at org.apache.hadoop.hdfs.server.datanode.DataNode.main(DataNode.java:2924)
Caused by: com.ctc.wstx.exc.WstxParsingException: Unexpected close tag </name>; expected </nafme>.
at [row,col,system-id]: [39,40,"file:/opt/module/hadoop-3.1.3/etc/hadoop/mapred-site.xml"]
at com.ctc.wstx.sr.StreamScanner.constructWfcException(StreamScanner.java:621)
at com.ctc.wstx.sr.StreamScanner.throwParseError(StreamScanner.java:491)
at com.ctc.wstx.sr.StreamScanner.throwParseError(StreamScanner.java:475)
at com.ctc.wstx.sr.BasicStreamReader.reportWrongEndElem(BasicStreamReader.java:3365)
at com.ctc.wstx.sr.BasicStreamReader.readEndElem(BasicStreamReader.java:3292)
at com.ctc.wstx.sr.BasicStreamReader.nextFromTree(BasicStreamReader.java:2911)
at com.ctc.wstx.sr.BasicStreamReader.next(BasicStreamReader.java:1123)
at org.apache.hadoop.conf.Configuration$Parser.parseNext(Configuration.java:3320)
at org.apache.hadoop.conf.Configuration$Parser.parse(Configuration.java:3114)
at org.apache.hadoop.conf.Configuration.loadResource(Configuration.java:3007)
... 14 more
2022-12-02 13:21:18,536 INFO org.apache.hadoop.util.ExitUtil: Exiting with status 1: java.lang.RuntimeException: com.ctc.wstx.exc.WstxParsingException: Unexpected close tag </name>; expected </nafme>.
at [row,col,system-id]: [39,40,"file:/opt/module/hadoop-3.1.3/etc/hadoop/mapred-site.xml"]
2022-12-02 13:21:18,551 INFO org.apache.hadoop.hdfs.server.datanode.DataNode: SHUTDOWN_MSG:
/************************************************************
SHUTDOWN_MSG: Shutting down DataNode at hadoop162/192.168.10.162
************************************************************/
2022-12-02 13:21:18,597 ERROR org.apache.hadoop.conf.Configuration: error parsing conf mapred-site.xml
com.ctc.wstx.exc.WstxParsingException: Unexpected close tag </name>; expected </nafme>.
at [row,col,system-id]: [39,40,"file:/opt/module/hadoop-3.1.3/etc/hadoop/mapred-site.xml"]
at com.ctc.wstx.sr.StreamScanner.constructWfcException(StreamScanner.java:621)
at com.ctc.wstx.sr.StreamScanner.throwParseError(StreamScanner.java:491)
at com.ctc.wstx.sr.StreamScanner.throwParseError(StreamScanner.java:475)
at com.ctc.wstx.sr.BasicStreamReader.reportWrongEndElem(BasicStreamReader.java:3365)
at com.ctc.wstx.sr.BasicStreamReader.readEndElem(BasicStreamReader.java:3292)
at com.ctc.wstx.sr.BasicStreamReader.nextFromTree(BasicStreamReader.java:2911)
at com.ctc.wstx.sr.BasicStreamReader.next(BasicStreamReader.java:1123)
at org.apache.hadoop.conf.Configuration$Parser.parseNext(Configuration.java:3320)
at org.apache.hadoop.conf.Configuration$Parser.parse(Configuration.java:3114)
at org.apache.hadoop.conf.Configuration.loadResource(Configuration.java:3007)
at org.apache.hadoop.conf.Configuration.loadResources(Configuration.java:2968)
at org.apache.hadoop.conf.Configuration.getProps(Configuration.java:2848)
at org.apache.hadoop.conf.Configuration.get(Configuration.java:1200)
at org.apache.hadoop.conf.Configuration.getTimeDuration(Configuration.java:1812)
at org.apache.hadoop.conf.Configuration.getTimeDuration(Configuration.java:1789)
at org.apache.hadoop.util.ShutdownHookManager.getShutdownTimeout(ShutdownHookManager.java:183)
at org.apache.hadoop.util.ShutdownHookManager.shutdownExecutor(ShutdownHookManager.java:145)
at org.apache.hadoop.util.ShutdownHookManager.access$300(ShutdownHookManager.java:65)
at org.apache.hadoop.util.ShutdownHookManager$1.run(ShutdownHookManager.java:102)
/opt/module/hadoop-3.1.3/logs » xcall atguigu#hadoop162
========== hadoop162 =========
3642 Jps
========== hadoop163 =========
3047 NodeManager
2603 DataNode
2893 ResourceManager
3503 Jps
========== hadoop164 =========
1191 DataNode
1368 NodeManager
1597 Jps
/opt/module/hadoop-3.1.3/logs » atguigu#hadoop162
enter image description here
there is an exception ,I can't start hadoop ,
022-12-02 13:21:18,597 ERROR org.apache.hadoop.conf.Configuration: error parsing conf mapred-site.xml
com.ctc.wstx.exc.WstxParsingException: Unexpected close tag </name>; expected </nafme>.
