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  • Running Spark on m4 instead of m3 on AWS
    via Stack Overflow by user6742737
    • java.lang.IllegalArgumentException: Unknown/unsupported param List(--executor-cores, , --files, s3://pythonpicode/, --primary-py-file,, --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. at org.apache.spark.deploy.yarn.ClientArguments.parseArgs(ClientArguments.scala:228) at org.apache.spark.deploy.yarn.ClientArguments.<init>(ClientArguments.scala:56) at org.apache.spark.deploy.yarn.Client$.main(Client.scala:646) at org.apache.spark.deploy.yarn.Client.main(Client.scala) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke( at sun.reflect.DelegatingMethodAccessorImpl.invoke( at java.lang.reflect.Method.invoke( at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:569) at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:166) at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:189) at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:110) at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
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