Github user sryza commented on a diff in the pull request:
https://github.com/apache/spark/pull/377#discussion_r12015098
--- Diff: docs/configuration.md ---
@@ -103,23 +103,31 @@ Apart from these, the following properties are also
available, and may be useful
</td>
</tr>
<tr>
+ <td>spark.system.reservedMemorySize</td>
+ <td>300m</td>
+ <td>
+ Constant amount of heap to reserve on executors for Spark's own code
and user code. Taken into account before calculating
+ memory available for and shuffle as configured in
<code>spark.storage.memoryFraction</code> and
+ <code>spark.shuffle.memoryFraction</code>.
+ </td>
+</tr>
+<tr>
<td>spark.storage.memoryFraction</td>
<td>0.6</td>
<td>
- Fraction of Java heap to use for Spark's memory cache. This should not
be larger than the "old"
- generation of objects in the JVM, which by default is given 0.6 of the
heap, but you can increase
- it if you configure your own old generation size.
+ Fraction of Java heap to use for Spark's memory cache, after
accounting for <code>spark.system.reservedMemorySize</code>.
+ The effective size should not be larger than the "old" generation of
objects in the JVM.
</td>
</tr>
<tr>
<td>spark.shuffle.memoryFraction</td>
<td>0.3</td>
<td>
- Fraction of Java heap to use for aggregation and cogroups during
shuffles, if
- <code>spark.shuffle.spill</code> is true. At any given time, the
collective size of
- all in-memory maps used for shuffles is bounded by this limit, beyond
which the contents will
- begin to spill to disk. If spills are often, consider increasing this
value at the expense of
- <code>spark.storage.memoryFraction</code>.
+ Fraction of Java heap to use for aggregation and cogroups during
shuffles, after accounting for
--- End diff --
This sentence reads a little weird. Move "if spark.shuffle.spill is true,"
to the front?
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