diff --git a/docs/running-on-yarn.md b/docs/running-on-yarn.md index fe0221ce7c5b65822177998038fd64182e696a8a..4d1fafc07b8fc362c61fc5567dbcf95a5ddca965 100644 --- a/docs/running-on-yarn.md +++ b/docs/running-on-yarn.md @@ -117,28 +117,6 @@ To use a custom metrics.properties for the application master and executors, upd Use lower-case suffixes, e.g. <code>k</code>, <code>m</code>, <code>g</code>, <code>t</code>, and <code>p</code>, for kibi-, mebi-, gibi-, tebi-, and pebibytes, respectively. </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> @@ -233,13 +211,6 @@ To use a custom metrics.properties for the application master and executors, upd Comma-separated list of jars to be placed in the working directory of each executor. </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> @@ -247,13 +218,6 @@ To use a custom metrics.properties for the application master and executors, upd The number of executors for static allocation. With <code>spark.dynamicAllocation.enabled</code>, the initial set of executors will be at least this large. </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>