@asmarz  On the edgenode Just to validate your situation I have spun up single node cluster Tokyo IP 192.168.0.67 and installed an edge node Busia IP 192.168.0.66 I will demonstrate the spark client setup on the edge node and evoke the spark-shell First I have to configure the passwordless ssh below my edge node   Passwordless setup [root@busia ~]# mkdir .ssh [root@busia ~]# chmod 600 .ssh/ [root@busia ~]# cd .ssh [root@busia .ssh]# ll total 0   Networking not setup The master is unreachable from the edge node [root@busia .ssh]# ping 198.168.0.67 PING 198.168.0.67 (198.168.0.67) 56(84) bytes of data. From 198.168.0.67 icmp_seq=1 Destination Host Unreachable From 198.168.0.67 icmp_seq=3 Destination Host Unreachable   On the master The master has a single node HDP 3.1.0 cluster, I will deploy the clients to the edge node from here [root@tokyo ~]# cd .ssh/ [root@tokyo .ssh]# ll total 16 -rw------- 1 root root 396 Jan 4 2019 authorized_keys -rw------- 1 root root 1675 Jan 4 2019 id_rsa -rw-r--r-- 1 root root 396 Jan 4 2019 id_rsa.pub -rw-r--r-- 1 root root 185 Jan 4 2019 known_hosts   Networking not setup The edge node is still unreachable from the master Tokyo   [root@tokyo .ssh]# ping 198.168.0.66 PING 198.168.0.66 (198.168.0.66) 56(84) bytes of data. From 198.168.0.66 icmp_seq=1 Destination Host Unreachable From 198.168.0.66 icmp_seq=2 Destination Host Unreachable   Copied the id-ira.pub key to the edgenode [root@tokyo ~]# cat .ssh/id_rsa.pub | ssh root@192.168.0.215 'cat >> .ssh/authorized_keys' The authenticity of host '192.168.0.215 (192.168.0.215)' can't be established. ECDSA key fingerprint is SHA256:ZhnKxkn+R3qvc+aF+Xl5S4Yp45B60mPIaPpu4f65bAM. ECDSA key fingerprint is MD5:73:b3:5a:b4:e7:06:eb:50:6b:8a:1f:0f:d1:07:55:cf. Are you sure you want to continue connecting (yes/no)? yes Warning: Permanently added '192.168.0.215' (ECDSA) to the list of known hosts. root@192.168.0.215's password:   Validation the passwordless ssh works [root@tokyo ~]# ssh root@192.168.0.215 Last login: Fri Jan 10 22:36:01 2020 from 192.168.0.178 [root@busia ~]# hostname -f busia.xxxxxx.xxx xxxxxx Single node Cluster  [root@tokyo ~]# useradd asmarz [root@tokyo ~]# su - asmarz   On the master as user asmarz  I can access the spark-shell and execute any spark code   Add the edge node to the cluster   Install the clients on the edge node   On the master as user asmarz  I have access to the spark-shell Installed Client components on the edge-node can be seen in the CLI     I chose to install all the clients  on the edge node just to demo as I have already install the hive client on the edge node  without any special setup I can now launch the hive HQL  on the master Tokyo from the edge node  After installing the spark client on the edge node I can now also launch the spark-shell  from the edge node and run any spark code, so this demonstrates that you can create any user on the edge node and he /she can rive Hive  HQL, SPARK SQL  or PIG script. You will notice I didn't update the  HDFS , YARN, MAPRED,HIVE  configurations it was automatically done by Ambari during the installation it copied over to the edge node the correct conf files !! The asmarz user from the edge node can also acess HDFS   Now as user asmarz  I have launched a spark-submit job  from the edge node  The launch is successful on the master Tokyo  see Resource Manager URL, that can be confirmed  in the RM UI This walkthrough validates that any user on the edge node can launch a job in the cluster this poses a security problem in production hence my earlier hint of Kerberos. Having said that  you will realize I didn't  do any special configuration  after the client installation because Ambari distributes the correct configuration of all the component  and it does that for every installation of a new component that's the reason  Ambari is a management tool If this walkthrough answers your question, please do accept the answer and close the thread. Happy hadooping  ... View more

@md88    I was just wondering why you have chosen to go down a very difficult road to deploy unpackaged Hadoop when you have a simplified way using Cloudera see HDP 3.1.4 deployment  this is a well-documented procedure that is relatively straight forward especially when you are new to Hadoop. In your initial thread, you said you had  HDP 2.6 already installed but the document you are referencing isn't a Cloudera documentation !! Please refer to the earlier link I shared above that thoroughly documents the installation of the HDP ecosystem  below are some of the components  which have been tested and integrated which gives you other tools  to be more productive i.e  Security, Streaming, ETL,one-stop notebook Zeppelin etc Official Apache component versions for HDP 3.1.4: Apache Accumulo 1.7.0 Apache Atlas 1.1.0 Apache Calcite 1.16.0 Apache DataFu 1.3.0 Apache Druid 0.12.1 (incubating) Apache Hadoop 3.1.1 Apache HBase 2.0.2 Apache Hive 3.1.0 Apache Kafka 2.0.0 Apache Knox 1.0.0 Apache Livy 0.5.0 Apache Oozie 4.3.1 Apache Phoenix 5.0.0 Apache Pig 0.16.0 Apache Ranger 1.2.0 Apache Spark 2.3.2 Apache Sqoop 1.4.7 Apache Storm 1.2.1 Apache TEZ 0.9.1 Apache Zeppelin 0.8.0 Apache ZooKeeper 3.4.6   Having said if you want Ambari to manage your standalone Hadoop cluster you will have to walk in uncharted waters because that process is called Ambari take-over is not well documented and hence quite frustrating for a newbie. Here is a link to Ryba is an open-source project. You will have to be proficient in Python the challenge will be to give Apache Ambari full knowledge of your clusters’ topologies which services are running and where they are running. Please let me know if you need more help.   ... View more