I am getting this error which executing any query on hive which involves mapreduce.
“ Unable to retrieve URL for Hadoop Task logs. Does not contain a valid host:port authority: local”
The reported Exceptions is seen in older versions of Hadoop (i.e. before YARN). Mostly you are using older versions of Hadoop.
The exception is seen when value of mapred.job.tracker parameter is set to "local" in mapred-site.xml instead it should be <IP address of job tracker>:<port>.
Related
I'm using Nifi 1.6.0.
I'm trying to write to HDFS and to Hive (cloudera) with nifi.
On "PutHDFS" I'm configure the "Hadoop Confiugration Resources" with hdfs-site.xml, core-site.xml files, set the directories and when I'm trying to Start it I got the following error:
"Failed to properly initialize processor, If still shcedule to run,
NIFI will attempt to initalize and run the Processor again after the
'Administrative Yield Duration' has elapsed. Failure is due to
java.lang.reflect.InvocationTargetException:
java.lang.reflect.InvicationTargetException"
On "PutHiveStreaming" I'm configure the "Hive Metastore URI" with
thrift://..., the database and the table name and on "Hadoop
Confiugration Resources" I'm put the Hive-site.xml location and when
I'm trying to Start it I got the following error:
"Hive streaming connect/write error, flow file will be penalized and routed to retry.
org.apache.nifi.util.hive.HiveWritter$ConnectFailure: Failed connectiong to EndPoint {metaStoreUri='thrift://myserver:9083', database='mydbname', table='mytablename', partitionVals=[]}:".
How can I solve the errors?
Thanks.
For #1, if you got your *-site.xml files from the cluster, it's possible that they are using internal IPs to refer to components like the DataNodes and you won't be able to reach them directly using that. Try setting dfs.client.use.datanode.hostname to true in your hdfs-site.xml on the client.
For #2, I'm not sure PutHiveStreaming will work against Cloudera, IIRC they use Hive 1.1.x and PutHiveStreaming is based on 1.2.x, so there may be some Thrift incompatibilities. If that doesn't seem to be the issue, make sure the client can connect to the metastore port (looks like 9083).
I am trying to do a simple data move from a mapr fs origin to a mapr fs destination (this is not my use case, just doing this simple movement for testing purposes). When trying to validate this pipeline, the error message I see in the staging area is:
HADOOPFS_11 - Cannot connect to the filesystem. Check if the Hadoop FS location: 'maprfs:///mapr/mycluster.cluster.local' is valid or not: 'java.io.IOException: Provided Subject must contain a KerberosPrincipal
Tyring different variations of the hadoop fs URI field (eg. mfs:///mapr/mycluster.cluster.local, maprfs:///mycluster.cluster.local) does not seem to help. Looking at the logs after trying to validate, I see
2018-01-04 10:28:56,686 mfs2mfs/mapr2sqlserver850bfbf0-6dc0-4002-8d44-b73e33fcf9b3 INFO Created source of type: com.streamsets.pipeline.stage.origin.maprfs.ClusterMapRFSSource#16978460 DClusterSourceOffsetCommitter *admin preview-pool-1-thread-3
2018-01-04 10:28:56,697 mfs2mfs/mapr2sqlserver850bfbf0-6dc0-4002-8d44-b73e33fcf9b3 INFO Error connecting to FileSystem: java.io.IOException: Provided Subject must contain a KerberosPrincipal ClusterHdfsSource *admin preview-pool-1-thread-3
java.io.IOException: Provided Subject must contain a KerberosPrincipal
....
2018-01-04 10:20:39,159 mfs2mfs/mapr2mapr850bfbf0-6dc0-4002-8d44-b73e33fcf9b3 INFO Authentication Config: ClusterHdfsSource *admin preview-pool-1-thread-3
2018-01-04 10:20:39,159 mfs2mfs/mapr2mapr850bfbf0-6dc0-4002-8d44-b73e33fcf9b3 ERROR Issues: Issue[instance='MapRFS_01' service='null' group='HADOOP_FS' config='null' message='HADOOPFS_11 - Cannot connect to the filesystem. Check if the Hadoop FS location: 'maprfs:///mapr/mycluster.cluster.local' is valid or not: 'java.io.IOException: Provided Subject must contain a KerberosPrincipal''] ClusterHdfsSource *admin preview-pool-1-thread-3
2018-01-04 10:20:39,169 mfs2mfs/mapr2mapr850bfbf0-6dc0-4002-8d44-b73e33fcf9b3 INFO Validation Error: Failed to configure or connect to the 'maprfs:///mapr/mycluster.cluster.local' Hadoop file system: java.io.IOException: Provided Subject must contain a KerberosPrincipal HdfsTargetConfigBean *admin 0 preview-pool-1-thread-3
java.io.IOException: Provided Subject must contain a KerberosPrincipal
....
