Hi @Veera B. Budhi, Job by job approach: One solution to your problem is to specify the queue to use when submitting your Spark job or when you connect to hive. When submitting your Spark job you can specify the queue by --queue like in this example $ ./bin/spark-submit --class org.apache.spark.examples.SparkPi --master yarn --deploy-mode cluster --driver-memory 4g --executor-memory 2g --executor-cores 1 --queue SparkQueue lib/spark-examples*.jar 10 To specify the queue at connection time to HS2: beeline -u "jdbc:hive2://sandbox.hortonworks.com:10000/default?tez.queue.name=HiveQueue" -n it1 -p it1-d org.apache.hive.jdbc.HiveDriver Or you can set the queue after you are connected using set tez.queue.name=HiveQueue; beeline -u "jdbc:hive2://sandbox.hortonworks.com:10000/default" -n it1 -p it1-d org.apache.hive.jdbc.HiveDriver >set tez.queue.name=HiveQueue; Change default queue: The second approach would be to specify a default queue for Hive or Spark to use. To do it for Spark set spark.yarn.queue to SparkQueue instead of default in Ambari To do this for Hive, you can add tez.queue.name to custom hiverserver2-site configuration in Ambari Hope this helps ... View more

Hi @Sunile Manjee There's no Zeppelin interpreter for Solr. List of available interpreters is here. You can make Solr a Spark RDD and hence access Solr Data with Spark interpreter in Zeppelin. Another approach (that I didn't test) is to use Solr JDBC connection and Zeppelin JDBC interpreter. A Jira Ticket make me think that some problem may be encountered. ... View more

Hi @Subhasis Roy Tuples are used to represent complex data types. Tuples are between parentheses like in this example: cat data (3,8,9) (4,5,6) (1,4,7) (3,7,5) (2,5,8) (9,5,8) A = LOAD 'data' AS (t1:tuple(t1a:int, t1b:int,t1c:int),t2:tuple(t2a:int,t2b:int,t2c:int)); X = FOREACH A GENERATE t1.t1a,t2.$0; DUMP X; (3,4) (1,3) (2,9) In your case, your data is simple and not between parentheses so you don't need to use tuple in your schema. Just run this A = LOAD '/tmp/test.csv' USING PigStorage(',') AS (a:chararray, b:chararray, c:chararray, d:chararray, e:chararray); DUMP A; (1201,gopal, manager, 50000, TP) (1202,manisha, proof reader, 50000, TP) If you want to access only some fields of your data you use this (here I show only the 4 first fields): X = FOREACH A GENERATE $0, $1, $2, $3; DUMP X; (1201,gopal, manager, 50000) (1202,manisha, proof reader, 50000) Does this answer your question ? ... View more

Hi @Indrajit swain, You are hitting the ElasticSearch that Atlas is running in background for its operations. This is why you get an older version of ES when you curl port 9200. To check it, stop your ES instance and check if you have something listening to port 9200 netstat -npl | grep 9200 You should still have something listening even when your ES is down. You can see the configuration of existing ES in Atlas configuration in Ambari When ES starts and find its port used (9200) it picks the next available one. So your ES instance will be running on port 9201. You can see it in the starting logs (like in my example) : [2016-05-06 17:09:41,452][INFO ][http ] [Speedball] publish_address {127.0.0.1:9201}, bound_addresses {127.0.0.1:9201} You can try to curl the two ports to test: [root@sandbox ~]# curl localhost:9200 { "status" : 200, "name" : "Gravity", "version" : { "number" : "1.2.1", "build_hash" : "6c95b759f9e7ef0f8e17f77d850da43ce8a4b364", "build_timestamp" : "2014-06-03T15:02:52Z", "build_snapshot" : false, "lucene_version" : "4.8" }, "tagline" : "You Know, for Search" } [root@sandbox ~]# curl localhost:9201 { "name" : "Speedball", "cluster_name" : "elasticsearch", "version" : { "number" : "2.3.2", "build_hash" : "b9e4a6acad4008027e4038f6abed7f7dba346f94", "build_timestamp" : "2016-04-21T16:03:47Z", "build_snapshot" : false, "lucene_version" : "5.5.0" }, "tagline" : "You Know, for Search" } You can also change the port of ES to something you want in the yaml file. Hope this helps ... View more