Member since
05-15-2018
132
Posts
15
Kudos Received
7
Solutions
My Accepted Solutions
Title | Views | Posted |
---|---|---|
1660 | 06-02-2020 06:22 PM | |
20218 | 06-01-2020 09:06 PM | |
2621 | 01-15-2019 08:17 PM | |
4916 | 12-21-2018 05:32 AM | |
5357 | 12-16-2018 09:39 PM |
04-07-2023
09:29 PM
1 Kudo
@satz , I am not referring to writing data using Kafka connect. Kafka partition data should be written to cloud after spending certain amount of time on Disk. https://docs.confluent.io/platform/current/kafka/tiered-storage.html Thanks, Uday
... View more
06-14-2022
12:00 PM
Hey, have you find out where to add this code? '--conf spark.unsafe.sorter.spill.read.ahead.enabled=false' Thanks!!
... View more
04-01-2021
09:38 AM
@satz I have similar issue, Is it possible to share data cleansing - removing newlines coding snippet.
... View more
06-02-2020
06:49 PM
Hello @renzhongpei , From the log4j properties file I see you are trying to write the logs in local file path [ log4j.appender.FILE.File=/home/rzpt/logs/spark.log ] Please note that, with the above log4j properties, the executors & Driver (in cluster mode) basically tries to write log files on above specified path on all the nodes where containers (executor) runs If your requirement is such, you would need to follow command like this (assuming the log4j.properties file in your local /tmp path on the node where you execute spark2-submit) spark2-submit --class com.nari.sgp.amc.measStandAssess.aurSum.AurSumMain --files /tmp/log4j.properties --conf spark.driver.extraJavaOptions="-Dlog4j.configuration=log4j.properties" --conf "spark.executor.extraJavaOptions="-Dlog4j.configuration=log4j.properties" --master yarn --deploy-mode cluster sgp-1.0.jar Note that in above command's "-Dlog4j.configuration=log4j.properties" you can use as it is (i.e) you don't need to give the explicit local path such as file:// . since the executor would automatically pickup the log4j.properties from the container localised path
... View more
06-02-2020
06:22 PM
Hello @mike_bronson7 , Thank you for posting your query You can execute 'get' on the same zookeeper client shell for the znode you would be able to get the hostname Example: zookeeper-shell.sh zoo_server1:2181 <<< "ls /brokers/ids/1018" It returns output as follows (example - in my case) [zk: localhost:2181(CONNECTED) 5] get /brokers/ids/10 {"listener_security_protocol_map":{"PLAINTEXT":"PLAINTEXT"},"endpoints":["PLAINTEXT://simple01.cloudera.com:9092"],"jmx_port":9393,"host":"simple01.cloudera.com","timestamp":"1590512066422","port":9092,"version":4} cZxid = 0x1619b ctime = Tue May 26 09:54:26 PDT 2020 mZxid = 0x1619b mtime = Tue May 26 09:54:26 PDT 2020 pZxid = 0x1619b cversion = 0 dataVersion = 1 aclVersion = 0 ephemeralOwner = 0x1722ddb1e844d50 dataLength = 238 numChildren = 0 so, my brokerID 10 is mapped with the host: simple01.cloudera.com
... View more
06-02-2020
05:28 PM
Hello @Venkat451 , Thank you for posting your query. From the error message shared (as below) I see the executor failing while it is trying to attach itself with the consumer group, more specifically, it is getting Authorisation exception while attaching to the group. ERROR org.apache.spark.executor.Executor - Exception in task 2.0 in stage 0.0 (TID 2) org.apache.kafka.common.errors.GroupAuthorizationException: Not authorized to access group: spark-executor-<groupID> If you have authorisation mechanisms such as (sentry, kafka ACLs, Ranger) enabled on your cluster please grant necessary permissions to the consumer group https://docs.cloudera.com/HDPDocuments/HDP2/HDP-2.6.1/bk_security/content/kafka-acl-examples.html
... View more
06-02-2020
04:26 AM
Hello @zanteb , Thank you for posting your query. While you are using with spark-submit you would require to pass the files (jass & keytab) with --files option on spark-submit just like [1] https://docs.cloudera.com/HDPDocuments/HDP3/HDP-3.1.5/developing-spark-applications/content/running_spark_streaming_jobs_on_a_kerberos-enabled_cluster.html While doing so, your JAAS and keytab file would be shipped to executors and Application master /Driver (incase of cluster mode) If your external client is not spark and it is just a standalone java code (example) then you can just go ahead with passing "-Djava.security.auth.login.config=jaas.conf"" while executing the code and file can reside on the same client node
... View more
05-25-2020
07:28 PM
Hi @satz I've checked the spark history logs and it says that it has a read permission denied for the user named "spark". I've change recursively the /user/spark permission and ownership to spark but when there is a new file, it has its own permission type so it can't be read again by spark.
... View more
05-22-2020
07:59 PM
You can also try to stop and start [HDP] namenode services from command line by using below command: If you are running NameNode HA (High Availability), start the JournalNodes by executing these commands on the JournalNode host machines: su -l hdfs -c "/usr/hdp/current/hadoop-hdfs-journalnode/../hadoop/sbin/hadoop-daemon.sh start journalnode" where $HDFS_USER is the HDFS user. For example, hdfs. Execute this command on the NameNode host machine(s): su -l hdfs -c "/usr/hdp/current/hadoop-hdfs-namenode/../hadoop/sbin/hadoop-daemon.sh start namenode" If you are running NameNode HA, start the ZooKeeper Failover Controller (ZKFC) by executing the following command on all NameNode machines. The starting sequence of the ZKFCs determines which NameNode will become Active. su -l hdfs -c "/usr/hdp/current/hadoop-hdfs-namenode/../hadoop/sbin/hadoop-daemon.sh start zkfc" If you are not running NameNode HA, execute the following command on the Secondary NameNode host machine. If you are running NameNode HA, the Standby NameNode takes on the role of the Secondary NameNode. su -l hdfs -c "/usr/hdp/current/hadoop-hdfs-namenode/../hadoop/sbin/hadoop-daemon.sh start secondarynamenode"
... View more
03-04-2020
11:27 PM
Hello @lakshmipathy , Please refer the below thread, hope this would help https://community.cloudera.com/t5/Support-Questions/How-to-define-topic-retention-with-kafka/td-p/222671
... View more