However, to my knowledge, the system is not running Keberos, so this error message is a bit confusing for me. Uncommenting #export SDC_JAVA_OPTS="-Dmaprlogin.password.enabled=true ${SDC_JAVA_OPTS}" in the sdc environment variable file for native mapr authentication did not seem to help the problem (even when reinstalling and commenting this line before running the streamsets mapr setup script).
Does anyone have any idea what is happening and how to fix it? Thanks.
This answer was provided on the mapr community forums and worked for me (using mapr v6.0). Note that the instruction here differ from those currently provided by the streamsets documentation. Throughout these instructions, I was logged in as user root.
After installing streamsets (and the mapr prerequisites) as per the documentation...
Change the owner of the the streamsets $SDC_DIST or $SDC_HOME location to the mapr user (or whatever other user you plan to use for the hadoop impersonation): $chown -R mapr:mapr $SDC_DIST (for me this was the /opt/streamsets-datacollector dir.). Do the same for $SDC_CONF (/etc/sdc for me) as well as /var/lib/sdc and var/log/sdc.
In $SDC_DIST/libexec/sdcd-env.sh, set the user and group name (near the top of the file) to mapr user "mapr" and enable mapr password login. The file should end up looking like:
# user that will run the data collector, it must exist in the system
#
export SDC_USER=mapr
# group of the user that will run the data collector, it must exist in the system
#
export SDC_GROUP=mapr
....
# Indicate that MapR Username/Password security is enabled
export SDC_JAVA_OPTS="-Dmaprlogin.password.enabled=true ${SDC_JAVA_OPTS}
Edit the file /usr/lib/systemd/system/sdc.service to look like:
[Service]
User=mapr
Group=mapr
$cd into /etc/systemd/system/ and create a directory called sdc.service.d. Within that directory, create a file (with any name) and add the contents (without spaces):
Environment=SDC_JAVA_OPTS=-Dmaprlogin.passowrd.enabled=true
If you are using mapr's sasl ticket auth. system (or something similar), generate a ticket for the this user on the node that is running streamsets. In this case, with the $maprlogin password command.
Then finally, restart the sdc service: $systemctl deamon-reload then $systemctl retart sdc.
Run something like $ps -aux | grep sdc | grep maprlogin to check that the sdc process is ownned by mapr and that the -Dmaprlogin.passowrd.enabled=true parameter has been successfully set. Once this is done, should be able to validate/run maprFS to maprFS operations in streamsets pipeline builder in batch processing mode.
** NOTE: If using Hadoop Configuration Directory param. instead of Hadoop FS URI, remember to have the files in your $HADOOP_HOME/conf directory (eg.hadoop-site.xml, yarn-site.xml, etc.) (in the case of mapr, something like /opt/mapr/hadoop/hadoop-<version>/etc/hadoop/) either soft-linked or hard-copied to a directory $SDC_DIST/resource/<some hadoop config dir. you made need to create> (I just copy eberything in the directory) and add this path to the Hadoop Configuration Directory param. for your MaprFS (or HadoopFS). In the sdc web UI Hadoop Configuration Directory box, it would look like Hadoop Configuration Directory: <the directory within $SDC_DIST/resources/ that holds the hadoop files>.
** NOTE: If you are still logging errors of the form
2018-01-16 14:26:10,883
ingest2sa_demodata_batch/ingest2sademodatabatchadca8442-cb00-4a0e-929b-df2babe4fd41
ERROR Error in Slave Runner: ClusterRunner *admin
runner-pool-2-thread-29
com.streamsets.datacollector.runner.PipelineRuntimeException:
CONTAINER_0800 - Pipeline
'ingest2sademodatabatchadca8442-cb00-4a0e-929b-df2babe4fd41'
validation error : HADOOPFS_11 - Cannot connect to the filesystem.
Check if the Hadoop FS location: 'maprfs:///' is valid or not:
'java.io.IOException: Provided Subject must contain a
KerberosPrincipal'
you may also need to add -Dmaprlogin.password.enabled=true to the pipeline's /cluster/Worker Java Options tab for the origin and destination hadoop FS stages.
** The video linked to in the mapr community link also says to generate a mapr ticket for the sdc user (the default user that sdc process runs as when running as a service), but I did not do this and the solution still worked for me (so if anyone has any idea why it should be done regardless, please let me know in the comments).
CDH Version: CDH5.4.5
Issue: When HDFS Encryption is enabled using KMS available in Hadoop CDH 5.4 , getting error while putting file into encryption zone.
Steps:
Steps for Encryption of Hadoop as follows:
Creating a key [SUCCESS]
[tester#master ~]$ hadoop key create 'TDEHDP'
-provider kms://https#10.1.118.1/key_generator/kms -size 128
tde group has been successfully created with options
Options{cipher='AES/CTR/NoPadding', bitLength=128, description='null', attributes=null}.
KMSClientProvider[https://10.1.118.1/key_generator/kms/v1/] has been updated.
