From 51b3d41e160a1326a04536241b427e65b39ed8df Mon Sep 17 00:00:00 2001
From: Reynold Xin <rxin@databricks.com>
Date: Tue, 5 May 2015 19:27:30 -0700
Subject: Revert "[SPARK-3454] separate json endpoints for data in the UI"

This reverts commit d49735800db27239c11478aac4b0f2ec9df91a3f.

The commit broke Spark on Windows.
---
 docs/monitoring.md | 74 ------------------------------------------------------
 1 file changed, 74 deletions(-)

(limited to 'docs/monitoring.md')

diff --git a/docs/monitoring.md b/docs/monitoring.md
index 1e0fc15086..8a85928d6d 100644
--- a/docs/monitoring.md
+++ b/docs/monitoring.md
@@ -174,80 +174,6 @@ making it easy to identify slow tasks, data skew, etc.
 
 Note that the history server only displays completed Spark jobs. One way to signal the completion of a Spark job is to stop the Spark Context explicitly (`sc.stop()`), or in Python using the `with SparkContext() as sc:` to handle the Spark Context setup and tear down, and still show the job history on the UI.
 
-## REST API
-
-In addition to viewing the metrics in the UI, they are also available as JSON.  This gives developers
-an easy way to create new visualizations and monitoring tools for Spark.  The JSON is available for
-both running applications, and in the history server.  The endpoints are mounted at `/json/v1`.  Eg.,
-for the history server, they would typically be accessible at `http://<server-url>:18080/json/v1`, and
-for a running application, at `http://localhost:4040/json/v1`.
-
-<table class="table">
-  <tr><th>Endpoint</th><th>Meaning</th></tr>
-  <tr>
-    <td><code>/applications</code></td>
-    <td>A list of all applications</td>
-  </tr>
-  <tr>
-    <td><code>/applications/[app-id]/jobs</code></td>
-    <td>A list of all jobs for a given application</td>
-  </tr>
-  <tr>
-    <td><code>/applications/[app-id]/jobs/[job-id]</code></td>
-    <td>Details for the given job</td>
-  </tr>
-  <tr>
-    <td><code>/applications/[app-id]/stages</code></td>
-    <td>A list of all stages for a given application</td>
-  </tr>
-  <tr>
-    <td><code>/applications/[app-id]/stages/[stage-id]</code></td>
-    <td>A list of all attempts for the given stage</td>
-  </tr>
-  <tr>
-    <td><code>/applications/[app-id]/stages/[stage-id]/[stage-attempt-id]</code></td>
-    <td>Details for the given stage attempt</td>
-  </tr>
-  <tr>
-    <td><code>/applications/[app-id]/stages/[stage-id]/[stage-attempt-id]/taskSummary</code></td>
-    <td>Summary metrics of all tasks in the given stage attempt</td>
-  </tr>
-  <tr>
-    <td><code>/applications/[app-id]/stages/[stage-id]/[stage-attempt-id]/taskList</code></td>
-    <td>A list of all tasks for the given stage attempt</td>
-  </tr>
-  <tr>
-    <td><code>/applications/[app-id]/executors</code></td>
-    <td>A list of all executors for the given application</td>
-  </tr>
-  <tr>
-    <td><code>/applications/[app-id]/storage/rdd</code></td>
-    <td>A list of stored RDDs for the given application</td>
-  </tr>
-  <tr>
-    <td><code>/applications/[app-id]/storage/rdd/[rdd-id]</code></td>
-    <td>Details for the storage status of a given RDD</td>
-  </tr>
-</table>
-
-When running on Yarn, each application has multiple attempts, so `[app-id]` is actually
-`[app-id]/[attempt-id]` in all cases.
-
-These endpoints have been strongly versioned to make it easier to develop applications on top.
- In particular, Spark guarantees:
-
-* Endpoints will never be removed from one version
-* Individual fields will never be removed for any given endpoint
-* New endpoints may be added
-* New fields may be added to existing endpoints
-* New versions of the api may be added in the future at a separate endpoint (eg., `json/v2`).  New versions are *not* required to be backwards compatible.
-* Api versions may be dropped, but only after at least one minor release of co-existing with a new api version
-
-Note that even when examining the UI of a running applications, the `applications/[app-id]` portion is
-still required, though there is only one application available.  Eg. to see the list of jobs for the
-running app, you would go to `http://localhost:4040/json/v1/applications/[app-id]/jobs`.  This is to
-keep the paths consistent in both modes.
-
 # Metrics
 
 Spark has a configurable metrics system based on the 
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