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[MINOR][DOC] spark.executor.memoryOverhead is not cluster-mode only #30311

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[MINOR][DOC] spark.executor.memoryOverhead is not cluster-mode only #30311

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4 changes: 2 additions & 2 deletions core/src/main/scala/org/apache/spark/internal/config/package.scala
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Expand Up @@ -302,8 +302,8 @@ package object config {
.createWithDefaultString("1g")

private[spark] val EXECUTOR_MEMORY_OVERHEAD = ConfigBuilder("spark.executor.memoryOverhead")
.doc("The amount of non-heap memory to be allocated per executor in cluster mode, " +
"in MiB unless otherwise specified.")
.doc("The amount of non-heap memory to be allocated per executor, in MiB unless otherwise" +
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@maropu maropu Nov 11, 2020

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This change means that the non-cluster mode refers to this value?

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@yaooqinn yaooqinn Nov 12, 2020

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yes, the 'client' deploy mode respects this too

" specified.")
.version("2.3.0")
.bytesConf(ByteUnit.MiB)
.createOptional
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7 changes: 3 additions & 4 deletions docs/configuration.md
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Expand Up @@ -274,10 +274,9 @@ of the most common options to set are:
<td><code>spark.executor.memoryOverhead</code></td>
<td>executorMemory * 0.10, with minimum of 384 </td>
<td>
Amount of additional memory to be allocated per executor process in cluster mode, in MiB unless
otherwise specified. This is memory that accounts for things like VM overheads, interned strings,
other native overheads, etc. This tends to grow with the executor size (typically 6-10%).
This option is currently supported on YARN and Kubernetes.
Amount of additional memory to be allocated per executor process, in MiB unless otherwise specified.
This is memory that accounts for things like VM overheads, interned strings, other native overheads, etc.
This tends to grow with the executor size (typically 6-10%). This option is currently supported on YARN and Kubernetes.
<br/>
<em>Note:</em> Additional memory includes PySpark executor memory
(when <code>spark.executor.pyspark.memory</code> is not configured) and memory used by other
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