* Availability after a killed worker
* Workers exit cleanly
* Memory cleanup in photon C tests
* Worker failure in multinode
* Consolidate worker cleanup handlers
* Update the result table before handling a task submission
* KILL_WORKER_TIMEOUT -> KILL_WORKER_TIMEOUT_MILLISECONDS
* Log a warning instead of crashing if no result table entry found
* First pass at a policy to solve deadlock
* Address Robert's comments
* stress test
* unit test
* Fix test cases
* Fix test for python3
* add more logging
* White space.
* Implement actor field for tasks
* Implement actor management in local scheduler.
* initial python frontend for actors
* import actors on worker
* IPython code completion and tests
* prepare creating actors through local schedulers
* add actor id to PyTask
* submit actor calls to local scheduler
* starting to integrate
* simple fix
* Fixes from rebasing.
* more work on python actors
* Improve local scheduler actor handlers.
* Pass actor ID to local scheduler when connecting a client.
* first working version of actors
* fixing actors
* fix creating two copies of the same actor
* fix actors
* remove sleep
* get rid of export synchronization
* update
* insert actor methods into the queue in the right order
* remove print statements
* make it compile again after rebase
* Minor updates.
* fix python actor ids
* Pass actor_id to start_worker.
* add test
* Minor changes.
* Update actor tests.
* Temporary plan for import counter.
* Temporarily fix import counters.
* Fix some tests.
* Fixes.
* Make actor creation non-blocking.
* Fix test?
* Fix actors on Python 2.
* fix rare case.
* Fix python 2 test.
* More tests.
* Small fixes.
* Linting.
* Revert tensorflow version to 0.12.0 temporarily.
* Small fix.
* Enhance inheritance test.
* Refactor local scheduler to remove worker indices.
* Change scheduling state enum to int in all function signatures.
* Bug fix, don't use pointers into a resizable array.
* Remove total_num_workers.
* Fix tests.
* Optimizations:
- Track mapping of missing object to dependent tasks to avoid iterating over task queue
- Perform all fetch requests for missing objects using the same timer
* Fix bug and add regression test
* Record task dependencies and active fetch requests in the same hash table
* fix typo
* Fix memory leak and add test cases for scheduling when dependencies are evicted
* Fix python3 test case
* Minor details.
* Split local scheduler task queue into waiting and dispatch queue
* Fix memory leak
* Add a new task scheduling status for when a task has been queued locally
* Fix global scheduler test case and add task status doc
* Documentation
* Address Philipp's comments
* Move tasks back to the waiting queue if their dependencies become unavailable
* Update existing task table entries instead of overwriting
* Object reconstruction in Photon and C test cases for Photon
* Fix hanging test case on mac
* Remove unnecessary event from photon tests
* make photon_disconnect not leak file descriptors
* fix some of the memory errors
* Fix valgrind
* lint
* Address Robert's comments and add test case for object reconstruction suppression
* Remove OWNER
* Initial scheduler commit
* global scheduler
* add global scheduler
* Implement global scheduler skeleton.
* Formatting.
* Allow local scheduler to be started without a connection to redis so that we can test it without a global scheduler.
* Fail if there are no local schedulers when the global scheduler receives a task.
* Initialize uninitialized value and formatting fix.
* Generalize local scheduler table to db client table.
* Remove code duplication in local scheduler and add flag for whether a task came from the global scheduler or not.
* Queue task specs in the local scheduler instead of tasks.
* Simple global scheduler tests, including valgrind.
* Factor out functions for starting processes.
* Fixes.
* Merge task table and task log
* Fix test in db tests
* Address Robert's comments and some better error checking
* Add a LOG_FATAL that exits the program
