This PR belongs to the stack that enables out of order execution. Previous PR: #20160, Next PR: #20177
In this PR specifically, we implemented a simple out_of_order_scheduling queue which queues the task for execution as soon as the dependency is ready.
Why are these changes needed?
This is the third PR in the stack that supports out or order execution for threaded/async actors. Previous PR #20149 Next PR #20160
At a high level, threaded actor/async actor already don't guarantee execution order, and the current "sequential" order implementation has caused some confusion and inconvenience. Please refer to #19822 for detailed discussion.
In this PR, we implemented the out-of-order of queue that supports out of order execution. Conceptually it's very simple: it sends the requests as soon as the dependency is resolved.
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## Why are these changes needed?
This pin is needed to fix `test_output` on master, which broke when 4.0.0 was released.
It may also fix the windows build (unsure).
## Related issue number
<!-- For example: "Closes #1234" -->
## Checks
- [ ] I've run `scripts/format.sh` to lint the changes in this PR.
- [ ] I've included any doc changes needed for https://docs.ray.io/en/master/.
- [ ] I've made sure the tests are passing. Note that there might be a few flaky tests, see the recent failures at https://flakey-tests.ray.io/
- Testing Strategy
- [ ] Unit tests
- [ ] Release tests
- [ ] This PR is not tested :(
Why are these changes needed?
In the past, there was a regression the placement group creation time gets slower as time goes. I believe the issue is fixed in the master, but this PR verifies if that's actually fixed.
This PR adds a long running test for the placement group. There are 2 purposes of the test.
Make sure the placement group creation / removal doesn't get slower as time goes. The test basically measure the first 20 iteration P50 creation time and run very long iteration. After all iteration, it checks if the p50 creation time is not too slow compared to the initial round.
Make sure placement group removal / creation works consistently for a long time without an issue.
Q: Should we make it a real long running test? (that runs for a day?)
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## Why are these changes needed?
There's one user who has an issue that one of raylets cannot schedule tasks anymore because `num_worker_not_started_by_job_config_not_exist ` > 0.
This PR adds better log messages to figure out if the root cause is the job information is not properly propagated from GCS to raylet through Redis pubsub.
## Related issue number
<!-- For example: "Closes #1234" -->
## Checks
- [ ] I've run `scripts/format.sh` to lint the changes in this PR.
- [ ] I've included any doc changes needed for https://docs.ray.io/en/master/.
- [ ] I've made sure the tests are passing. Note that there might be a few flaky tests, see the recent failures at https://flakey-tests.ray.io/
- Testing Strategy
- [ ] Unit tests
- [ ] Release tests
- [ ] This PR is not tested :(
* Revert "Revert "[RLlib] POC: `PGTrainer` class that works by sub-classing, not `trainer_template.py`. (#20055)" (#20284)"
This reverts commit 246787cdd9.
Co-authored-by: sven1977 <svenmika1977@gmail.com>
## Why are these changes needed?
This is a part of redis removal. This PR remove redis kv in function table.
rpush related code is not updated in this PR.
## Related issue number
This PR adds support for automatic block splitting on read and map transforms, to keep block size bounded to ~500MiB. This avoids potential OOM situations where a map task may consume too much intermediate Python heap memory, or too much object store shared memory for one block.
## Why are these changes needed?
The .boto files are already added to the base image and ACL'ed to root, adding them again during app config build causes permission issues.
## Related issue number
## Why are these changes needed?
Ray wheel size limit is still at 100MB. Removing debug symbols would decrease Ray Linux wheel sizes.
## Related issue number
## Checks
* [xgboost] Fix release test app configs
* Revert full app config
* Update base docker image
* Only change cpu base image
* default
* Pin xgboost to 1.5. in cpu tests
* Remove numpy hack
* Revert one line
Co-authored-by: Amog Kamsetty <amogkamsetty@yahoo.com>
