Using the Programmatic API

Livy provides a programmatic Java/Scala and Python API that allows applications to run code inside Spark without having to maintain a local Spark context. Here shows how to use the Java API.

Add the Livy client dependency to your application’s POM:


Note: Until Livy’s first Apache release you will have to install the livy artifacts locally using mvn install.

To be able to compile code that uses Spark APIs, also add the correspondent Spark dependencies.

To run Spark jobs within your applications, extend org.apache.livy.Job and implement the functionality you need. Here’s an example job that calculates an approximate value for Pi:

import java.util.*;


import org.apache.livy.*;

public class PiJob implements Job<Double>, Function<Integer, Integer>,
  Function2<Integer, Integer, Integer> {

  private final int samples;

  public PiJob(int samples) {
    this.samples = samples;

  public Double call(JobContext ctx) throws Exception {
    List<Integer> sampleList = new ArrayList<Integer>();
    for (int i = 0; i < samples; i++) {
      sampleList.add(i + 1);

    return 4.0d * / samples;

  public Integer call(Integer v1) {
    double x = Math.random();
    double y = Math.random();
    return (x*x + y*y < 1) ? 1 : 0;

  public Integer call(Integer v1, Integer v2) {
    return v1 + v2;


To submit this code using Livy, create a LivyClient instance and upload your application code to the Spark context. Here’s an example of code that submits the above job and prints the computed value:

LivyClient client = new LivyClientBuilder()
  .setURI(new URI(livyUrl))

try {
  System.err.printf("Uploading %s to the Spark context...\n", piJar);
  client.uploadJar(new File(piJar)).get();

  System.err.printf("Running PiJob with %d samples...\n", samples);
  double pi = client.submit(new PiJob(samples)).get();

  System.out.println("Pi is roughly: " + pi);
} finally {

To learn about all the functionality available to applications, read the javadoc documentation for the classes under the api module.