at [row,col,system-id]: [39,40,"file:/opt/module/hadoop-3.1.3/etc/hadoop/mapred-site.xml"]
As the error says, you have mismatched XML tags.
nafme isn't a valid property tag
I Installed HDFP 3.0.1 in Vmware.
DataNode and NameNode are running
I upload files from AmbariUI/Terminal to HDFS, Everything works.
When I try to write the data:
Configuration conf = new Configuration();
conf.set("fs.defaultFS", "hdfs://172.16.68.131:8020");
FileSystem fs = FileSystem.get(conf);
OutputStream os = fs.create(new Path("hdfs://172.16.68.131:8020/tmp/write.txt"));
InputStream is = new BufferedInputStream(new FileInputStream("/home/vq/hadoop/test.txt"));
IOUtils.copyBytes(is, os, conf);
log:
19/07/15 22:40:31 WARN hdfs.DataStreamer: Abandoning BP-1419118625-172.17.0.2-1543512323726:blk_1073760904_20134
19/07/15 22:40:31 WARN hdfs.DataStreamer: Excluding datanode DatanodeInfoWithStorage[172.18.0.2:50010,DS-6c34ba72-0587-4927-88a1-781ba7d444d9,DISK]
19/07/15 22:40:32 WARN hdfs.DataStreamer: DataStreamer Exception
org.apache.hadoop.ipc.RemoteException(java.io.IOException): File /tmp/write.txt could only be written to 0 of the 1 minReplication nodes. There are 1 datanode(s) running and 1 node(s) are excluded in this operationa .
It creates file in HDFS but it's empty.
The same is when I read the data:
Configuration conf = new Configuration();
conf.set("fs.defaultFS", "hdfs://172.16.68.131:8020");
FileSystem fs = FileSystem.get(conf);
FSDataInputStream inputStream = fs.open(new Path("hdfs://172.16.68.131:8020/tmp/ui.txt"));
System.out.println(inputStream.available());
byte[] bs = new byte[inputStream.available()];
I can read available bytes. but can't read the file.
log:
19/07/15 22:33:33 WARN hdfs.DFSClient: Failed to connect to /172.18.0.2:50010 for file /tmp/ui.txt for block BP-1419118625-172.17.0.2-1543512323726:blk_1073760902_20132, add to deadNodes and continue.
org.apache.hadoop.net.ConnectTimeoutException: 60000 millis timeout while waiting for channel to be ready for connect. ch : java.nio.channels.SocketChannel[connection-pending remote=/172.18.0.2:50010]
19/07/15 22:33:33 WARN hdfs.DFSClient: No live nodes contain block BP-1419118625-172.17.0.2-1543512323726:blk_1073760902_20132 after checking nodes = [DatanodeInfoWithStorage[172.18.0.2:50010,DS-6c34ba72-0587-4927-88a1-781ba7d444d9,DISK]], ignoredNodes = null
19/07/15 22:33:33 INFO hdfs.DFSClient: Could not obtain BP-1419118625-172.17.0.2-1543512323726:blk_1073760902_20132 from any node: No live nodes contain current block Block locations: DatanodeInfoWithStorage[172.18.0.2:50010,DS-6c34ba72-0587-4927-88a1-781ba7d444d9,DISK] Dead nodes: DatanodeInfoWithStorage[172.18.0.2:50010,DS-6c34ba72-0587-4927-88a1-781ba7d444d9,DISK]. Will get new block locations from namenode and retry...
