala:94)
at org.elasticsearch.spark.sql.EsSparkSQL$$anonfun$saveToEs$1.apply(EsSparkSQL.scala:94)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:99)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:322)
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: org.elasticsearch.hadoop.rest.EsHadoopTransportException: java.net.BindException: Address already in use: JVM_Bind
at org.elasticsearch.hadoop.rest.NetworkClient.execute(NetworkClient.java:129)
at org.elasticsearch.hadoop.rest.RestClient.execute(RestClient.java:461)
at org.elasticsearch.hadoop.rest.RestClient.execute(RestClient.java:425)
at org.elasticsearch.hadoop.rest.RestClient.execute(RestClient.java:429)
at org.elasticsearch.hadoop.rest.RestClient.get(RestClient.java:155)
at org.elasticsearch.hadoop.rest.RestClient.remoteEsVersion(RestClient.java:627)
at org.elasticsearch.hadoop.rest.InitializationUtils.discoverEsVersion(InitializationUtils.java:243)
... 10 more
Caused by: java.net.BindException: Address already in use: JVM_Bind
at java.net.DualStackPlainSocketImpl.bind0(Native Method)
at java.net.DualStackPlainSocketImpl.socketBind(DualStackPlainSocketImpl.java:106)
at java.net.AbstractPlainSocketImpl.bind(AbstractPlainSocketImpl.java:387)
at java.net.PlainSocketImpl.bind(PlainSocketImpl.java:190)
at java.net.Socket.bind(Socket.java:644)
at java.net.Socket.<init>(Socket.java:433)
at java.net.Socket.<init>(Socket.java:286)
at org.apache.commons.httpclient.protocol.DefaultProtocolSocketFactory.createSocket(DefaultProtocolSocketFactory.java:80)
at org.apache.commons.httpclient.protocol.DefaultProtocolSocketFactory.createSocket(DefaultProtocolSocketFactory.java:122)
at org.apache.commons.httpclient.HttpConnection.open(HttpConnection.java:707)
at org.apache.commons.httpclient.HttpMethodDirector.executeWithRetry(HttpMethodDirector.java:387)
at org.apache.commons.httpclient.HttpMethodDirector.executeMethod(HttpMethodDirector.java:171)
at org.apache.commons.httpclient.HttpClient.executeMethod(HttpClient.java:397)
at org.apache.commons.httpclient.HttpClient.executeMethod(HttpClient.java:323)
at org.elasticsearch.hadoop.rest.commonshttp.CommonsHttpTransport.execute(CommonsHttpTransport.java:478)
at org.elasticsearch.hadoop.rest.NetworkClient.execute(NetworkClient.java:112)
... 16 more
Any ideas what the problem could be?
Spark uses default configuration and is instantiated in Java as
SparkConf conf = new SparkConf().setAppName(topic).setMaster("local");
JavaStreamingContext streamingContext = new JavaStreamingContext(conf, Durations.seconds(2));
Elasticsearch is configured via Docker compose with the following environment parameters:
- cluster.name=cp-es-cluster
- node.name=cloud1
- http.cors.enabled=true
- http.cors.allow-origin="*"
- network.host=0.0.0.0
- discovery.zen.ping.unicast.hosts=${ENV_IP}
- network.publish_host=${ENV_IP}
- discovery.zen.minimum_master_nodes=1
- xpack.security.enabled=false
- xpack.monitoring.enabled=false
Related
I am using Flink on the cluster. As I submitted the task, I got the following exception:
Caused by: java.util.concurrent.CompletionException: java.lang.IllegalStateException: Trying to work with offloaded serialized shuffle descriptors.
