* Remove worker Wait() call due to SIGCHLD being ignored
* Port _pid_alive to Windows
* Show PID as well as TID in glog
* Update TensorFlow version for Python 3.8 on Windows
* Handle missing Pillow on Windows
* Work around dm-tree PermissionError on Windows
* Fix some lint errors on Windows with Python 3.8
* Simplify torch requirements
* Quiet git clean
* Handle finalizer issues
* Exit with the signal number
* Get rid of wget
* Fix some Windows compatibility issues with tests
Co-authored-by: Mehrdad <noreply@github.com>
* Remove all __future__ imports from RLlib.
* Remove (object) again from tf_run_builder.py::TFRunBuilder.
* Fix 2xLINT warnings.
* Fix broken appo_policy import (must be appo_tf_policy)
* Remove future imports from all other ray files (not just RLlib).
* Remove future imports from all other ray files (not just RLlib).
* Remove future import blocks that contain `unicode_literals` as well.
Revert appo_tf_policy.py to appo_policy.py (belongs to another PR).
* Add two empty lines before Schedule class.
* Put back __future__ imports into determine_tests_to_run.py. Fails otherwise on a py2/print related error.
* Make full use of node
implement local node
fix bugs mentioned in comments
* Add more tests
* Use more specific exception handling
* fix, lint
* fix for py2.x
* Stream logs to driver by default.
* Fix from rebase
* Redirect raylet output independently of worker output.
* Fix.
* Create redis client with services.create_redis_client.
* Suppress Redis connection error at exit.
* Remove thread_safe_client from redis.
* Shutdown driver threads in ray.shutdown().
* Add warning for too many log messages.
* Only stop threads if worker is connected.
* Only stop threads if they exist.
* Remove unnecessary try/excepts.
* Fix
* Only add new logging handler once.
* Increase timeout.
* Fix tempfile test.
* Fix logging in cluster_utils.
* Revert "Increase timeout."
This reverts commit b3846b89040bcd8e583b2e18cb513cb040e71d95.
* Retry longer when connecting to plasma store from node manager and object manager.
* Close pubsub channels to avoid leaking file descriptors.
* Limit log monitor open files to 200.
* Increase plasma connect retries.
* Add comment.
- NodeUpdater gets its' IP in parallel now (no longer in __init__)
- We use persistent connections in SSH (temp folder created only for ray; ControlMaster)
- hash_runtime_conf was performing a pointless hexlify step, wasting time on large files
- We use NodeUpdaterThreads and share the NodeProvider; NodeUpdaterProcess is removed
- AWSNodeProvider caches nodes more aggressively
- NodeProvider now has a shim batch terminate_nodes() call; AWSNodeProvider parallelises it; the autoscaler uses it
- AWSNodeProvider batches EC2 update_tags calls
- Logging changes throughout to provide standardised timing information for profiling
- Pulled out a few unnecessary is_running calls (NodeUpdater will loop waiting for SSH anyway)
## Related issue number
Issue #3599
## What do these changes do?
* distribute load and resource information on a heartbeat
* for each raylet, maintain total and available resource capacity as well as measure of current load
* this PR introduces a new notion of load, defined as a sum of all resource demand induced by queued ready tasks on the local raylet. This provides a heterogeneity-aware measure of load that supersedes legacy Ray's task count as a proxy for load.
* modify the scheduling policy to perform *capacity-based*, *load-aware*, *optimistically concurrent* resource allocation
* perform task spillover to the heartbeating node in response to a heartbeat, implementing heterogeneity-aware late-binding/work-stealing.
## What do these changes do?
1. Separate the log related code to logger.py from services.py.
2. Allow users to modify logging formatter in `ray start`.
## Related issue number
https://github.com/ray-project/ray/pull/2664
ray exec CLUSTER CMD [--screen] [--start] [--stop]
ray attach CLUSTER [--start]
Example:
ray exec sgd.yaml 'source activate tensorflow_p27 && cd ~/ray/python/ray/rllib && ./train.py --run=PPO --env=CartPole-v0' --screen --start --stop
This will in one command create a cluster and run the command on it in a screen session. The screen can later be attached to via ray attach. After the command finishes, the cluster workers will be terminated and the head node stopped.
This PR adds a driver table for the new GCS, which enables cleanup functionality associated with monitoring driver death.
Some testing in `monitor_test.py` is restored, but redis sharding for xray is needed to enable remaining tests.
* Fix documentation indentation.
* Add error table to GCS and push error messages through node manager.
* Add type to error data.
* Linting
* Fix failure_test bug.
* Linting.
* Enable one more test.
* Attempt to fix doc building.
* Restructuring
* Fixes
* More fixes.
* Move current_time_ms function into util.h.
* build_credis.sh: use an up-to-date credis commit.
* build_credis.sh: leveldb is updated, so update build cmds for it
* WIP: make monitor.py issue flush; switch gcs client to use credis
* Experimental: enable automatic GCS flushing with configurable policy.
* Fix linux compilation error
* Fix leveldb build
* Use optimized build for credis
* Address comments
* Attempt to fix tests
* Implement global state API for xray.
* Fix object table.
* Fixes for log structure.
* Implement cluster_resources.
* Add driver task to task table.
* Remove python flatbuffers code
* Get some global state API tests running.
* Python linting.
* Fix linting.
* Fix mock modules for doc
* Copy over flatbuffer bindings.
* Fix for tests.
* Linting
* Fix monitor crash.
Eric Liang