I have a 5 node cluster with 4 data nodes which is in a good condition. But in order to add a secondary name node, I tried to generate the ssh key again instead of copying the already existing key onto the new machine. The new host was not registering with the following error: INFO 2017-09-21 17:24:06,811 NetUtil.py:67 - Connecting to https://asterix01.cem.spirent.com:8440/ca ERROR 2017-09-21 17:24:06,934 NetUtil.py:93 - [SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed (_ssl.c:579) ERROR 2017-09-21 17:24:06,934 NetUtil.py:94 - SSLError: Failed to connect. Please check openssl library versions. Refer to: https://bugzilla.redhat.com/show_bug.cgi?id=1022468 for more details. WARNING 2017-09-21 17:24:06,937 NetUtil.py:121 - Server at https://asterix01.cem.spirent.com:8440 is not reachable, sleeping for 10 seconds... So I stopped trying to add the new host and checked if the existing hosts are doing any good and restarted ambari-agent of one of them. The logs show failure with the same error as above- which confirms there is an issue with the keys. What can I do to resolve this? I tried to setup passwordless SSH as root user afresh as given in the documentation but it still fails. Can someone help me fix this please? I definitely can ssh without passwords from the command line. ... View more

Additionally, what exactly does dynamic allocation mean?? (I know it means allocating containers/executors on the fly but please elaborate) What are "spark.dynamicAllocation.maxExecutors"?? What should its value be? How are each of these parameters related to each other?? What should be the setting of all these parameters for best performance on the cluster? I read the documentation but I am afraid I am still confused with the terminology. Really appreciate if someone can elaborate. ... View more

Where do I find the option to set the number of executors in Ambari? When running spark shell, I can say --num-executors=46 and run the command. But I want to run spark through beeline and I am not sure where to set this parameter. My cluster has 4 datanodes each having 24 processors making a total of 96 processors in the cluster. I have set SPARK_EXECUTOR_CORES=2 in "advanced spark2-defaults" in ambari and want to set 46 executors. I tried setting "spark.dynamicAllocation.maxExecutors" to 46 and when I run the query through beeline (client mode), it uses only 47 containers and 24.5% of the cluster. How can I make the application use all the 96 (or max number) containers and the full cluster? ... View more