19/07/15 22:33:33 WARN hdfs.DFSClient: DFS chooseDataNode: got # 3 IOException, will wait for 6717.521796266041 msec
I've seen many answers on the internet but no success.
My Spark application is failing when it has to access numerous CSV files (~1000 # 63MB each) from S3, and pipe them into a Spark RDD. The actual process of splitting up the CSV seems to work, but an extra function call to S3NativeFileSystem seems to be causing an error and the job to crash.
To begin, the following is my PySpark Application:
from pyspark import SparkContext
sc = SparkContext("local", "Simple App")
from pyspark.sql import SQLContext
sqlContext = SQLContext(sc)
import time
startTime = float(time.time())
dataPath = 's3://PATHTODIRECTORY/'
sc._jsc.hadoopConfiguration().set("fs.s3.awsAccessKeyId", "MYKEY")
sc._jsc.hadoopConfiguration().set("fs.s3.awsSecretAccessKey", "MYSECRETKEY")
def buildSchemaDF(tableName, columnList):
currentRDD = sc.textFile(dataPath + tableName).map(lambda line: line.split("|"))
currentDF = currentRDD.toDF(columnList)
return currentDF
loadStartTime = float(time.time())
lineitemDF = buildSchemaDF('lineitem*', ['l_orderkey','l_partkey','l_suppkey','l_linenumber','l_quantity','l_extendedprice','l_discount','l_tax','l_returnflag','l_linestatus','l_shipdate','l_commitdate','l_receiptdate','l_shipinstruct','l_shipmode','l_comment'])
lineitemDF.registerTempTable("lineitem")
loadTimeElapsed = float(time.time()) - loadStartTime
queryStartTime = float(time.time())
qstr = """
SELECT
lineitem.l_returnflag,
lineitem.l_linestatus,
sum(l_quantity) as sum_qty,
sum(l_extendedprice) as sum_base_price,
sum(l_discount) as sum_disc,
sum(l_tax) as sum_tax,
avg(l_quantity) as avg_qty,
avg(l_extendedprice) as avg_price,
avg(l_discount) as avg_disc,
count(l_orderkey) as count_order
FROM
lineitem
WHERE
l_shipdate <= '19981001'
GROUP BY
l_returnflag,
l_linestatus
ORDER BY
l_returnflag,
l_linestatus
"""
tpch1DF = sqlContext.sql(qstr)
queryTimeElapsed = float(time.time()) - queryStartTime
totalTimeElapsed = float(time.time()) - startTime
tpch1DF.show()
queryResults = [qstr, loadTimeElapsed, queryTimeElapsed, totalTimeElapsed]
distData = sc.parallelize(queryResults)
distData.saveAsTextFile(dataPath + 'queryResults.csv')
print 'Load Time: ' + str(loadTimeElapsed)
print 'Query Time: ' + str(queryTimeElapsed)
print 'Total Time: ' + str(totalTimeElapsed)
To take it step by step I start off by spinning up a Spark EMR Cluster with the following AWS CLI command (carriage returns added for readability):
aws emr create-cluster --name "Big TPCH Spark cluster2" --release-label emr-4.6.0
--applications Name=Spark --ec2-attributes KeyName=blazing-test-aws
--log-uri s3://aws-logs-132950491118-us-west-2/elasticmapreduce/j-1WZ39GFS3IX49/
--instance-type m3.2xlarge --instance-count 6 --use-default-roles
After the EMR cluster finishes provisioning I then copy over my Pyspark application onto the master node at '/home/hadoop/pysparkApp.py'. With it copied over I'm able to add the Step for spark-submit.
aws emr add-steps --cluster-id j-1DQJ8BDL1394N --steps
Type=spark,Name=SparkTPCHTests,Args=[--deploy-mode,cluster,-
conf,spark.yarn.submit.waitAppCompletion=true,--num-executors,5,--executor
cores,5,--executor memory,20g,/home/hadoop/tpchSpark.py]
,ActionOnFailure=CONTINUE
Now if I run this step over only a few of the aforementioned CSV files the final results will be generated, but the script will still claim to have failed.
