Installation#


Prepare the environment#

You can follow the commands in this section to install Java and conda before installing BigDL Orca.

Install Java#

You need to download and install JDK in the environment, and properly set the environment variable JAVA_HOME. JDK8 is highly recommended.

# For Ubuntu
sudo apt-get install openjdk-8-jre
export JAVA_HOME=/usr/lib/jvm/java-8-openjdk-amd64/

# For CentOS
su -c "yum install java-1.8.0-openjdk"
export JAVA_HOME=/usr/lib/jvm/java-1.8.0-openjdk-1.8.0.282.b08-1.el7_9.x86_64/jre

export PATH=$PATH:$JAVA_HOME/bin
java -version  # Verify the version of JDK.

Install Anaconda#

We recommend using conda to prepare the Python environment.

You can follow the steps below to install conda:

# Download Anaconda installation script 
wget -P /tmp https://repo.anaconda.com/archive/Anaconda3-2020.02-Linux-x86_64.sh

# Execute the script to install conda
bash /tmp/Anaconda3-2020.02-Linux-x86_64.sh

# Run this command in your terminal to activate conda
source ~/.bashrc

Then create a Python environment for BigDL Orca:

conda create -n py37 python=3.7  # "py37" is conda environment name, you can use any name you like.
conda activate py37

Install BigDL Orca#

This section demonstrates how to install BigDL Orca via pip, which is the most recommended way.

Notes:

  • Installing BigDL Orca from pip will automatically install pyspark. To avoid possible conflicts, you are highly recommended to unset the environment variable SPARK_HOME if it exists in your environment.

  • If you are using a custom URL of Python Package Index to install the latest version, you may need to check whether the latest packages have been sync’ed with pypi. Or you can add the option -i https://pypi.python.org/simple when pip install to use pypi as the index-url.

To use basic Orca features#

You can install Orca in your created conda environment for distributed data processing, training and inference with the following command:

pip install bigdl-orca  # For the official release version

or for the nightly build version, use:

pip install --pre --upgrade bigdl-orca  # For the latest nightly build version

Note that installing Orca will automatically install the dependencies including bigdl-dllib, bigdl-tf, bigdl-math, packaging, filelock, pyzmq and their dependencies if they haven’t been detected in your conda environment._

To additionally use RayOnSpark#

If you wish to run RayOnSpark or sklearn-style Estimator APIs in Orca with “ray” backend, use the extra key [ray] during the installation above:

pip install bigdl-orca[ray]  # For the official release version

or for the nightly build version, use:

pip install --pre --upgrade bigdl-orca[ray]  # For the latest nightly build version

Note that with the extra key of [ray], pip will automatically install the additional dependencies for RayOnSpark, including ray[default]==1.9.2, aiohttp==3.8.1, async-timeout==4.0.1, aioredis==1.3.1, hiredis==2.0.0, prometheus-client==0.11.0, psutil, setproctitle.

To additionally use AutoML#

If you wish to run AutoML, use the extra key [automl] during the installation above:

pip install bigdl-orca[automl]  # For the official release version

or for the nightly build version, use:

pip install --pre --upgrade bigdl-orca[automl]  # For the latest nightly build version

Note that with the extra key of [automl], pip will automatically install the additional dependencies for distributed hyper-parameter tuning, including ray[tune]==1.9.2, scikit-learn, tensorboard, xgboost together with the dependencies given by the extra key [ray].

To install Orca for Spark3#

By default, Orca is built on top of Spark 2.4.6 (with pyspark==2.4.6 as a dependency). If you want to install Orca built on top of Spark 3.1.3 (with pyspark==3.1.3 as a dependency), you can use the following command instead:

# For the official release version
pip install bigdl-orca-spark3
pip install bigdl-orca-spark3[ray]
pip install bigdl-orca-spark3[automl]

# For the latest nightly build version
pip install --pre --upgrade bigdl-orca-spark3
pip install --pre --upgrade bigdl-orca-spark3[ray]
pip install --pre --upgrade bigdl-orca-spark3[automl]

Note: You should only install Orca built on top of ONE Spark version, but not both. If you want to switch the Spark version, please uninstall Orca cleanly before reinstall.

To uninstall Orca#

# For default Orca built on top of Spark 2.4.6
pip uninstall bigdl-orca bigdl-dllib bigdl-tf bigdl-math bigdl-core

# For Orca built on top of Spark 3.1.3
pip uninstall bigdl-orca-spark3 bigdl-dllib-spark3 bigdl-tf bigdl-math bigdl-core

Note: If necessary, you need to manually uninstall pyspark and other dependencies introduced by Orca.


Download BigDL Orca#

You can also download the BigDL package via the download links below.

2.2.0
2.3.0-SNAPSHOT
2.1.0
Spark 2.4 download download download
Spark 3.1 download download download

Note that SNAPSHOT indicates the latest nightly build version of BigDL.

If you wish to download the BigDL package in the command line, you can run this script instead.