If you have HDP 2.6.3 then you should be able to find spark 2.2 version of spark-llap available under /usr/hdp/current/ Perhaps you are using the older versions of shc using --packages and thats not compatible with spark 2.2. ... View more

/etc/hive/conf/hive-site.xml is the config for Hive service itself and is managed via Ambari through the Hive service config page. /usr/hdp/current/spark-client/conf/hive-site.xml actually points to /etc/spark/conf/hive-site.xml . This is the minimal hive config that Spark needs to access Hive. This is managed via Ambari through the Spark service config page. Ambari correctly configures this hive site for Kerberos. Depending upon your version of HDP you may not have the correct support in Ambari for configuring Livy. ... View more

For JDBC there is a built-in jar for JDBC support. No need for Simba. ... View more

Probably missing having hbase-site or phoenix conf in the classpath. So it cannot find the ZK info for hbase/phoenix. ... View more

Fixed the link. It has the code. ... View more

Yes. For Spark 1.6 it is GA in HDP 2.5.3. The documentation is available from the Github site for a given SHC release tag. That is the source of truth. ... View more

--files will add it to the working directory of the YARN app master and container and this would mean that those files (and not jars) would be in the classpath of the app master and container. But in client mode jobs the main driver code is running in the client machine. So these --files are not available on the driver. SPARK_CLASSPATH adds these files to the driver classpath. Its an env var. So one could say the following. Note it will warn saying its deprecated and cannot be used concurrently with --driver-class-path option. More information can be found here. https://github.com/hortonworks-spark/shc export SPARK_CLASSPATH=/a/b/c/hbase-site.xml;/d/e/f/hive-site.xml ... View more

Unfortunately, that kind of functionality does not exist for Spark Streaming. Spark Streaming runs as a standard YARN job and YARN commands could be used to start, stop (kill) and re-submit a job. A properly written Spark streaming job should be able to support at-least once or exactly-once semantics through this lifecycle. But other than that there is no UI or other automation support for it. Zeppelin is designed for interactive analysis and running Spark streaming via Zeppelin is not recommended (other than demos for presentations). ... View more

SHC does not have a notion of listing tables in HBase. It works on the table catalog provided to the data source in the program. Hive will also not list HBase tables because they are not present in the metastore. There is some rudimentary way to add Hbase external tables in Hive but I dont think that really used. I could be wrong. To list Hbase tables, currently the only reliable way would be to use HBase API's inside the spark program to list tables. ... View more

Hive and HiveContext in Spark can only show the tables that are registered in the Hive Metastore and Hbase tables are usually not there because the schema of most Hbase tables are not easily defined in the metastore. To read HBase tables from Spark using DataFrame API please consider Spark HBase Connector ... View more

In HDP 2.5 Zeppelin JDBC interpreter can run 1 query in a paragraph. There is a limit of 10 queries that can be run simultaneously overall. ... View more

First of all, which Spark version are you using. Apache Spark 2.0 has support for automatically acquiring HBase security tokens correctly for that job and all its executors. Apache Spark 1.6 does not have that feature but in HDP Spark 1.6 we have backported that feature and it can acquire the HBase tokens for the jobs. The tokens are automatically acquired if 1) security is enabled and 2) hbase-site.xml is present on the client classpath 3) that hbase-site.xml has kerberos security configured. Then hbase tokens for the hbase master specified in that hbase-site.xml are acquired and used in the job. In order to obtain the tokens spark client needs to use hbase code and so specific hbase jars need to be present in the client classpath. This is documented in here on the SHC github page. Search for "secure" on that page. To access hbase inside the spark jobs the job obviously needs hbase jars to be present for the driver and/or executors. That would be part of your existing job submission for non-secure clusters, which I assume already works. If this job is going to be long running and run beyond the token expire time (typically 7 days) then you need to submit the Spark job with the --keytab and --principal option such that Spark can use that keytab to re-acquire tokens before the current ones expire. ... View more

If this does not work for you please open the feature request by creating an issue on the github project for SHC. /cc @wyang ... View more

+1. Thats what I mentioned in my last comment below. Copying here so everyone get the context quickly. Ranger KMS could be the issue because it causes problems for getting HDFS delegation token. If Z or L user needs to get HDFS delegation token then they also need to be super users for Ranger. You are better off trying with non-Ranger cluster or adding them to Ranger super users which is different from core site super users. ... View more

AM percent property in YARN is relevant if the cluster has idle resources but still and AM is not being being started for the application. On the YARN UI you will see available capacity but AM not being started. E.g. cluster has 100GB capacity and is using 50GB only. If you want to run X apps concurrently and each AM need M GB resources (per config) then you need X*M capacity for AMs and this can be used to determine the AM percent as a function of the total cluster capacity. On the other hand, if the cluster does not have any capacity at that time (as seen in YARN UI) then changing the AM percent may not help. The cluster does not have capacity to obtain a container slot for the AM. E.g. cluster has 100GB capacity and is already using 100GB. In this case you will have to wait for capacity to free up. ... View more

AM percent property in YARN is relevant if the cluster has idle resources but still and AM is not being being started for the application. On the YARN UI you will see available capacity but AM not being started. E.g. cluster has 100GB capacity and is using 50GB only. If you want to run X apps concurrently and each AM need M GB resources (per config) then you need X*M capacity for AMs and this can be used to determine the AM percent as a function of the total cluster capacity. On the other hand, if the cluster does not have any capacity at that time (as seen in YARN UI) then changing the AM percent may not help. The cluster does not have capacity to obtain a container slot for the AM. E.g. cluster has 100GB capacity and is already using 100GB. In this case you will have to wait for capacity to free up. ... View more

Ranger KMS could be the issue because it causes problems for getting HDFS delegation token. If Z or L user needs to get HDFS delegation token then they also need to be super users for Ranger. You are better off trying with non-Ranger cluster or adding them to Ranger super users which is different from core site super users. ... View more

If you are trying to authenticate use FOO via LDAP on Zeppelin and then use Zeppelin to launch a %livy.spark notebook as user FOO then you are using Livy impersonation (this is different from Zeppelin's own impersonation which is only recommended for the shell interpreter, not Livy interpreter). User FOO should be available in the Hadoop cluster also because the jobs will eventually run as that user. HDP 2.5.3 should already have all the configs setup for you. Its a bug that livy.spark.master in Zeppelin is not yarn-cluster. Next, Livy should be using Livy keytab and Zeppelin should be using Zeppelin keytab. Zeppelin user needs to be configured a livy.superuser in Livy config. Livy user should be configured as a proxy user in core-site.xml so that YARN/HDFS allow it to impersonate other users (in thi case hadoopadmin) when submitting spark jobs. If that Zeppelin->Livy connection fails then you will see an exception in Zeppelin and logs in Livy. If that succeeds then Livy will try to submit the job. If that fails you will see the exception in Livy logs. From the above exception in your last comment, it appears that Livy user is not configured as a proxy user properly in core-site.xml. You can check that in hadoop configs and may have to restart affected services in case you change it. In HDP 2.5.3 this should already be done for you during Livy installation via Ambari. ... View more