"--py-files" is not a valid option

Hi Team,

I was trying to run Hail non-interactively, by passing a Python script to spark-submit. I have LSF system and my command is below

lsf-spark202-submit.sh --conf “spark.driver.maxResultSize=0” --conf “spark.reducer.maxSizeInFlight=100m” --conf “spark.shuffle.file.buffer=64k” --conf “spark.akka.frameSize=256” --conf “spark.akka.threads=10” --conf “spark.executor.memory=100g” --conf “spark.driver.memory=50g” --conf " spark.local.dir=/gpfs/ngsdata/sparkcache" --class “is.hail.driver.Main” /gpfs/software/spark/hail-all-spark.jar --py-files /gpfs/software/hailnew/build/distributions/hail-python.zip hailscript.py

and I am getting below error.

“–py-files” is not a valid option

Since this is my very first time of using Hail so can some one please help me on this?

Something looks odd – the --class "is.hail.driver.Main" is something that was used with the command line interface, which was removed ~8 months ago.

What happens if you just run lsf-spark202-submit.sh -h?

lsf-spark202-submit.sh -h

  • SPARK_HOME=/gpfs/software/spark/spark-2.1.0-bin-hadoop2.7/
  • ‘[’ ‘’ = ‘’ ‘]’
  • export SPARK_MASTER_PORT=6311
    ++ hostname
  • SPARK_MASTER=hpclogin1
  • . /gpfs/master/lsf/10.1/linux2.6-glibc2.3-x86_64/bin/lsf-start-spark.sh
    ++ /gpfs/software/spark/spark-2.1.0-bin-hadoop2.7//sbin/start-master.sh
    ++ echo Launch spark master spark://hpclogin1:6311 successfully.
    Launch spark master spark://hpclogin1:6311 successfully.
    ++ HOST=false
    ++ CORE=false
    ++ NUM_HOSTS=0
    ++ sleep 2
    ++ export GATK_SPARK_MASTER=spark://hpclogin1:6311
    ++ GATK_SPARK_MASTER=spark://hpclogin1:6311
  • echo -h
  • GATK_SPARK_MASTER=spark://hpclogin1:6311
  • /gpfs/software/spark/spark-2.1.0-bin-hadoop2.7//bin/spark-submit --master spark://hpclogin1:6311 -h
    Usage: spark-submit [options] <app jar | python 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]

–master MASTER_URL spark://host:port, mesos://host:port, yarn, or 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 local 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.

–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

–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.

Spark standalone with cluster deploy mode only:
–driver-cores NUM Cores for driver (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)

–driver-cores NUM Number of cores used by the driver, only in cluster mode
(Default: 1).
–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.

  • /gpfs/software/spark/spark-2.1.0-bin-hadoop2.7//sbin/stop-master.sh
  • kill -9
    kill: usage: kill [-s sigspec | -n signum | -sigspec] pid | jobspec … or kill -l [sigspec]

This issue is solved!! You may close this now.