[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 apache#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
tdas · Oct 17, 2014 · e7f4ea8 · e7f4ea8
1 parent 642b246
commit e7f4ea8
Showing 1 changed file with 4 additions and 12 deletions.
diff --git a/docs/configuration.md b/docs/configuration.md
@@ -161,14 +161,6 @@ Apart from these, the following properties are also available, and may be useful
 #### Runtime Environment
 <table class="table">
 <tr><th>Property Name</th><th>Default</th><th>Meaning</th></tr>
-<tr>
-  <td><code>spark.executor.memory</code></td>
-  <td>512m</td>
-  <td>
-    Amount of memory to use per executor process, in the same format as JVM memory strings
-    (e.g. <code>512m</code>, <code>2g</code>).
-  </td>
-</tr>
 <tr>
   <td><code>spark.executor.extraJavaOptions</code></td>
   <td>(none)</td>
@@ -365,7 +357,7 @@ Apart from these, the following properties are also available, and may be useful
   <td><code>spark.ui.port</code></td>
   <td>4040</td>
   <td>
-    Port for your application's dashboard, which shows memory and workload data
+    Port for your application's dashboard, which shows memory and workload data.
   </td>
 </tr>
 <tr>
@@ -880,8 +872,8 @@ Apart from these, the following properties are also available, and may be useful
   <td><code>spark.scheduler.revive.interval</code></td>
   <td>1000</td>
   <td>
-    The interval length for the scheduler to revive the worker resource offers to run tasks.
-    (in milliseconds)
+    The interval length for the scheduler to revive the worker resource offers to run tasks
+    (in milliseconds).
   </td>
 </tr>
 </tr>
@@ -893,7 +885,7 @@ Apart from these, the following properties are also available, and may be useful
     to wait for before scheduling begins. Specified as a double between 0 and 1.
     Regardless of whether the minimum ratio of resources has been reached,
     the maximum amount of time it will wait before scheduling begins is controlled by config 
-    <code>spark.scheduler.maxRegisteredResourcesWaitingTime</code> 
+    <code>spark.scheduler.maxRegisteredResourcesWaitingTime</code>.
   </td>
 </tr>
 <tr>