Github user berngp commented on the pull request:

    https://github.com/apache/spark/pull/116#issuecomment-38418948
  
    @aarondav provided the squash commit with the agreed changes.
    
    Bellow the help message that we could have if we want to support the args 
used by #86. Please share your thoughts.
    
    ```
    ${txtbld}Usage${txtrst}: spark-shell [OPTIONS]
    
    ${txtbld}OPTIONS${txtrst}:
        -h  --help          : Print this help information.
        --executor-memory   : The memory used by each executor of the Spark 
Shell, the number 
                              is followed by m for megabytes or g for 
gigabytes, e.g. "1g".
        --driver-memory     : The memory used by the Spark Shell, the number is 
followed 
                              by m for megabytes or g for gigabytes, e.g. "1g", 
defaults to 512Mb.
        --master            : A full string that describes the Spark Master, 
defaults to "local"
                              e.g. "spark://localhost:7077".
        --log-conf          : Enables logging of the supplied SparkConf as INFO 
at start of the
                              Spark Context.
    
    ${txtbld}Spark standalone with cluster deploy mode only${txtrst}:
        --driver-cores      : Cores for driver.
        --supervise         : Whether to restart the driver on failure.
    
    ${txtbld}Spark standalone and Mesos only${txtrst}:
        --total-executor-cores : CORES Total cores for all executors.
    
    ${txtbld}YARN-only${txtrst}:
        --executor-cores    : Number of cores per executor (Default: 1).
        --executor-memory   : Memory per executor (e.g. 1000M, 2G) (Default: 
1G).
        --queue QUEUE       : The YARN queue to submit the application to 
(Default: 'default').
        --num-executors NUM : Number of executors to start (Default: 2).
        --files FILES       : Comma separated list of files to be placed next 
to all executors.
        --archives ARCHIVES : Comma separated list of archives to be extracted 
next to all executors.
    
    e.g.
        spark-shell -m spark://localhost:7077 -c 4 -dm 512m -em 2g
    ```


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