The EclairJS Nashorn API exposes the Spark programming model to JavaScript. EclairJS Nashorn is built on top of Spark's Java API. For a NodeJS implementation of the Spark programming model visit the eclairjs-node project. More detailed information is available in the Eclair Nashorn Wiki.

Prerequisites

• Java 8 SE
• Spark (V1.6.0 built for Hadoop 2.6.0 and later)
• git
• Maven

git clone git@github.com:EclairJS/eclairjs-nashorn.git
mvn package
export SPARK_HOME=<location of Spark binary distribution>

bin/eclairjs.sh examples/word_count.js

or

bin/eclairjs.sh
eclairJS>var list = sc.parallelize([1,10,20,30,40]);
list.count();

    var SparkConf = require('eclairjs/SparkConf');
    var SparkContext = require('eclairjs/SparkContext');
    
    var file = "src/test/resources/dream.txt"; // Should be some file on your system
    var conf = new SparkConf().setAppName("JavaScript word count")
                          .setMaster("local[*]");
    var sparkContext = new SparkContext(conf);
    var rdd = sparkContext.textFile(file).cache();
    var rdd2 = rdd.flatMap(function(sentence) {
        return sentence.split(" ");
    });
    var rdd3 = rdd2.filter(function(word) {
        return word.trim().length > 0;
    });
    var rdd4 = rdd3.mapToPair(function(word) {
        return [word, 1];
    });
    var rdd5 = rdd4.reduceByKey(function(a, b) {
        return a + b;
    });
    var rdd6 = rdd5.mapToPair(function(tuple) {
        return [tuple[1]+0.0, tuple[0]];
    })
    var rdd7 = rdd6.sortByKey(false);
    print("top 10 words = " + rdd7.take(10));

Prerequisites

• Jupyter
• Apache Toree Install Toree pip install toree==0.1.0.dev7 Note where the site-packages are located for example /Library/Python/2.7/site-packages Instructions:

1. Rebuild mvn package -Pnotebook

2. Edit kernel.json and update the following:

<path to Pyton/sitepagages>/toree/bin/run.sh
"SPARK_OPTS": --jars file:<path to nashorn jar>
"SPARK_HOME": <path to spark 1.6.0 distribution>

4. Copy kernel.json to ~/.ipython/kernels/eclair/kernel.json

• Gateway 4.0.0 and higher uses ~/Library/Jupyter/kernels/eclair

5. Create a directory for your notebook mkdir ~/jsNotebook

6. Change to that directory cd ~/jsNotebook

7. Start jupyter ipython notebook

8. A browser will open http://localhost:8888/tree select the new->Spark 1.6.0 (EclairJS)

9. Enter the following code in notebook cell and run

var SparkContext = require('eclairjs/SparkContext');
var sc = new SparkContext("local[*]", "myapp");
var rdd = sc.parallelize([10, 4, 2, 12, 3]);
eval("count = " + rdd.count());

It should be noted that the master branch is used for development and although every effort is made to keep it stable it could be in a slight state of flux depending on what is going on. Please see our releases page if you would like to download a stable version.