2.Creating a directory [SUCCESS]
[tester#master ~]$ hdfs dfs -mkdir /user/tester/vs_key_testdir
Adding Encryption Zone [SUCCESS]
[tester#master ~]$ hdfs crypto -createZone -keyName 'TDEHDP'
-path /user/tester/vs_key_testdir
Added encryption zone /user/tester/vs_key_testdir
Copying File to encryption Zone [ERROR]
[tdetester#master ~]$ hdfs dfs -copyFromLocal test.txt /user/tester/vs_key_testdir
15/09/04 06:06:33 ERROR hdfs.KeyProviderCache: Could not find uri with
key [dfs.encryption.key.provider.uri] to create a keyProvider !!
copyFromLocal: No KeyProvider is configured, cannot access an
encrypted file 15/09/04 06:06:33 ERROR hdfs.DFSClient: Failed to close
inode 20823
org.apache.hadoop.ipc.RemoteException(org.apache.hadoop.hdfs.server.namenode.LeaseExpiredException):
No lease on /user/tester/vs_key_testdir/test.txt.COPYING (inode
20823): File does not exist. Holder
DFSClient_NONMAPREDUCE_1061684229_1 does not have any open files.
Any idea/suggestion will be helpful.
This issue was crossposted here: https://community.cloudera.com/t5/Storage-Random-Access-HDFS/Could-not-find-uri-with-key-dfs-encryption-key-provider-uri-to/td-p/31637
Main conclusion: It is a non-issue
Here is the answer that was provided by the support staff:
CDH's base release versions are just that: base. The fix for the
harmless log print due to HDFS-7931 is present in all CDH5 releases
since CDH 5.4.1.
If you see that error in context of having configured a KMS, then its
a worthy one to consider. If you do not use KMS or EZs, then the error
may be ignored. Alternatively upgrade to the latest CDH5 (5.4.x or
5.5.x) releases to receive a bug fix that makes the error only appear when in the context of a KMS being configured over an encrypted path.
Per your log snippet, I don't see a problem (the canary does not
appear to be failing?). If you're trying to report a failure, please
send us more characteristics of the failure, as HDFS-7931 is a minor
issue with an unnecessary log print.
My Pig script works fine on its own, until I put it in an Oozie workflow, where I receive the following error:
ERROR 2043: Unexpected error during execution.
org.apache.pig.backend.executionengine.ExecException: ERROR 2043: Unexpected error during execution.
...
Caused by: java.io.IOException: No FileSystem for scheme: hbase
I registered the HBase and Zookeeper jars successfully, but received the same error.
I also attempted to set the Zookeeper Quorum by adding variation of these lines in the Pig script:
SET hbase.zookeeper.quorum 'vm-myhost-001,vm-myhost-002,vm-myhost-003'
Some searching on the internet instructed me to add this to the beginning of my workflow.xml:
SET mapreduce.fileoutputcommitter.marksuccessfuljobs false
This solved the problem. I was even able to remove the registration of the HBase and Zookeeper jars and the Zookeeper quorum.
Now after double checking, I noticed that my jobs actually do their job: they store the results in HBase as expected. But, Oozie claims that a failure occurred, when it didn't.
I don't think that setting the mapreduce.fileoutputcommitter.marksuccessfuljobs to false constitutes a solution.
Are there any other solutions?
It seems that there is currently no real solution for this.
However, this answer to a different question seems to indicate that the best workaround is to create the success flag 'manually'.
I am successfully using the DataStax Java Driver to access Cassandra inside my Java code just before I start a MapReduce Job.
cluster = Cluster.builder().addContactPoint("127.0.0.1").build();
However I am needing to check additional information to decide on a per record basis how to reduce the record. If I attempt to use the same code inside a Hadoop Reducer class it fails to connect with the error:
INFO mapred.JobClient: Task Id :
attempt_201310280851_0012_r_000000_1, Status : FAILED
com.datastax.driver.core.exceptions.NoHostAvailableException:
All host(s) tried for query failed (tried: /127.0.0.1 ([/127.0.0.1]
Unexpected error during transport initialization
(com.datastax.driver.core.TransportException: [/127.0.0.1] Error writing)))
at com.datastax.driver.core.ControlConnection.reconnectInternal(ControlConnection.java:186)
at com.datastax.driver.core.ControlConnection.connect(ControlConnection.java:81)
at com.datastax.driver.core.Cluster$Manager.init(Cluster.java:662)
at com.datastax.driver.core.Cluster$Manager.access$100(Cluster.java:604)
at com.datastax.driver.core.Cluster.<init>(Cluster.java:69)
at com.datastax.driver.core.Cluster.buildFrom(Cluster.java:96)
at com.datastax.driver.core.Cluster$Builder.build(Cluster.java:585)
The MapReduce input and output will successfully read and write to Cassandra. As I mentioned I can connect before I run the job so I do not think it is an issue with the Cassandra server.