at java.util.concurrent.CompletableFuture.encodeRelay(CompletableFuture.java:326)
at java.util.concurrent.CompletableFuture.completeRelay(CompletableFuture.java:338)
at java.util.concurrent.CompletableFuture.uniRelay(CompletableFuture.java:925)
at java.util.concurrent.CompletableFuture$UniRelay.tryFire(CompletableFuture.java:913)
at java.util.concurrent.CompletableFuture.postComplete(CompletableFuture.java:488)
at java.util.concurrent.CompletableFuture.completeExceptionally(CompletableFuture.java:1990)
at org.apache.flink.runtime.rpc.akka.AkkaInvocationHandler.lambda$invokeRpc$0(AkkaInvocationHandler.java:234)
at java.util.concurrent.CompletableFuture.uniWhenComplete(CompletableFuture.java:774)
at java.util.concurrent.CompletableFuture$UniWhenComplete.tryFire(CompletableFuture.java:750)
at java.util.concurrent.CompletableFuture.postComplete(CompletableFuture.java:488)
at java.util.concurrent.CompletableFuture.completeExceptionally(CompletableFuture.java:1990)
at org.apache.flink.runtime.concurrent.FutureUtils$1.onComplete(FutureUtils.java:1079)
at akka.dispatch.OnComplete.internal(Future.scala:263)
at akka.dispatch.OnComplete.internal(Future.scala:261)
at akka.dispatch.japi$CallbackBridge.apply(Future.scala:191)
at akka.dispatch.japi$CallbackBridge.apply(Future.scala:188)
at scala.concurrent.impl.CallbackRunnable.run(Promise.scala:36)
at org.apache.flink.runtime.concurrent.Executors$DirectExecutionContext.execute(Executors.java:73)
at scala.concurrent.impl.CallbackRunnable.executeWithValue(Promise.scala:44)
at scala.concurrent.impl.Promise$DefaultPromise.tryComplete(Promise.scala:252)
at akka.pattern.PromiseActorRef.$bang(AskSupport.scala:572)
at akka.remote.DefaultMessageDispatcher.dispatch(Endpoint.scala:101)
at akka.remote.EndpointReader$$anonfun$receive$2.applyOrElse(Endpoint.scala:999)
at akka.actor.Actor$class.aroundReceive(Actor.scala:517)
at akka.remote.EndpointActor.aroundReceive(Endpoint.scala:458)
... 9 more
Caused by: java. lang.IllegalStateException: Trying to work with offloaded serialized shuffle descriptors.
at org.apache.flink.runtime.deployment.InputGateDeploymentDescriptor.getShuffleDescriptors(InputGateDeploymentDescriptor.java:150)
at org.apache.flink.runtime.io.network.partition.consumer.SingleInputGateFactory.create(SingleInputGateFactory.java:125)
at org.apache.flink.runtime.io.network.NettyShuffleEnvironment.createInputGates(NettyShuffleEnvironment.java:261)
at org.apache.flink.runtime.taskmanager.Task.<init>(Task.java:420)
at org.apache.flink.runtime.taskexecutor.TaskExecutor.submitTask(TaskExecutor.java:737)
at sun.reflect.GeneratedMethodAccessor32.invoke(Unknown Source)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.flink.runtime.rpc.akka.AkkaRpcActor.lambda$handleRpcInvocation$1(AkkaRpcActor.java:316)
at org.apache.flink.runtime.concurrent.akka.ClassLoadingUtils.runWithContextClassLoader(ClassLoadingUtils.java:83)
at org.apache.flink.runtime.rpc.akka.AkkaRpcActor.handleRpcInvocation(AkkaRpcActor.java:314)
at org.apache.flink.runtime.rpc.akka.AkkaRpcActor.handleRpcMessage(AkkaRpcActor.java:217)
at org.apache.flink.runtime.rpc.akka.AkkaRpcActor.handleMessage(AkkaRpcActor.java:163)
at akka.japi.pf.UnitCaseStatement.apply(CaseStatements.scala:24)
at akka.japi.pf.UnitCaseStatement.apply(CaseStatements.scala:20)
at scala.PartialFunction.applyOrElse(PartialFunction.scala:123)
at scala.PartialFunction.applyOrElse$(PartialFunction.scala:122)
at akka.japi.pf.UnitCaseStatement.applyOrElse(CaseStatements.scala:20)
at scala.PartialFunction$OrElse.applyOrElse(PartialFunction.scala:171)
at scala.PartialFunction$OrElse.applyOrElse(PartialFunction.scala:172)
at scala.PartialFunction$OrElse.applyOrElse(PartialFunction.scala:172)
