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04-25-2016
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609
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111
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My Accepted Solutions
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2677 | 07-19-2017 02:43 AM | |
1980 | 07-13-2017 11:42 AM |
10-09-2016
11:02 PM
@Fabien could you please try these steps to login ambari using admin open a terminal do ssh root@127.0.0.1 -p 2222 ambari-admin-password-reset // update admin passwd ambari-agent restart now open ambari ui and login using admin/<passwd you setted>
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09-21-2016
02:39 PM
3 Kudos
Env: HDP-2.3.4.0-3485 Java 8 Attached code contain: —pom.xml to manage all the dependencies — HiveClientSecure.java - oozie java action to be configured into workflow.xml — jaas.conf — oozie uses jaas configuration for kerberos login — log4j.properties - to capture logs jaas.conf: modify principal name and key tab location accordingly and place it to on each node on the cluster.I have placed it on /tmp/jaas/jaas.conf for testing purpose.
Client {
com.sun.security.auth.module.Krb5LoginModule required
useKeyTab=trueuseTicketCache=true
principal="ambari-qa-hbase234@HWXBLR.COM"
keyTab="/etc/security/keytabs/smokeuser.headless.keytab"debug="true"doNotPrompt=true;
}; workflow.xml: <workflow-app xmlns="uri:oozie:workflow:0.2" name="java-main-wf"> <start to="java-node"/> <a<action name="java-node">
<java>
<job-tracker>${jobTracker}</job-tracker>
<name-node>${nameNode}</name-node>
<configuration>
<property>
<name>mapred.job.queue.name</name>
<value>${queueName}</value>
</property> </configuration>
<main-class>HiveJdbcClientSecure</main-class>
<arg>jdbc:hive2://hb-n2.hwxblr.com:10000/;principal=hive/hb-n2.hwxblr.com@HWXBLR.COM</arg> <arg>ambari-qa-hbase234@HWXBLR.COM</arg>
<arg>/etc/security/keytabs/smokeuser.headless.keytab</arg> </java>
<ok to="end"/> <error to="fail"/> </action> <kill name="fail">
<message>Java failed, error message[${wf:errorMessage(wf:lastErrorNode())}]</message>
</kill>
<end name="end"/>
</workflow-app> Sample Application Build and Run Instruction. 1. extract attached jar 2. cd HiveServer2JDBCSample 3. mvn clean package(it will create a fat jar with all the dependencies into it.) 4. upload it to hdfs // in my case I am using amberi-qa user which is map to principal defined in workflow xml 5. hadoop fs -put target/HiveServer2JDBCTest-jar-with-dependencies.jar examples/apps/java-main/lib 6. upload workflow xml 7. hadoop fs -put /tmp/workflow.xml examples/apps/java-main/ Run Through oozie. source /etc/oozie/conf/oozie-env.sh ; /usr/hdp/current/oozie-client/bin/oozie job -oozie http://hb-n2.hwxblr.com:11000/oozie -config /usr/hdp/current/oozie-client/doc/examples/apps/java-main/job.properties -run hiveserver2oozieaction.tar.gz
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09-19-2016
05:20 PM
2 Kudos
@srinivasa rao I guess you read about when you perform a "select * from <tablename>", Hive fetches the whole data from file as a FetchTask rather than a mapreduce task which just dumps the data as it is without doing anything on it, similar to "hadoop dfs -text <filename>" However, the above does not take advantage of the true parallelism. In your case, for 1 GB will not make the difference, but image a 100 TB table and you do use a single threaded task in a cluster with 1000 nodes. FetchTask is not a good use of parallelism. Tez provides some options to split the data set to allow true parallelism. tez.grouping.max-size and tez.grouping.min-size are split parameters. Ref: https://docs.hortonworks.com/HDPDocuments/HDP2/HDP-2.3.4/bk_installing_manually_book/content/ref-ffec9e6b-41f4-47de-b5cd-1403b4c4a7c8.1.html If any of the responses was helpful, please don't forget to vote/accept the answer.
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09-26-2016
06:01 PM
@Rajkumar Singh thanks. good stuff.
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01-11-2019
02:36 PM
@Constantin Stanca Hi, could you please why there could be a split-brain situation when the number of zookeeper nodes is even? Thanks~
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07-18-2016
05:39 PM
It worked! Even though did not resolve my problem, but I was able to restart Hive. Thank you for the help!
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01-09-2018
11:44 PM
4 Kudos
By connecting to web ui over port 10002 one could check the number of live sessions on that instance of hiveserver
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07-05-2016
02:30 PM
Good to hear, thanks for the follow up information @Ravikumar Kumashi.
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06-19-2016
03:02 PM
normally mapper dont fail with OOM and 8192M is pretty good, I suspect that if you have some big records while reading from csv, are you doing some memory intensive operation inside mapper. could you please share the task log for this attempt attempt_1466342436828_0001_m_000008_2
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06-14-2016
08:57 AM
Thanks @ Pierre Villard This is what i was expecting... Thanks once again...
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