I think it's associated with an extra call to S3NativeFileSystem, but I'm not certain. These are the Yarn log messages I'm getting which lead me to that conclusion. The first call appears to work just fine:
16/05/15 23:18:00 INFO HadoopRDD: Input split: s3://data-set-builder/splitLineItem2/lineitemad:0+64901757
16/05/15 23:18:00 INFO latency: StatusCode=[200], ServiceName=[Amazon S3], AWSRequestID=[ED8011CE4E1F6F18], ServiceEndpoint=[https://data-set-builder.s3-us-west-2.amazonaws.com], HttpClientPoolLeasedCount=0, RetryCapacityConsumed=0, RequestCount=1, HttpClientPoolPendingCount=0, HttpClientPoolAvailableCount=2, ClientExecuteTime=[77.956], HttpRequestTime=[77.183], HttpClientReceiveResponseTime=[20.028], RequestSigningTime=[0.229], CredentialsRequestTime=[0.003], ResponseProcessingTime=[0.128], HttpClientSendRequestTime=[0.35],
While the second one does not seem to execute properly, resulting in "Partial Results" (206 Error):
16/05/15 23:18:00 INFO S3NativeFileSystem: Opening 's3://data-set-builder/splitLineItem2/lineitemad' for reading
16/05/15 23:18:00 INFO latency: StatusCode=[206], ServiceName=[Amazon S3], AWSRequestID=[10BDDE61AE13AFBE], ServiceEndpoint=[https://data-set-builder.s3.amazonaws.com], HttpClientPoolLeasedCount=0, RetryCapacityConsumed=0, RequestCount=1, HttpClientPoolPendingCount=0, HttpClientPoolAvailableCount=2, Client Execute Time=[296.86], HttpRequestTime=[295.801], HttpClientReceiveResponseTime=[293.667], RequestSigningTime=[0.204], CredentialsRequestTime=[0.002], ResponseProcessingTime=[0.34], HttpClientSendRequestTime=[0.337],
16/05/15 23:18:02 INFO ApplicationMaster: Waiting for spark context initialization ...
I'm lost as to why it's even making the second call to S3NativeFileSystem when the first one appears to have responded effectively and even split the file. Is this something that is a product of my EMR configuration? I know S3Native has file limit issues and that a straight S3 call is optimal, which is what I've tried to do, but this call seems to be there no matter what I do. Please help!
Also, to add a few other error messages in my Yarn Log in case they are relevant.
1)
16/05/15 23:19:22 ERROR ApplicationMaster: SparkContext did not initialize after waiting for 100000 ms. Please check earlier log output for errors. Failing the application.
16/05/15 23:19:22 INFO ApplicationMaster: Final app status: FAILED, exitCode: 13, (reason: Timed out waiting for SparkContext.)
2)
16/05/15 23:19:22 ERROR DiskBlockObjectWriter: Uncaught exception while reverting partial writes to file /mnt/yarn/usercache/hadoop/appcache/application_1463354019776_0001/blockmgr-f847744b-c87a-442c-9135-57cae3d1f6f0/2b/temp_shuffle_3fe2e09e-f8e4-4e5d-ac96-1538bdc3b401
java.io.FileNotFoundException: /mnt/yarn/usercache/hadoop/appcache/application_1463354019776_0001/blockmgr-f847744b-c87a-442c-9135-57cae3d1f6f0/2b/temp_shuffle_3fe2e09e-f8e4-4e5d-ac96-1538bdc3b401 (No such file or directory)
at java.io.FileOutputStream.open(Native Method)
at java.io.FileOutputStream.<init>(FileOutputStream.java:221)
at org.apache.spark.storage.DiskBlockObjectWriter.revertPartialWritesAndClose(DiskBlockObjectWriter.scala:162)
at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.stop(BypassMergeSortShuffleWriter.java:226)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:79)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
16/05/15 23:19:22 ERROR BypassMergeSortShuffleWriter: Error while deleting file /mnt/yarn/usercache/hadoop/appcache/application_1463354019776_0001/blockmgr-f847744b-c87a-442c-9135-57cae3d1f6f0/2b/temp_shuffle_3fe2e09e-f8e4-4e5d-ac96-1538bdc3b401
16/05/15 23:19:22 WARN TaskMemoryManager: leak 32.3 MB memory from org.apache.spark.unsafe.map.BytesToBytesMap#762be8fe
16/05/15 23:19:22 ERROR Executor: Managed memory leak detected; size = 33816576 bytes, TID = 14
16/05/15 23:19:22 ERROR Executor: Exception in task 13.0 in stage 1.0 (TID 14)
java.io.FileNotFoundException: /mnt/yarn/usercache/hadoop/appcache/application_1463354019776_0001/blockmgr-f847744b-c87a-442c-9135-57cae3d1f6f0/3a/temp_shuffle_b9001fca-bba9-400d-9bc4-c23c002e0aa9 (No such file or directory)
at java.io.FileOutputStream.open(Native Method)
at java.io.FileOutputStream.<init>(FileOutputStream.java:221)
at org.apache.spark.storage.DiskBlockObjectWriter.open(DiskBlockObjectWriter.scala:88)
at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:140)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
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)
Order of precedence for spark configurations is :
SparkContext (code/application) > Spark-submit > Spark-defaults.conf
So couple of things to point here -
Use YARN cluster as deploy mode and master in your spark submit command -
spark-submit --deploy-mode cluster --master yarn ...