at akka.actor.Actor.aroundReceive(Actor.scala:537)
at akka.actor.Actor.aroundReceive$(Actor.scala:535)
at akka.actor.AbstractActor.aroundReceive(AbstractActor.scala:220)
at akka.actor.ActorCell.receiveMessage(ActorCell.scala:580)
at akka.actor.ActorCell.invoke(ActorCell.scala:548)
at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:270)
at akka.dispatch.Mailbox.run(Mailbox.scala:231)
at akka.dispatch.Mailbox.exec(Mailbox.scala:243)
at java.util.concurrent.ForkJoinTask.doExec(ForkJoinTask.java:289)
at java.util.concurrent.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1056)
at java.util.concurrent.ForkJoinPool.runWorker(ForkJoinPool.java:1692)
at java.util.concurrent.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:175)
Flink version: 1.13.6;
Scala version: 2.11
Kafka version: 2.2.2
Part of my code:
object batchProcess {
def main(args:Array[String]): Unit = {
val host = "localhost"
val port = 6379
val env = StreamExecutionEnvironment.getExecutionEnvironment
// read from kafka
val source = KafkaSource.builder[String].setBootstrapServers("localhost:9092")
.setTopics("movie_rating_records").setGroupId("my-group").setStartingOffsets(OffsetsInitializer.earliest)
.setValueOnlyDeserializer(new SimpleStringSchema())
.setBounded(OffsetsInitializer.latest).build()
// val inputDataStream = env.readTextFile("a.txt")
val inputDataStream = env.fromSource(source, WatermarkStrategy.noWatermarks(), "Kafka Source")
val dataStream = inputDataStream
.map( data =>{
val arr = data.split(",")
( arr(0),arr(1).toInt,arr(2).toInt,arr(3).toFloat,arr(4).toLong)
})
val (counterUserIdPos,counterUserIdNeg,counterMovieIdPos,counterMovieIdNeg,counterUserId2MovieId) = commonProcess(dataStream)
counterUserIdPos.map(x =>{
val jedisIns = new Jedis(host,port,100000)
jedisIns.set("batch2feature_userId_rating1_"+x._1.toString, x._2.toString)
jedisIns.close()
})
env.execute("test")
}
}
The input stream from Kafka is a string split by a comma, for example: 1542295208rating,556,112852,1.0,1542295208. The above code process the string and puts them into another datastream process function. And finally, it writes the result into Redis.
Any help or hints on resolving the issue would be greatly appreciated!
Here aer a few pointers I can think of
Netty is the internal serialization mechanism of Flink => from the stack trace we know the error is likely occurring in one of the .map or so, not when interacting with Kafka nor Redis.
Serialization issues are sometimes happening in Flink when using Scala. Maybe the second .map is somehow causing connection pools or some other context instance to be serialized into the lambda, so replacing it with a Flink SinkFunction might help (in addition to improving performance since you'd only create one Jedis instance per partition).
Investigate also what serialization is going on in the commonProcess.
Essentially, you should be hunting for a place where the code somehow needs to serialize some instance whose type would confuse the Flink serialization mechanism.
I am trying to run a vertx WebClient within AWS Lambda. AWS Lambdas have a max of 1024 file descriptors and are non-adjustable. I am having trouble finding what exactly is using up all of my file descriptors. I am only using the WebClient from vertx and not running any verticles. Here is my shared WebClient:
var webClientOptions = new WebClientOptions()
.setSsl(true)
.setUseAlpn(true)
.setReusePort(true)
.setDefaultPort(443)
.setHttp2MaxPoolSize(30)
.setProtocolVersion(HttpVersion.HTTP_2)
.setSslHandshakeTimeout(30)
.setIdleTimeout(5)
.setIdleTimeoutUnit(TimeUnit.SECONDS);
return WebClient.create(vertx, webClientOptions);
This client is reused between lambda invocations, and never closed.
