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| author | Weiqing Yang <yangweiqing001@gmail.com> | 2016-11-17 11:13:22 +0000 |
|---|---|---|
| committer | Sean Owen <sowen@cloudera.com> | 2016-11-17 11:13:22 +0000 |
| commit | a3cac7bd86a6fe8e9b42da1bf580aaeb59378304 (patch) | |
| tree | a42022fbf0d01726f33aa40355cdec13e06e850d | |
| parent | 07b3f045cd6f79b92bc86b3b1b51d3d5e6bd37ce (diff) | |
| download | spark-a3cac7bd86a6fe8e9b42da1bf580aaeb59378304.tar.gz spark-a3cac7bd86a6fe8e9b42da1bf580aaeb59378304.tar.bz2 spark-a3cac7bd86a6fe8e9b42da1bf580aaeb59378304.zip | |
[YARN][DOC] Remove non-Yarn specific configurations from running-on-yarn.md
## What changes were proposed in this pull request?
Remove `spark.driver.memory`, `spark.executor.memory`, `spark.driver.cores`, and `spark.executor.cores` from `running-on-yarn.md` as they are not Yarn-specific, and they are also defined in`configuration.md`.
## How was this patch tested?
Build passed & Manually check.
Author: Weiqing Yang <yangweiqing001@gmail.com>
Closes #15869 from weiqingy/yarnDoc.
| -rw-r--r-- | docs/running-on-yarn.md | 36 |
1 files changed, 0 insertions, 36 deletions
diff --git a/docs/running-on-yarn.md b/docs/running-on-yarn.md index fe0221ce7c..4d1fafc07b 100644 --- a/docs/running-on-yarn.md +++ b/docs/running-on-yarn.md @@ -118,28 +118,6 @@ To use a custom metrics.properties for the application master and executors, upd </td> </tr> <tr> - <td><code>spark.driver.memory</code></td> - <td>1g</td> - <td> - Amount of memory to use for the driver process, i.e. where SparkContext is initialized. - (e.g. <code>1g</code>, <code>2g</code>). - - <br /><em>Note:</em> In client mode, this config must not be set through the <code>SparkConf</code> - directly in your application, because the driver JVM has already started at that point. - Instead, please set this through the <code>--driver-memory</code> command line option - or in your default properties file. - </td> -</tr> -<tr> - <td><code>spark.driver.cores</code></td> - <td><code>1</code></td> - <td> - Number of cores used by the driver in YARN cluster mode. - Since the driver is run in the same JVM as the YARN Application Master in cluster mode, this also controls the cores used by the YARN Application Master. - In client mode, use <code>spark.yarn.am.cores</code> to control the number of cores used by the YARN Application Master instead. - </td> -</tr> -<tr> <td><code>spark.yarn.am.cores</code></td> <td><code>1</code></td> <td> @@ -234,13 +212,6 @@ To use a custom metrics.properties for the application master and executors, upd </td> </tr> <tr> - <td><code>spark.executor.cores</code></td> - <td>1 in YARN mode, all the available cores on the worker in standalone mode.</td> - <td> - The number of cores to use on each executor. For YARN and standalone mode only. - </td> -</tr> -<tr> <td><code>spark.executor.instances</code></td> <td><code>2</code></td> <td> @@ -248,13 +219,6 @@ To use a custom metrics.properties for the application master and executors, upd </td> </tr> <tr> - <td><code>spark.executor.memory</code></td> - <td>1g</td> - <td> - Amount of memory to use per executor process (e.g. <code>2g</code>, <code>8g</code>). - </td> -</tr> -<tr> <td><code>spark.yarn.executor.memoryOverhead</code></td> <td>executorMemory * 0.10, with minimum of 384 </td> <td> |