OR
spark-submit --master yarn-cluster ...
Remove "local" string from line sc = SparkContext("local", "Simple App") in your code. Use conf = SparkConf().setAppName(appName)
sc = SparkContext(conf=conf) to initialize Spark context.
Ref - http://spark.apache.org/docs/latest/programming-guide.html
I have an external table in hive that is stored on my hadoop cluster and I want to move its contents into an external table that is stored on Amazon s3.
So I created an s3 backed table like so:
CREATE EXTERNAL TABLE IF NOT EXISTS export.export_table
like table_to_be_exported
ROW FORMAT SERDE ...
with SERDEPROPERTIES ('fieldDelimiter'='|')
STORED AS TEXTFILE
LOCATION 's3a://bucket/folder';
Then I run: INSERT INTO export.export_table SELECT * FROM table_to_be_exported
It outputs the following
INFO : Number of reduce tasks is set to 0 since there's no reduce operator
WARN : Hadoop command-line option parsing not performed. Implement the Tool interface and execute your application with ToolRunner to remedy this.
INFO : Starting Job = job_1435176004514_0028, Tracking URL = http://quickstart.cloudera:8088/proxy/application_1435176004514_0028/
INFO : Kill Command = /usr/lib/hadoop/bin/hadoop job -kill job_1435176004514_0028
INFO : Hadoop job information for Stage-1: number of mappers: 1; number of reducers: 0
INFO : 2015-07-06 09:22:18,379 Stage-1 map = 0%, reduce = 0%
INFO : 2015-07-06 09:22:27,795 Stage-1 map = 100%, reduce = 0%, Cumulative CPU 2.9 sec
INFO : MapReduce Total cumulative CPU time: 2 seconds 900 msec
INFO : Ended Job = job_1435176004514_0028
INFO : Stage-4 is selected by condition resolver.
INFO : Stage-3 is filtered out by condition resolver.
INFO : Stage-5 is filtered out by condition resolver.
INFO : Moving data to: s3a://bucket/folder/.hive-staging_hive_2015-07-06_09-22-10_351_9216807769834089982-3/-ext-10000 from s3a://bucket/folder/.hive-staging_hive_2015-07-06_09-22-10_351_9216807769834089982-3/-ext-10002
ERROR : Failed with exception Wrong FS: s3a://bucket/folder/.hive-staging_hive_2015-07-06_09-22-10_351_9216807769834089982-3/-ext-10002, expected: hdfs://quickstart.cloudera:8020
java.lang.IllegalArgumentException: Wrong FS: s3a://bucket/folder/.hive-staging_hive_2015-07-06_09-22-10_351_9216807769834089982-3/-ext-10002, expected: hdfs://quickstart.cloudera:8020
at org.apache.hadoop.fs.FileSystem.checkPath(FileSystem.java:645)
at org.apache.hadoop.hdfs.DistributedFileSystem.getPathName(DistributedFileSystem.java:193)
at org.apache.hadoop.hdfs.DistributedFileSystem.getEZForPath(DistributedFileSystem.java:1916)
at org.apache.hadoop.hdfs.client.HdfsAdmin.getEncryptionZoneForPath(HdfsAdmin.java:262)
at org.apache.hadoop.hive.shims.Hadoop23Shims$HdfsEncryptionShim.isPathEncrypted(Hadoop23Shims.java:1187)
at org.apache.hadoop.hive.ql.metadata.Hive.moveFile(Hive.java:2449)
at org.apache.hadoop.hive.ql.exec.MoveTask.moveFile(MoveTask.java:105)
at org.apache.hadoop.hive.ql.exec.MoveTask.execute(MoveTask.java:222)
at org.apache.hadoop.hive.ql.exec.Task.executeTask(Task.java:160)
at org.apache.hadoop.hive.ql.exec.TaskRunner.runSequential(TaskRunner.java:88)
at org.apache.hadoop.hive.ql.Driver.launchTask(Driver.java:1638)
at org.apache.hadoop.hive.ql.Driver.execute(Driver.java:1397)
at org.apache.hadoop.hive.ql.Driver.runInternal(Driver.java:1181)
at org.apache.hadoop.hive.ql.Driver.run(Driver.java:1047)
