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[MINOR][DOCS] Add a note that 'spark.executor.pyspark.memory' is dependent on 'resource' #23664

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[MINOR][DOCS] Add a note that 'spark.executor.pyspark.memory' is dependent on 'resource' #23664

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Add a note that 'spark.executor.pyspark.memory' is dependent on 'reso…
HyukjinKwon Jan 27, 2019
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Make the note style consistent
HyukjinKwon Jan 27, 2019
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HyukjinKwon Jan 28, 2019
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HyukjinKwon Jan 31, 2019
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9 changes: 6 additions & 3 deletions docs/configuration.md
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Expand Up @@ -190,8 +190,10 @@ of the most common options to set are:
and it is up to the application to avoid exceeding the overhead memory space
shared with other non-JVM processes. When PySpark is run in YARN or Kubernetes, this memory
is added to executor resource requests.

NOTE: Python memory usage may not be limited on platforms that do not support resource limiting, such as Windows.
<br/>
<em>Note:</em> This feature is dependent on Python's `resource` module; therefore, the behaviors and
limitations are inherited. For instance, Windows does not support resource limiting and actual
resource is not limited on MacOS.
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Expand Down Expand Up @@ -223,7 +225,8 @@ of the most common options to set are:
stored on disk. This should be on a fast, local disk in your system. It can also be a
comma-separated list of multiple directories on different disks.

NOTE: In Spark 1.0 and later this will be overridden by SPARK_LOCAL_DIRS (Standalone), MESOS_SANDBOX (Mesos) or
<br/>
<em>Note:</em> This will be overridden by SPARK_LOCAL_DIRS (Standalone), MESOS_SANDBOX (Mesos) or
LOCAL_DIRS (YARN) environment variables set by the cluster manager.
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