How I am using it:
var requestFutures = new ArrayList<CompletableFuture<Foo>>();
for (var request : requests) {
CompletableFuture<Foo> future = new CompletableFuture();
requestFutures.add(future);
Buffer buffer = Buffer.buffer(request.getPayload());
httpRequest.sendBuffer(buffer, (res) -> {
future.complete(res);
});
}
for (var requestFuture : requestFutures) {
requestFuture.get();
}
Where I have 45k-65k requests to send. What I get is:
io.netty.channel.ChannelException: Failed to open a socket.
at io.netty.channel.socket.nio.NioSocketChannel.newSocket(NioSocketChannel.java:70)
at io.netty.channel.socket.nio.NioSocketChannel.<init>(NioSocketChannel.java:87)
at io.netty.channel.socket.nio.NioSocketChannel.<init>(NioSocketChannel.java:80)
at io.netty.bootstrap.AbstractBootstrap.initAndRegister(AbstractBootstrap.java:320)
at io.netty.bootstrap.Bootstrap.doResolveAndConnect(Bootstrap.java:163)
at io.netty.bootstrap.Bootstrap.connect(Bootstrap.java:145)
at io.vertx.core.net.impl.ChannelProvider.handleConnect(ChannelProvider.java:140)
at io.vertx.core.net.impl.ChannelProvider.connect(ChannelProvider.java:93)
at io.vertx.core.http.impl.HttpChannelConnector.doConnect(HttpChannelConnector.java:171)
at io.vertx.core.http.impl.HttpChannelConnector.connect(HttpChannelConnector.java:105)
at io.vertx.core.http.impl.pool.Pool$Holder.connect(Pool.java:125)
at io.vertx.core.http.impl.pool.Pool.checkPendingTasks(Pool.java:250)
at io.netty.util.concurrent.AbstractEventExecutor.safeExecute(AbstractEventExecutor.java:163)
at io.netty.util.concurrent.SingleThreadEventExecutor.runAllTasks(SingleThreadEventExecutor.java:404)
at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:474)
at io.netty.util.concurrent.SingleThreadEventExecutor$5.run(SingleThreadEventExecutor.java:909)
at io.netty.util.concurrent.FastThreadLocalRunnable.run(FastThreadLocalRunnable.java:30)
at java.base/java.lang.Thread.run(Unknown Source)
Caused by: java.net.SocketException: Too many open files
at java.base/sun.nio.ch.Net.socket0(Native Method)
at java.base/sun.nio.ch.Net.socket(Unknown Source)
at java.base/sun.nio.ch.Net.socket(Unknown Source)
at java.base/sun.nio.ch.SocketChannelImpl.<init>(Unknown Source)
at java.base/sun.nio.ch.SelectorProviderImpl.openSocketChannel(Unknown Source)
at io.netty.channel.socket.nio.NioSocketChannel.newSocket(NioSocketChannel.java:68)
... 17 more
When I run this locally and watch the open files/sockets in the OSX Activity Monitor it shoots up to thousands. I don't understand why it's doing this based on how i've configured the WebClientOptions.
Can someone tell from this information why I would be using so many file descriptors?
setHttp2MaxPoolSize(30) is a lot, in theory you only need 1 because it is HTTP/2
I'm trying to connect to Hbase using Hbase client API in a kerborized Cloudera cluster.
Sample code:
Configuration hbaseConf = HBaseConfiguration.create();
/*hbaseConf.set("hbase.master", "somenode.net:2181");
hbaseConf.set("hbase.client.scanner.timeout.period", "1200000");
hbaseConf.set("hbase.zookeeper.quorum",
"somenode.net,somenode2.net");
hbaseConf.set("zookeeper.znode.parent", "/hbase");*/
hbaseConf.setInt("timeout", 120000);
hbaseConf.set(TableInputFormat.INPUT_TABLE, tableName);
//hbaseConf.addResource("src/main/resources/hbase-site.xml");
UserGroupInformation.setConfiguration(hbaseConf);
UserGroupInformation.loginUserFromKeytab("principal", "keytab");
JavaPairRDD<ImmutableBytesWritable, Result> javaPairRdd = ctx
.newAPIHadoopRDD(hbaseConf, TableInputFormat.class,
ImmutableBytesWritable.class, Result.class);
I tried to set the hbase-site.xml in the maven project resources, also passed as jar file in spark-submit command using --jars, but nothing works.