at org.apache.hadoop.hive.ql.Driver.run(Driver.java:1042)
at org.apache.hive.service.cli.operation.SQLOperation.runQuery(SQLOperation.java:145)
at org.apache.hive.service.cli.operation.SQLOperation.access$100(SQLOperation.java:70)
at org.apache.hive.service.cli.operation.SQLOperation$1$1.run(SQLOperation.java:197)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:415)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1671)
at org.apache.hive.service.cli.operation.SQLOperation$1.run(SQLOperation.java:209)
at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:471)
at java.util.concurrent.FutureTask.run(FutureTask.java:262)
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)
Error: Error while processing statement: FAILED: Execution Error, return code 1 from org.apache.hadoop.hive.ql.exec.MoveTask (state=08S01,code=1)
I have s3a key and secret set in my hadoop core-site.xml and am able to do reads and writes from s3 using hadoop directly hdfs dfs -ls s3a://.
Any guesses as to what I could do to get this to work?
Try using s3 instead of s3a, my guess is that s3a is not supported yet in EMR's Hive distribution.
Im using flume to move files to hdfs ... while moving file its showing this error.. please help me to solve this issue.
15/05/20 15:49:26 INFO instrumentation.MonitoredCounterGroup: Component type: SOURCE, name: r1 started
15/05/20 15:49:26 INFO avro.ReliableSpoolingFileEventReader: Preparing to move file /home/crayondata.com/shanmugapriya/apache-flume-1.5.2-bin/staging/HypeVisitorTest.java to /home/crayondata.com/shanmugapriya/apache-flume-1.5.2-bin/staging/HypeVisitorTest.java.COMPLETED
15/05/20 15:49:26 INFO source.SpoolDirectorySource: Spooling Directory Source runner has shutdown.
15/05/20 15:49:26 INFO hdfs.HDFSDataStream: Serializer = TEXT, UseRawLocalFileSystem = false
15/05/20 15:49:26 INFO hdfs.BucketWriter: Creating hdfs://localhost:9000/sha/HypeVisitorTest.java.1432117166377.tmp
15/05/20 15:49:26 ERROR hdfs.HDFSEventSink: process failed
java.lang.UnsupportedOperationException: Not implemented by the DistributedFileSystem FileSystem implementation
at org.apache.hadoop.fs.FileSystem.getScheme(FileSystem.java:216)
at org.apache.hadoop.fs.FileSystem.loadFileSystems(FileSystem.java:2564)
at org.apache.hadoop.fs.FileSystem.getFileSystemClass(FileSystem.java:2574)
at org.apache.hadoop.fs.FileSystem.createFileSystem(FileSystem.java:2591)
at org.apache.hadoop.fs.FileSystem.access$200(FileSystem.java:91)
at org.apache.hadoop.fs.FileSystem$Cache.getInternal(FileSystem.java:2630)
at org.apache.hadoop.fs.FileSystem$Cache.get(FileSystem.java:2612)
at org.apache.hadoop.fs.FileSystem.get(FileSystem.java:370)
at org.apache.hadoop.fs.Path.getFileSystem(Path.java:296)
at org.apache.flume.sink.hdfs.BucketWriter$1.call(BucketWriter.java:270)
at org.apache.flume.sink.hdfs.BucketWriter$1.call(BucketWriter.java:262)
at org.apache.flume.sink.hdfs.BucketWriter$9$1.run(BucketWriter.java:718)
at org.apache.flume.sink.hdfs.BucketWriter.runPrivileged(BucketWriter.java:183)
at org.apache.flume.sink.hdfs.BucketWriter.access$1700(BucketWriter.java:59)
at org.apache.flume.sink.hdfs.BucketWriter$9.call(BucketWriter.java:715)
at java.util.concurrent.FutureTask.run(FutureTask.java:262)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
15/05/20 15:49:26 ERROR flume.SinkRunner: Unable to deliver event. Exception follows.
