Also make sure you provide your encrypted user name and password in the repository URL   example:  https://<user_name>:<password>@archive.cloudera.com/p/cm7/redhat/7   user name password can be obtained using your valid Cloudera license  ... View more

I did the following steps and it helped 1) [root@cm_scm_103 cloudera-scm-agent]# cp /opt/cloudera/parcel-repo/STREAMSETS_DATACOLLECTOR-3.14.0-el7.parcel.torrent /opt/cloudera/parcel-cache/ [root@cm_scm_103 cloudera-scm-agent]# ls -ltr /opt/cloudera/parcel-cache/STREAMSETS_DATACOLLECTOR-3.14.0-el7.parcel.torrent -rw-r----- 1 root root 211751 May 9 11:14 /opt/cloudera/parcel-cache/STREAMSETS_DATACOLLECTOR-3.14.0-el7.parcel.torrent You have mail in /var/spool/mail/root [root@cm_scm_103 cloudera-scm-agent]# 2) make sure enough free space in /opt/cloudera/parcels 3) Restarted cloudera-scm-agent in server_b01, server_b02 and cm_scm_103 [root@server_b01 parcel-cache]# systemctl restart cloudera-scm-agent 4) Restarted cloudera-scm-server in cm_scm_103 [root@cm_scm_103 cloudera-scm-agent]# sudo service cloudera-scm-server restart ... View more

[root@servername conf.dist]# spark2-submit Usage: spark-submit [options] <app jar | python file | R file> [app arguments] Usage: spark-submit --kill [submission ID] --master [spark://...] Usage: spark-submit --status [submission ID] --master [spark://...] Usage: spark-submit run-example [options] example-class [example args] Options: --master MASTER_URL spark://host:port, mesos://host:port, yarn, k8s://https://host:port, or local (Default: local[*]). --deploy-mode DEPLOY_MODE Whether to launch the driver program locally ("client") or on one of the worker machines inside the cluster ("cluster") (Default: client). --class CLASS_NAME Your application's main class (for Java / Scala apps). --name NAME A name of your application. --jars JARS Comma-separated list of jars to include on the driver and executor classpaths. --packages Comma-separated list of maven coordinates of jars to include on the driver and executor classpaths. Will search the local maven repo, then maven central and any additional remote repositories given by --repositories. The format for the coordinates should be groupId:artifactId:version. --exclude-packages Comma-separated list of groupId:artifactId, to exclude while resolving the dependencies provided in --packages to avoid dependency conflicts. --repositories Comma-separated list of additional remote repositories to search for the maven coordinates given with --packages. --py-files PY_FILES Comma-separated list of .zip, .egg, or .py files to place on the PYTHONPATH for Python apps. --files FILES Comma-separated list of files to be placed in the working directory of each executor. File paths of these files in executors can be accessed via SparkFiles.get(fileName). --conf PROP=VALUE Arbitrary Spark configuration property. --properties-file FILE Path to a file from which to load extra properties. If not specified, this will look for conf/spark-defaults.conf. --driver-memory MEM Memory for driver (e.g. 1000M, 2G) (Default: 1024M). --driver-java-options Extra Java options to pass to the driver. --driver-library-path Extra library path entries to pass to the driver. --driver-class-path Extra class path entries to pass to the driver. Note that jars added with --jars are automatically included in the classpath. --executor-memory MEM Memory per executor (e.g. 1000M, 2G) (Default: 1G). --proxy-user NAME User to impersonate when submitting the application. This argument does not work with --principal / --keytab. --help, -h Show this help message and exit. --verbose, -v Print additional debug output. --version, Print the version of current Spark. Cluster deploy mode only: --driver-cores NUM Number of cores used by the driver, only in cluster mode (Default: 1). Spark standalone or Mesos with cluster deploy mode only: --supervise If given, restarts the driver on failure. --kill SUBMISSION_ID If given, kills the driver specified. --status SUBMISSION_ID If given, requests the status of the driver specified. Spark standalone and Mesos only: --total-executor-cores NUM Total cores for all executors. Spark standalone and YARN only: --executor-cores NUM Number of cores per executor. (Default: 1 in YARN mode, or all available cores on the worker in standalone mode) YARN-only: --queue QUEUE_NAME The YARN queue to submit to (Default: "default"). --num-executors NUM Number of executors to launch (Default: 2). If dynamic allocation is enabled, the initial number of executors will be at least NUM. --archives ARCHIVES Comma separated list of archives to be extracted into the working directory of each executor. --principal PRINCIPAL Principal to be used to login to KDC, while running on secure HDFS. --keytab KEYTAB The full path to the file that contains the keytab for the principal specified above. This keytab will be copied to the node running the Application Master via the Secure Distributed Cache, for renewing the login tickets and the delegation tokens periodically. [root@servername conf.dist]# ... View more