Error log:
Caused by: java.net.SocketTimeoutException: callTimeout=60000, callDuration=68545: row '¨namespace:test,,00000000000000' on table 'hbase:meta' at region=hbase:meta,,1.1588230740, hostname=hostname.net,60020,1511970022474, seqNum=0
at org.apache.hadoop.hbase.client.RpcRetryingCaller.callWithRetries(RpcRetryingCaller.java:159)
at org.apache.hadoop.hbase.client.ResultBoundedCompletionService$QueueingFuture.run(ResultBoundedCompletionService.java:65)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
Caused by: java.io.IOException: Broken pipe
at sun.nio.ch.FileDispatcherImpl.write0(Native Method)
at sun.nio.ch.SocketDispatcher.write(SocketDispatcher.java:47)
at sun.nio.ch.IOUtil.writeFromNativeBuffer(IOUtil.java:93)
at sun.nio.ch.IOUtil.write(IOUtil.java:65)
at sun.nio.ch.SocketChannelImpl.write(SocketChannelImpl.java:487)
at org.apache.hadoop.net.SocketOutputStream$Writer.performIO(SocketOutputStream.java:63)
at org.apache.hadoop.net.SocketIOWithTimeout.doIO(SocketIOWithTimeout.java:142)
at org.apache.hadoop.net.SocketOutputStream.write(SocketOutputStream.java:159)
at org.apache.hadoop.net.SocketOutputStream.write(SocketOutputStream.java:117)
at java.io.BufferedOutputStream.flushBuffer(BufferedOutputStream.java:82)
at java.io.BufferedOutputStream.flush(BufferedOutputStream.java:140)
at java.io.DataOutputStream.flush(DataOutputStream.java:123)
at org.apache.hadoop.hbase.ipc.IPCUtil.write(IPCUtil.java:278)
at org.apache.hadoop.hbase.ipc.IPCUtil.write(IPCUtil.java:266)
at org.apache.hadoop.hbase.ipc.RpcClientImpl$Connection.writeRequest(RpcClientImpl.java:920)
at org.apache.hadoop.hbase.ipc.RpcClientImpl$Connection.tracedWriteRequest(RpcClientImpl.java:873)
at org.apache.hadoop.hbase.ipc.RpcClientImpl.call(RpcClientImpl.java:1242)
at org.apache.hadoop.hbase.ipc.AbstractRpcClient.callBlockingMethod(AbstractRpcClient.java:227)
at org.apache.hadoop.hbase.ipc.AbstractRpcClient$BlockingRpcChannelImplementation.callBlockingMethod(AbstractRpcClient.java:336)
at org.apache.hadoop.hbase.protobuf.generated.ClientProtos$ClientService$BlockingStub.scan(ClientProtos.java:34094)
at org.apache.hadoop.hbase.client.ScannerCallable.openScanner(ScannerCallable.java:394)
at org.apache.hadoop.hbase.client.ScannerCallable.call(ScannerCallable.java:203)
at org.apache.hadoop.hbase.client.ScannerCallable.call(ScannerCallable.java:64)
at org.apache.hadoop.hbase.client.RpcRetryingCaller.callWithoutRetries(RpcRetryingCaller.java:200)
at org.apache.hadoop.hbase.client.ScannerCallableWithReplicas$RetryingRPC.call(ScannerCallableWithReplicas.java:360)
at org.apache.hadoop.hbase.client.ScannerCallableWithReplicas$RetryingRPC.call(ScannerCallableWithReplicas.java:334)
at org.apache.hadoop.hbase.client.RpcRetryingCaller.callWithRetries(RpcRetryingCaller.java:126)
... 4 more
18/02/26 16:25:42 INFO spark.SparkContext: Invoking stop() from shutdown hook
The problem you are facing is because your environment is not properly set up.
I have answer it to my own question here
I play around with the twitter connector in apache flink and now want to save some streamed data in my local hdfs instance. In the flink documentation is a small BucketerSink example, but my program always quit with the following error:
Exception in thread "main" org.apache.flink.runtime.client.JobExecutionException: Job execution failed.
