java.lang.IllegalArgumentException: Unknown/unsupported param List(--executor-memory, 0.5g, --executor-cores, 2, --primary-py-file, s3://<mybucketname>/mypythonfile.py, --class, org.apache.spark.deploy.PythonRunner) Usage: org.apache.spark.deploy.yarn.Client [options] Options: --jar JAR_PATH Path to your application's JAR file (required in yarn-cluster mode) . . .

Stack Overflow | Gopala | 5 months ago
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    java.lang.IllegalArgumentException: Unknown/unsupported param List(--executor-memory, 0.5g, --executor-cores, 2, --primary-py-file, s3://<mybucketname>/mypythonfile.py, --class, org.apache.spark.deploy.PythonRunner) Usage: org.apache.spark.deploy.yarn.Client [options] Options: --jar JAR_PATH Path to your application's JAR file (required in yarn-cluster mode) . . .
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    java.lang.IllegalArgumentException: Unknown/unsupported param List(--executor-cores, , --files, s3://pythonpicode/PythonPi.py, --primary-py-file, PythonPi.py, --class, org.apache.spark.deploy.PythonRunner) Usage: org.apache.spark.deploy.yarn.Client [options] Options: --jar JAR_PATH Path to your application's JAR file (required in yarn-cluster mode) --class CLASS_NAME Name of your application's main class (required) --primary-py-file A main Python file --arg ARG Argument to be passed to your application's main class. Multiple invocations are possible, each will be passed in order. --num-executors NUM Number of executors to start (Default: 2) --executor-cores NUM Number of cores per executor (Default: 1). --driver-memory MEM Memory for driver (e.g. 1000M, 2G) (Default: 512 Mb) --driver-cores NUM Number of cores used by the driver (Default: 1). --executor-memory MEM Memory per executor (e.g. 1000M, 2G) (Default: 1G) --name NAME The name of your application (Default: Spark) --queue QUEUE The hadoop queue to use for allocation requests (Default: 'default') --addJars jars Comma separated list of local jars that want SparkContext.addJar to work with. --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 distributed with the job. --archives archives Comma separated list of archives to be distributed with the job.
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    GitHub comment 209#98161267

    GitHub | 2 years ago | dsdinter
    java.lang.IllegalArgumentException: You must specify at least 1 executor! Usage: org.apache.spark.deploy.yarn.Client [options] Options: --jar JAR_PATH Path to your application's JAR file (required in yarn-cluster mode) --class CLASS_NAME Name of your application's main class (required) --primary-py-file A main Python file --arg ARG Argument to be passed to your application's main class. Multiple invocations are possible, each will be passed in order. --num-executors NUM Number of executors to start (Default: 2) --executor-cores NUM Number of cores per executor (Default: 1). --driver-memory MEM Memory for driver (e.g. 1000M, 2G) (Default: 512 Mb) --driver-cores NUM Number of cores used by the driver (Default: 1). --executor-memory MEM Memory per executor (e.g. 1000M, 2G) (Default: 1G) --name NAME The name of your application (Default: Spark) --queue QUEUE The hadoop queue to use for allocation requests (Default: 'default') --addJars jars Comma separated list of local jars that want SparkContext.addJar to work with. --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 distributed with the job. --archives archives Comma separated list of archives to be distributed with the job.
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    Root Cause Analysis

    1. java.lang.IllegalArgumentException

      Unknown/unsupported param List(--executor-memory, 0.5g, --executor-cores, 2, --primary-py-file, s3://<mybucketname>/mypythonfile.py, --class, org.apache.spark.deploy.PythonRunner) Usage: org.apache.spark.deploy.yarn.Client [options] Options: --jar JAR_PATH Path to your application's JAR file (required in yarn-cluster mode) . . .

      at org.apache.spark.deploy.SparkSubmit$.main()
    2. Spark
      SparkSubmit.main
      1. org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:121)
      2. org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
      2 frames