spark git commit: [SPARK-21069][SS][DOCS] Add rate source to programming guide.

[zs...@apache.org]

Repository: spark
Updated Branches:
  refs/heads/master 9760c15ac -> d0bfc6733


[SPARK-21069][SS][DOCS] Add rate source to programming guide.

## What changes were proposed in this pull request?

SPARK-20979 added a new structured streaming source: Rate source. This patch adds the corresponding documentation to programming guide.

## How was this patch tested?

Tested by running jekyll locally.

Author: Prashant Sharma <pr...@apache.org>
Author: Prashant Sharma <pr...@in.ibm.com>

Closes #18562 from ScrapCodes/spark-21069/rate-source-docs.


Project: http://git-wip-us.apache.org/repos/asf/spark/repo
Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/d0bfc673
Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/d0bfc673
Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/d0bfc673

Branch: refs/heads/master
Commit: d0bfc6733521709e453d643582df2bdd68f28de7
Parents: 9760c15
Author: Prashant Sharma <pr...@apache.org>
Authored: Fri Jul 7 23:33:12 2017 -0700
Committer: Shixiong Zhu <sh...@databricks.com>
Committed: Fri Jul 7 23:33:12 2017 -0700

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 docs/structured-streaming-programming-guide.md | 15 +++++++++++++++
 1 file changed, 15 insertions(+)
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http://git-wip-us.apache.org/repos/asf/spark/blob/d0bfc673/docs/structured-streaming-programming-guide.md
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diff --git a/docs/structured-streaming-programming-guide.md b/docs/structured-streaming-programming-guide.md
index 3bc377c..8f64faa 100644
--- a/docs/structured-streaming-programming-guide.md
+++ b/docs/structured-streaming-programming-guide.md
@@ -499,6 +499,8 @@ There are a few built-in sources.
 
   - **Socket source (for testing)** - Reads UTF8 text data from a socket connection. The listening server socket is at the driver. Note that this should be used only for testing as this does not provide end-to-end fault-tolerance guarantees. 
 
+  - **Rate source (for testing)** - Generates data at the specified number of rows per second, each output row contains a `timestamp` and `value`. Where `timestamp` is a `Timestamp` type containing the time of message dispatch, and `value` is of `Long` type containing the message count, starting from 0 as the first row. This source is intended for testing and benchmarking.
+
 Some sources are not fault-tolerant because they do not guarantee that data can be replayed using 
 checkpointed offsets after a failure. See the earlier section on 
 [fault-tolerance semantics](#fault-tolerance-semantics).
@@ -547,6 +549,19 @@ Here are the details of all the sources in Spark.
     <td></td>
   </tr>
   <tr>
+    <td><b>Rate Source</b></td>
+    <td>
+        <code>rowsPerSecond</code> (e.g. 100, default: 1): How many rows should be generated per second.<br/><br/>
+        <code>rampUpTime</code> (e.g. 5s, default: 0s): How long to ramp up before the generating speed becomes <code>rowsPerSecond</code>. Using finer granularities than seconds will be truncated to integer seconds. <br/><br/>
+        <code>numPartitions</code> (e.g. 10, default: Spark's default parallelism): The partition number for the generated rows. <br/><br/>
+        
+        The source will try its best to reach <code>rowsPerSecond</code>, but the query may be resource constrained, and <code>numPartitions</code> can be tweaked to help reach the desired speed.
+    </td>
+    <td>Yes</td>
+    <td></td>
+  </tr>
+
+  <tr>
     <td><b>Kafka Source</b></td>
     <td>
         See the <a href="structured-streaming-kafka-integration.html">Kafka Integration Guide</a>.


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