at org.apache.flink.runtime.jobmanager.JobManager$$anonfun$handleMessage$1$$anonfun$applyOrElse$7.apply$mcV$sp(JobManager.scala:933)
at org.apache.flink.runtime.jobmanager.JobManager$$anonfun$handleMessage$1$$anonfun$applyOrElse$7.apply(JobManager.scala:876)
at org.apache.flink.runtime.jobmanager.JobManager$$anonfun$handleMessage$1$$anonfun$applyOrElse$7.apply(JobManager.scala:876)
at scala.concurrent.impl.Future$PromiseCompletingRunnable.liftedTree1$1(Future.scala:24)
at scala.concurrent.impl.Future$PromiseCompletingRunnable.run(Future.scala:24)
at akka.dispatch.TaskInvocation.run(AbstractDispatcher.scala:40)
at akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:397)
at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
at scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
at scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
at scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
Caused by: java.lang.ExceptionInInitializerError
at org.apache.hadoop.util.StringUtils.<clinit>(StringUtils.java:76)
at org.apache.hadoop.security.Groups.parseStaticMapping(Groups.java:92)
at org.apache.hadoop.security.Groups.<init>(Groups.java:76)
at org.apache.hadoop.security.Groups.getUserToGroupsMappingService(Groups.java:239)
at org.apache.hadoop.security.UserGroupInformation.initialize(UserGroupInformation.java:255)
at org.apache.hadoop.security.UserGroupInformation.ensureInitialized(UserGroupInformation.java:232)
at org.apache.hadoop.security.UserGroupInformation.loginUserFromSubject(UserGroupInformation.java:718)
at org.apache.hadoop.security.UserGroupInformation.getLoginUser(UserGroupInformation.java:703)
at org.apache.hadoop.security.UserGroupInformation.getCurrentUser(UserGroupInformation.java:605)
at org.apache.hadoop.fs.FileSystem$Cache$Key.<init>(FileSystem.java:2473)
at org.apache.hadoop.fs.FileSystem$Cache$Key.<init>(FileSystem.java:2465)
at org.apache.hadoop.fs.FileSystem$Cache.get(FileSystem.java:2331)
at org.apache.hadoop.fs.FileSystem.get(FileSystem.java:369)
at org.apache.hadoop.fs.Path.getFileSystem(Path.java:296)
at org.apache.flink.streaming.connectors.fs.bucketing.BucketingSink.initFileSystem(BucketingSink.java:418)
at org.apache.flink.streaming.connectors.fs.bucketing.BucketingSink.initializeState(BucketingSink.java:352)
at org.apache.flink.streaming.util.functions.StreamingFunctionUtils.tryRestoreFunction(StreamingFunctionUtils.java:177)
at org.apache.flink.streaming.util.functions.StreamingFunctionUtils.restoreFunctionState(StreamingFunctionUtils.java:159)
at org.apache.flink.streaming.api.operators.AbstractUdfStreamOperator.initializeState(AbstractUdfStreamOperator.java:105)
at org.apache.flink.streaming.api.operators.AbstractStreamOperator.initializeState(AbstractStreamOperator.java:251)
at org.apache.flink.streaming.runtime.tasks.StreamTask.initializeOperators(StreamTask.java:678)
at org.apache.flink.streaming.runtime.tasks.StreamTask.initializeState(StreamTask.java:666)
at org.apache.flink.streaming.runtime.tasks.StreamTask.invoke(StreamTask.java:252)
at org.apache.flink.runtime.taskmanager.Task.run(Task.java:702)
at java.base/java.lang.Thread.run(Thread.java:844)
Caused by: java.lang.StringIndexOutOfBoundsException: begin 0, end 3, length 1
at java.base/java.lang.String.checkBoundsBeginEnd(String.java:3116)
at java.base/java.lang.String.substring(String.java:1885)
at org.apache.hadoop.util.Shell.<clinit>(Shell.java:49)
... 25 more
Do you have any ideas what went wrong with my code? I use the inital twitter connector example for testing and my environment is build up with a docker container for hdfs. The ports are correctly mapped form docker to my local machine and i also can check the status of hdfs on the web ui.
