Stephanie Wang ee08c8274b Shard Redis. (#539)
* Implement sharding in the Ray core

* Single node Python modifications to do sharding

* Do the sharding in redis.cc

* Pipe num_redis_shards through start_ray.py and worker.py.

* Use multiple redis shards in multinode tests.

* first steps for sharding ray.global_state

* Fix problem in multinode docker test.

* fix runtest.py

* fix some tests

* fix redis shard startup

* fix redis sharding

* fix

* fix bug introduced by the map-iterator being consumed

* fix sharding bug

* shard event table

* update number of Redis clients to be 64K

* Fix object table tests by flushing shards in between unit tests

* Fix local scheduler tests

* Documentation

* Register shard locations in the primary shard

* Add plasma unit tests back to build

* lint

* lint and fix build

* Fix

* Address Robert's comments

* Refactor start_ray_processes to start Redis shard

* lint

* Fix global scheduler python tests

* Fix redis module test

* Fix plasma test

* Fix component failure test

* Fix local scheduler test

* Fix runtest.py

* Fix global scheduler test for python3

* Fix task_table_test_and_update bug, from actor task table submission race

* Fix jenkins tests.

* Retry Redis shard connections

* Fix test cases

* Convert database clients to DBClient struct

* Fix race condition when subscribing to db client table

* Remove unused lines, add APITest for sharded Ray

* Fix

* Fix memory leak

* Suppress ReconstructionTests output

* Suppress output for APITestSharded

* Reissue task table add/update commands if initial command does not publish to any subscribers.

* fix

* Fix linting.

* fix tests

* fix linting

* fix python test

* fix linting
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Ray
===

.. image:: https://travis-ci.org/ray-project/ray.svg?branch=master
    :target: https://travis-ci.org/ray-project/ray

.. image:: https://readthedocs.org/projects/ray/badge/?version=latest
    :target: http://ray.readthedocs.io/en/latest/?badge=latest

|

Ray is a flexible, high-performance distributed execution framework.

View the `documentation`_.

.. _`documentation`: http://ray.readthedocs.io/en/latest/index.html
S
Description
An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.
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