Adding docs for the Scalding interpreter

docs/_includes/themes/zeppelin/_navigation.html

@@ -45,6 +45,7 @@
                 <li><a href="{{BASE_PATH}}/interpreter/lens.html">Lens</a></li>
                 <li><a href="{{BASE_PATH}}/interpreter/markdown.html">Markdown</a></li>
                 <li><a href="{{BASE_PATH}}/interpreter/postgresql.html">Postgresql, hawq</a></li>
+                <li><a href="{{BASE_PATH}}/interpreter/scalding.html">Scalding</a></li>
                 <li><a href="{{BASE_PATH}}/pleasecontribute.html">Shell</a></li>
                 <li><a href="{{BASE_PATH}}/interpreter/spark.html">Spark</a></li>
                 <li><a href="{{BASE_PATH}}/pleasecontribute.html">Tajo</a></li>

docs/docs.md

@@ -41,6 +41,7 @@ limitations under the License.
 * [lens](./interpreter/lens.html)
 * [md](./interpreter/markdown.html)
 * [postgresql, hawq](./interpreter/postgresql.html)
+* [scalding](./interpreter/scalding.html)
 * [sh](./pleasecontribute.html)
 * [spark](./interpreter/spark.html)
 * [tajo](./pleasecontribute.html)

docs/interpreter/scalding.md

@@ -0,0 +1,71 @@
+---
+layout: page
+title: "Scalding Interpreter"
+description: ""
+group: manual
+---
+{% include JB/setup %}
+
+
+## Scalding Interpreter for Apache Zeppelin
+[Scalding](https://github.com/twitter/scalding) is an open source Scala library for writing MapReduce jobs.
+
+### Enabling the Scalding Interpreter
+
+ In a notebook, to enable the **Scalding** interpreter, click on the **Gear** icon,select **Scalding**, and hit **Save**.
+ 
+ <center>
+ ![Interpreter Binding](../assets/themes/zeppelin/img/docs-img/scalding-InterpreterBinding.png)
+
+ ![Interpreter Selection](../assets/themes/zeppelin/img/docs-img/scalding-InterpreterSelection.png)
+ </center>
+
+### Configuring the Interpreter
+Zeppelin comes with a pre-configured Scalding interpreter in local mode, so you do not need to install anything.
+
+### Testing the Interpreter
+
+In example, by using the [Alice in Wonderland](https://gist.github.com/johnynek/a47699caa62f4f38a3e2) tutorial, we will count words (of course!), and plot a graph of the top 10 words in the book.
+
+```
+%scalding
+
+import scala.io.Source
+
+// Get the Alice in Wonderland book from gutenberg.org:
+val alice = Source.fromURL("http://www.gutenberg.org/files/11/11.txt").getLines
+val aliceLineNum = alice.zipWithIndex.toList
+val alicePipe = TypedPipe.from(aliceLineNum)
+
+// Now get a list of words for the book:
+val aliceWords = alicePipe.flatMap { case (text, _) => text.split("\\s+").toList }
+
+// Now lets add a count for each word:
+val aliceWithCount = aliceWords.filterNot(_.equals("")).map { word => (word, 1L) }
+
+// let's sum them for each word:
+val wordCount = aliceWithCount.group.sum
+
+print ("Here are the top 10 words\n")
+val top10 = wordCount
+  .groupAll
+  .sortBy { case (word, count) => -count }
+  .take(10)
+top10.dump
+
+```
+```
+%scalding
+
+val table = "words\t count\n" + top10.toIterator.map{case (k, (word, count)) => s"$word\t$count"}.mkString("\n")
+print("%table " + table)
+
+```
+
+If you click on the icon for the pie chart, you should be able to see a chart like this:
+![Scalding - Pie - Chart](../assets/themes/zeppelin/img/docs-img/scalding-pie.png)
+
+### Current Status & Future Work
+The current implementation of the Scalding interpreter does not support canceling jobs, or fine-grained progress updates. 
+
+The pre-configured Scalding interpreter only supports Scalding in local mode. Hadoop mode for Scalding is currently unsupported, and will be future work (contributions welcome!).