org.apache.flume.EventDeliveryException: java.lang.UnsupportedOperationException: Not implemented by the DistributedFileSystem FileSystem implementation
at org.apache.flume.sink.hdfs.HDFSEventSink.process(HDFSEventSink.java:471)
at org.apache.flume.sink.DefaultSinkProcessor.process(DefaultSinkProcessor.java:68)
at org.apache.flume.SinkRunner$PollingRunner.run(SinkRunner.java:147)
at java.lang.Thread.run(Thread.java:745)
Caused by: java.lang.UnsupportedOperationException: Not implemented by the DistributedFileSystem FileSystem implementation
at org.apache.hadoop.fs.FileSystem.getScheme(FileSystem.java:216)
at org.apache.hadoop.fs.FileSystem.loadFileSystems(FileSystem.java:2564)
at org.apache.hadoop.fs.FileSystem.getFileSystemClass(FileSystem.java:2574)
at org.apache.hadoop.fs.FileSystem.createFileSystem(FileSystem.java:2591)
at org.apache.hadoop.fs.FileSystem.access$200(FileSystem.java:91)
at org.apache.hadoop.fs.FileSystem$Cache.getInternal(FileSystem.java:2630)
at org.apache.hadoop.fs.FileSystem$Cache.get(FileSystem.java:2612)
at org.apache.hadoop.fs.FileSystem.get(FileSystem.java:370)
at org.apache.hadoop.fs.Path.getFileSystem(Path.java:296)
at org.apache.flume.sink.hdfs.BucketWriter$1.call(BucketWriter.java:270)
at org.apache.flume.sink.hdfs.BucketWriter$1.call(BucketWriter.java:262)
at org.apache.flume.sink.hdfs.BucketWriter$9$1.run(BucketWriter.java:718)
at org.apache.flume.sink.hdfs.BucketWriter.runPrivileged(BucketWriter.java:183)
at org.apache.flume.sink.hdfs.BucketWriter.access$1700(BucketWriter.java:59)
at org.apache.flume.sink.hdfs.BucketWriter$9.call(BucketWriter.java:715)
at java.util.concurrent.FutureTask.run(FutureTask.java:262)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
... 1 more
15/05/20 15:49:26 INFO source.SpoolDirectorySource: Spooling Directory Source runner has shutdown.
Here is my flumeconf.conf file
# example.conf: A single-node Flume configuration
# Name the components on this agent
a1.sources = r1
a1.sinks = k1
a1.channels = c1
# Describe/configure the source
a1.sources.r1.type = spooldir
a1.sources.r1.spoolDir = /home/shanmugapriya/apache-flume-1.5.2-bin/staging
a1.sources.r1.fileHeader = true
a1.sources.r1.maxBackoff = 10000
a1.sources.r1.basenameHeader = true
# Describe the sink
a1.sinks.k1.type = hdfs
a1.sinks.k1.hdfs.path = hdfs://localhost:9000/sha
a1.sinks.k1.hdfs.writeFormat = Text
a1.sinks.k1.hdfs.fileType = DataStream
a1.sinks.k1.hdfs.rollInterval = 0
a1.sinks.k1.hdfs.rollSize = 0
a1.sinks.k1.hdfs.rollCount = 0
a1.sinks.k1.hdfs.idleTimeout = 100
a1.sinks.k1.hdfs.filePrefix = %{basename}
# Use a channel which buffers events in memory
a1.channels.c1.type = memory
a1.channels.c1.capacity = 100000
a1.channels.c1.transactionCapacity = 1000
a1.channels.c1.byteCapacity = 0
# Bind the source and sink to the channel
a1.sources.r1.channels = c1
a1.sinks.k1.channel = c1
please help to solve this.. TIA...
#Shan Please confirm you have the relevant Hadoop HDFS jars in your classpath for Apache Flume
Also from your sink to HDFS I see that you have port 9000, however the default port is normally 8020, is this correct?