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apache / incubator-livy / 1bbefe601641aa4db74dbed1f7faf458b9a70a63
commit1bbefe601641aa4db74dbed1f7faf458b9a70a63[log] [tgz]
authorjerryshao <sshao@hortonworks.com>Fri Oct 20 11:10:43 2017 +0800
committerjerryshao <sshao@hortonworks.com>Fri Oct 20 11:10:43 2017 +0800
tree4ca33e3bc9a79f885989b010b22e93f7f23afa79
parent19004b51a14de68a34526bab22b1b64a2376f042 [diff]
[LIVY-411][REPL] Fix session cannot start issue when python or r package is missing

## What changes were proposed in this pull request?

https://issues.apache.org/jira/browse/LIVY-411

In Livy 0.5.0, we supported multiple languages in one session, but it requires that all the packages should be available before session creation, such as R package and Python package, otherwise session will be failed to create. However, in some cases python or R package may be missing in Spark distro, this will make Livy fail to creation interactive session.

To fix this issue, we should not force such restriction on session creation, but delay the check until related interpreter is used. If such packaging is missing, we should make the related execution failure and return user the cause of issue, but don't affect other correctly started interpreters.

## How was this patch tested?

Existing test and manually verification on local cluster.

Author: jerryshao <sshao@hortonworks.com>

Closes #56 from jerryshao/LIVY-411.
7 files changed
tree: 4ca33e3bc9a79f885989b010b22e93f7f23afa79
  1. .github/
  2. api/
  3. assembly/
  4. bin/
  5. client-common/
  6. client-http/
  7. conf/
  8. core/
  9. coverage/
  10. dev/
  11. docs/
  12. examples/
  13. integration-test/
  14. python-api/
  15. repl/
  16. rsc/
  17. scala/
  18. scala-api/
  19. server/
  20. test-lib/
  21. .gitignore
  22. .rat-excludes
  23. .travis.yml
  24. checkstyle-suppressions.xml
  25. checkstyle.xml
  26. DISCLAIMER
  27. LICENSE
  28. NOTICE
  29. pom.xml
  30. README.md
  31. scalastyle.xml
README.md

Apache Livy

Build Status

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

  • Interactive Scala, Python and R shells
  • Batch submissions in Scala, Java, Python
  • Multiple 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

Pull requests are welcomed! But before you begin, please check out the Contributing section on the Community page of our website.

Online Documentation

Guides and documentation on getting started using Livy, example code snippets, and Livy API documentation can be found at livy.incubator.apache.org.

Before Building Livy

To build Livy, you will need:

Debian/Ubuntu:

  • mvn (from maven package or maven3 tarball)
  • openjdk-7-jdk (or Oracle Java7 jdk)
  • Python 2.6+
  • R 3.x

Redhat/CentOS:

  • mvn (from maven package or maven3 tarball)
  • java-1.7.0-openjdk (or Oracle Java7 jdk)
  • Python 2.6+
  • R 3.x

MacOS:

  • Xcode command line tools
  • Oracle's JDK 1.7+
  • Maven (Homebrew)
  • Python 2.6+
  • R 3.x

Required python packages for building Livy:

  • cloudpickle
  • requests
  • requests-kerberos
  • flake8
  • flaky
  • pytest

To run Livy, you will also need a Spark installation. You can get Spark releases at https://spark.apache.org/downloads.html.

Livy requires at least Spark 1.6 and supports both Scala 2.10 and 2.11 builds of Spark, Livy will automatically pick repl dependencies through detecting the Scala version of Spark.

Livy also supports Spark 2.0+ for both interactive and batch submission, you could seamlessly switch to different versions of Spark through SPARK_HOME configuration, without needing to rebuild Livy.

Building Livy

Livy is built using Apache Maven. To check out and build Livy, run:

git clone https://github.com/apache/incubator-livy.git
cd livy
mvn package

By default Livy is built against Apache Spark 1.6.2, but the version of Spark used when running Livy does not need to match the version used to build Livy. Livy internally uses reflection to mitigate the gaps between different Spark versions, also Livy package itself does not contain a Spark distribution, so it will work with any supported version of Spark (Spark 1.6+) without needing to rebuild against specific version of Spark.