Here is my code approach:
StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment().setParallelism(1);
Properties props = new Properties();
props.setProperty(TwitterSource.CONSUMER_KEY, "KEY");
props.setProperty(TwitterSource.CONSUMER_SECRET, "SECRET");
props.setProperty(TwitterSource.TOKEN, "TOKEN");
props.setProperty(TwitterSource.TOKEN_SECRET, "TOKENSECRET");
DataStream<String> streamSource = env.addSource(new TwitterSource(props));
DataStream<Tuple2<String, Integer>> tweets = streamSource
// selecting English tweets and splitting to (word, 1)
.flatMap(new SelectGermanAndTokenizeFlatMap())
// group by words and sum their occurrences
.keyBy(0)
.timeWindow(Time.minutes(1), Time.seconds(30))
.sum(1);
BucketingSink<Tuple2<String, Integer>> sink = new BucketingSink<>("hdfs://localhost:8020/flink/twitter-test");
sink.setBucketer(new DateTimeBucketer<Tuple2<String, Integer>>("yyyy-MM-dd--HHmm"));
sink.setBatchSize(1024 * 1024 * 400);
tweets.addSink(sink);
//tweets.print();
env.execute("Twitter Streaming Example");
I'm trying to create JAVARDD on s3 file but not able to create rdd.Can someone help me to solve this problem.
Code :
SparkConf conf = new SparkConf().setAppName(appName).setMaster("local");
JavaSparkContext javaSparkContext = new JavaSparkContext(conf);
javaSparkContext.hadoopConfiguration().set("fs.s3.awsAccessKeyId",
accessKey);
javaSparkContext.hadoopConfiguration().set("fs.s3.awsSecretAccessKey",
secretKey);
javaSparkContext.hadoopConfiguration().set("fs.s3.impl",
"org.apache.hadoop.fs.s3native.NativeS3FileSystem");
JavaRDD<String> rawData = sparkContext
.textFile("s3://mybucket/sample.txt");
This code throwing exception
2015-05-06 18:58:57 WARN LoadSnappy:46 - Snappy native library not loaded
java.lang.IllegalArgumentException: java.net.URISyntaxException: Expected scheme-specific part at index 3: s3:
at org.apache.hadoop.fs.Path.initialize(Path.java:148)
at org.apache.hadoop.fs.Path.<init>(Path.java:126)
at org.apache.hadoop.fs.Path.<init>(Path.java:50)
at org.apache.hadoop.fs.FileSystem.globPathsLevel(FileSystem.java:1084)
at org.apache.hadoop.fs.FileSystem.globPathsLevel(FileSystem.java:1087)
at org.apache.hadoop.fs.FileSystem.globPathsLevel(FileSystem.java:1087)
at org.apache.hadoop.fs.FileSystem.globPathsLevel(FileSystem.java:1087)
at org.apache.hadoop.fs.FileSystem.globPathsLevel(FileSystem.java:1087)
at org.apache.hadoop.fs.FileSystem.globStatusInternal(FileSystem.java:1023)
at org.apache.hadoop.fs.FileSystem.globStatus(FileSystem.java:987)
at org.apache.hadoop.mapred.FileInputFormat.listStatus(FileInputFormat.java:177)
at org.apache.hadoop.mapred.FileInputFormat.getSplits(FileInputFormat.java:208)
at org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:203)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:219)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:217)
at scala.Option.getOrElse(Option.scala:120)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:217)
at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:32)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:219)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:217)
at scala.Option.getOrElse(Option.scala:120)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:217)
at org.apache.spark.rdd.RDD.take(RDD.scala:1156)
at org.apache.spark.rdd.RDD.first(RDD.scala:1189)
at org.apache.spark.api.java.JavaRDDLike$class.first(JavaRDDLike.scala:477)
at org.apache.spark.api.java.JavaRDD.first(JavaRDD.scala:32)
at com.cignifi.DataExplorationValidation.processFile(DataExplorationValidation.java:148)
at com.cignifi.DataExplorationValidation.main(DataExplorationValidation.java:104)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:606)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:569)
at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:166)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:189)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:110)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Caused by: java.net.URISyntaxException: Expected scheme-specific part at index 3: s3:
at java.net.URI$Parser.fail(URI.java:2829)
at java.net.URI$Parser.failExpecting(URI.java:2835)
at java.net.URI$Parser.parse(URI.java:3038)
at java.net.URI.<init>(URI.java:753)
at org.apache.hadoop.fs.Path.initialize(Path.java:145)
... 36 more
Some more details
Spark version 1.3.0.
Running in local mode using spark-submit.
I tried this thing on local and EC2 instance ,In both case I'm getting same error.
It should be s3n:// instead of s3://
See External Datasets in Spark Programming Guide