mirror of
https://github.com/vale981/ray
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194 lines
6 KiB
ReStructuredText
194 lines
6 KiB
ReStructuredText
Installing Ray
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==============
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Ray supports Python 2 and Python 3 as well as MacOS and Linux. Windows support
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is planned for the future.
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Latest stable version
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---------------------
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You can install the latest stable version of Ray as follows.
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.. code-block:: bash
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pip install -U ray # also recommended: ray[debug]
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Latest Snapshots (Nightlies)
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----------------------------
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Here are links to the latest wheels (which are built for each commit on the
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master branch). To install these wheels, run the following command:
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.. code-block:: bash
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pip install -U [link to wheel]
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=================== ===================
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Linux MacOS
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=================== ===================
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`Linux Python 3.7`_ `MacOS Python 3.7`_
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`Linux Python 3.6`_ `MacOS Python 3.6`_
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`Linux Python 3.5`_ `MacOS Python 3.5`_
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`Linux Python 2.7`_ `MacOS Python 2.7`_
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=================== ===================
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.. _`Linux Python 3.7`: https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-0.8.0.dev4-cp37-cp37m-manylinux1_x86_64.whl
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.. _`Linux Python 3.6`: https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-0.8.0.dev4-cp36-cp36m-manylinux1_x86_64.whl
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.. _`Linux Python 3.5`: https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-0.8.0.dev4-cp35-cp35m-manylinux1_x86_64.whl
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.. _`Linux Python 2.7`: https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-0.8.0.dev4-cp27-cp27mu-manylinux1_x86_64.whl
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.. _`MacOS Python 3.7`: https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-0.8.0.dev4-cp37-cp37m-macosx_10_6_intel.whl
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.. _`MacOS Python 3.6`: https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-0.8.0.dev4-cp36-cp36m-macosx_10_6_intel.whl
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.. _`MacOS Python 3.5`: https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-0.8.0.dev4-cp35-cp35m-macosx_10_6_intel.whl
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.. _`MacOS Python 2.7`: https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-0.8.0.dev4-cp27-cp27m-macosx_10_6_intel.whl
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Building Ray from Source
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------------------------
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Installing from ``pip`` should be sufficient for most Ray users.
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However, should you need to build from source, follow instructions below for both Linux and MacOS.
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Dependencies
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~~~~~~~~~~~~
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To build Ray, first install the following dependencies. We recommend using
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`Anaconda`_.
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.. _`Anaconda`: https://www.continuum.io/downloads
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For Ubuntu, run the following commands:
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.. code-block:: bash
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sudo apt-get update
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sudo apt-get install -y build-essential curl unzip psmisc
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# If you are not using Anaconda, you need the following.
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sudo apt-get install python-dev # For Python 2.
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sudo apt-get install python3-dev # For Python 3.
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pip install cython==0.29.0
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For MacOS, run the following commands:
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.. code-block:: bash
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brew update
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brew install wget
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pip install cython==0.29.0
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If you are using Anaconda, you may also need to run the following.
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.. code-block:: bash
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conda install libgcc
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Install Ray
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~~~~~~~~~~~
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Ray can be built from the repository as follows.
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.. code-block:: bash
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git clone https://github.com/ray-project/ray.git
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# Install Bazel.
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ray/ci/travis/install-bazel.sh
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cd ray/python
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pip install -e . --verbose # Add --user if you see a permission denied error.
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Docker Source Images
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--------------------
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Run the script to create Docker images.
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.. code-block:: bash
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cd ray
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./build-docker.sh
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This script creates several Docker images:
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- The ``ray-project/deploy`` image is a self-contained copy of code and binaries
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suitable for end users.
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- The ``ray-project/examples`` adds additional libraries for running examples.
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- The ``ray-project/base-deps`` image builds from Ubuntu Xenial and includes
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Anaconda and other basic dependencies and can serve as a starting point for
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developers.
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Review images by listing them:
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.. code-block:: bash
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docker images
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Output should look something like the following:
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.. code-block:: bash
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REPOSITORY TAG IMAGE ID CREATED SIZE
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ray-project/examples latest 7584bde65894 4 days ago 3.257 GB
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ray-project/deploy latest 970966166c71 4 days ago 2.899 GB
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ray-project/base-deps latest f45d66963151 4 days ago 2.649 GB
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ubuntu xenial f49eec89601e 3 weeks ago 129.5 MB
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Launch Ray in Docker
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~~~~~~~~~~~~~~~~~~~~
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Start out by launching the deployment container.
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.. code-block:: bash
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docker run --shm-size=<shm-size> -t -i ray-project/deploy
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Replace ``<shm-size>`` with a limit appropriate for your system, for example
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``512M`` or ``2G``. The ``-t`` and ``-i`` options here are required to support
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interactive use of the container.
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**Note:** Ray requires a **large** amount of shared memory because each object
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store keeps all of its objects in shared memory, so the amount of shared memory
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will limit the size of the object store.
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You should now see a prompt that looks something like:
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.. code-block:: bash
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root@ebc78f68d100:/ray#
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Test if the installation succeeded
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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To test if the installation was successful, try running some tests. This assumes
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that you've cloned the git repository.
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.. code-block:: bash
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python -m pytest -v python/ray/tests/test_mini.py
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Troubleshooting installing Arrow
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--------------------------------
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Some candidate possibilities.
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You have a different version of Flatbuffers installed
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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Arrow pulls and builds its own copy of Flatbuffers, but if you already have
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Flatbuffers installed, Arrow may find the wrong version. If a directory like
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``/usr/local/include/flatbuffers`` shows up in the output, this may be the
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problem. To solve it, get rid of the old version of flatbuffers.
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There is some problem with Boost
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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If a message like ``Unable to find the requested Boost libraries`` appears when
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installing Arrow, there may be a problem with Boost. This can happen if you
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installed Boost using MacPorts. This is sometimes solved by using Brew instead.
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