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[SPARK-3890][Docs]remove redundant spark.executor.memory in doc
Introduced in pwendell@f7e79bc, I'm not sure why we need two spark.executor.memory here. Author: WangTaoTheTonic <[email protected]> Author: WangTao <[email protected]> Closes #2745 from WangTaoTheTonic/redundantconfig and squashes the following commits: e7564dc [WangTao] too long line fdbdb1f [WangTaoTheTonic] trivial workaround d06b6e5 [WangTaoTheTonic] remove redundant spark.executor.memory in doc
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docs/configuration.md

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@@ -161,14 +161,6 @@ Apart from these, the following properties are also available, and may be useful
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#### Runtime Environment
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<table class="table">
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<tr><th>Property Name</th><th>Default</th><th>Meaning</th></tr>
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<tr>
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<td><code>spark.executor.memory</code></td>
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<td>512m</td>
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<td>
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Amount of memory to use per executor process, in the same format as JVM memory strings
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(e.g. <code>512m</code>, <code>2g</code>).
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</td>
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</tr>
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<tr>
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<td><code>spark.executor.extraJavaOptions</code></td>
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<td>(none)</td>
@@ -365,7 +357,7 @@ Apart from these, the following properties are also available, and may be useful
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<td><code>spark.ui.port</code></td>
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<td>4040</td>
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<td>
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Port for your application's dashboard, which shows memory and workload data
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Port for your application's dashboard, which shows memory and workload data.
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</td>
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</tr>
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<tr>
@@ -880,8 +872,8 @@ Apart from these, the following properties are also available, and may be useful
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<td><code>spark.scheduler.revive.interval</code></td>
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<td>1000</td>
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<td>
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The interval length for the scheduler to revive the worker resource offers to run tasks.
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(in milliseconds)
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The interval length for the scheduler to revive the worker resource offers to run tasks
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(in milliseconds).
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</td>
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</tr>
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</tr>
@@ -893,7 +885,7 @@ Apart from these, the following properties are also available, and may be useful
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to wait for before scheduling begins. Specified as a double between 0 and 1.
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Regardless of whether the minimum ratio of resources has been reached,
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the maximum amount of time it will wait before scheduling begins is controlled by config
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<code>spark.scheduler.maxRegisteredResourcesWaitingTime</code>
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<code>spark.scheduler.maxRegisteredResourcesWaitingTime</code>.
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</td>
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</tr>
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<tr>

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