Livy Interpreter for Apache Zeppelin

Overview

Livy is an open source REST interface for interacting with Spark from anywhere. It supports executing snippets of code or programs in a Spark context that runs locally or in YARN.

  • Interactive Scala, Python and R shells
  • Batch submissions in Scala, Java, Python
  • Multi users can share the same server (impersonation support)
  • Can be used for submitting jobs from anywhere with REST
  • Does not require any code change to your programs

Requirements

Additional requirements for the Livy interpreter are:

  • Spark 1.3 or above.
  • Livy server.

Configuration

We added some common configurations for spark, and you can set any configuration you want. You can find all Spark configurations in here. And instead of starting property with spark. it should be replaced with livy.spark.. Example: spark.driver.memory to livy.spark.driver.memory

Property Default Description
zeppelin.livy.url http://localhost:8998 URL where livy server is running
zeppelin.livy.spark.sql.maxResult 1000 Max number of Spark SQL result to display.
zeppelin.livy.spark.sql.field.truncate true Whether to truncate field values longer than 20 characters or not
zeppelin.livy.session.create_timeout 120 Timeout in seconds for session creation
zeppelin.livy.displayAppInfo true Whether to display app info
zeppelin.livy.pull_status.interval.millis 1000 The interval for checking paragraph execution status
livy.spark.driver.cores Driver cores. ex) 1, 2.
livy.spark.driver.memory Driver memory. ex) 512m, 32g.
livy.spark.executor.instances Executor instances. ex) 1, 4.
livy.spark.executor.cores Num cores per executor. ex) 1, 4.
livy.spark.executor.memory Executor memory per worker instance. ex) 512m, 32g.
livy.spark.dynamicAllocation.enabled Use dynamic resource allocation. ex) True, False.
livy.spark.dynamicAllocation.cachedExecutorIdleTimeout Remove an executor which has cached data blocks.
livy.spark.dynamicAllocation.minExecutors Lower bound for the number of executors.
livy.spark.dynamicAllocation.initialExecutors Initial number of executors to run.
livy.spark.dynamicAllocation.maxExecutors Upper bound for the number of executors.
livy.spark.jars.packages Adding extra libraries to livy interpreter
zeppelin.livy.ssl.trustStore client trustStore file. Used when livy ssl is enabled
zeppelin.livy.ssl.trustStorePassword password for trustStore file. Used when livy ssl is enabled
zeppelin.livy.ssl.trustStoreType JKS type of truststore. Either JKS or PKCS12.
zeppelin.livy.ssl.keyStore client keyStore file. Needed if Livy requires two way SSL authentication.
zeppelin.livy.ssl.keyStorePassword password for keyStore file.
zeppelin.livy.ssl.keyStoreType JKS type of keystore. Either JKS or PKCS12.
zeppelin.livy.ssl.keyPassword password for key in the keyStore file. Defaults to zeppelin.livy.ssl.keyStorePassword.
zeppelin.livy.http.headers key_1: value_1; key_2: value_2 custom http headers when calling livy rest api. Each http header is separated by `;`, and each header is one key value pair where key value is separated by `:`

We remove livy.spark.master in zeppelin-0.7. Because we sugguest user to use livy 0.3 in zeppelin-0.7. And livy 0.3 don't allow to specify livy.spark.master, it enfornce yarn-cluster mode.

Adding External libraries

You can load dynamic library to livy interpreter by set livy.spark.jars.packages property to comma-separated list of maven coordinates of jars to include on the driver and executor classpaths. The format for the coordinates should be groupId:artifactId:version.

Example

Property Example Description
livy.spark.jars.packages io.spray:spray-json_2.10:1.3.1 Adding extra libraries to livy interpreter

How to use

Basically, you can use

spark

%livy.spark
sc.version

pyspark

%livy.pyspark
print "1"

sparkR

%livy.sparkr
hello <- function( name ) {
    sprintf( "Hello, %s", name );
}

hello("livy")

Impersonation

When Zeppelin server is running with authentication enabled, then this interpreter utilizes Livy’s user impersonation feature i.e. sends extra parameter for creating and running a session ("proxyUser": "${loggedInUser}"). This is particularly useful when multi users are sharing a Notebook server.

Apply Zeppelin Dynamic Forms

You can leverage Zeppelin Dynamic Form. Form templates is only avalible for livy sql interpreter.

%livy.sql
select * from products where ${product_id=1}

And creating dynamic formst programmatically is not feasible in livy interpreter, because ZeppelinContext is not available in livy interpreter.

Shared SparkContext

Starting from livy 0.5 which is supported by Zeppelin 0.8.0, SparkContext is shared between scala, python, r and sql. That means you can query the table via %livy.sql when this table is registered in %livy.spark, %livy.pyspark, $livy.sparkr.

FAQ

Livy debugging: If you see any of these in error console

Connect to livyhost:8998 [livyhost/127.0.0.1, livyhost/0:0:0:0:0:0:0:1] failed: Connection refused

Looks like the livy server is not up yet or the config is wrong

Exception: Session not found, Livy server would have restarted, or lost session.

The session would have timed out, you may need to restart the interpreter.

Blacklisted configuration values in session config: spark.master

Edit conf/spark-blacklist.conf file in livy server and comment out #spark.master line.

If you choose to work on livy in apps/spark/java directory in https://github.com/cloudera/hue, copy spark-user-configurable-options.template to spark-user-configurable-options.conf file in livy server and comment out #spark.master.