This PR reverts the previous revert with the following minor changes.
Worker capping is off by default.
The cap feature flag is on the for the tests that explicitely require it.
Adds a RAY_DATA_DISABLE_PROGRESS_BARS env var to control the default progress bar behavior. The default value is "0". Setting it to "1" disables progress bars, unless they are reenabled again by the set_progress_bars method.
## Why are these changes needed?
Publisher and subscriber for logs, in driver, dashboard and tests are refactored to make it easier to support using Ray pubsub for logs. Actual support of Ray pubsub for logs will be added later in #20492.
This PR does not intend to introduce any behavior change.
## Related issue number
This PR is the last PR that enables out of order execution. Previous PR: #20176
In this PR specifically, we added an execute_out_of_order option to .options call, which creates the actor with both out_of_order_submit_queue and out_of_order_scheduling queue.
this PR also added @simon-mo original case for testing.
The default block size of 500MiB seems too low for some common workloads, e.g. shuffling 500GB. This creates 1000 blocks which means 1 million intermediate shuffle objects until we implement #20500.
Before this PR, `ds.iter_batches()` would yield no batches if `prefetch_blocks > ds.num_blocks()` was given, since the sliding window semantics were to return no windows if `window_size > len(iterable)`. This PR tweaks the sliding window implementation to always return at least one window, even if the one window is smaller than the given window size.
<!-- Please add a reviewer to the assignee section when you create a PR. If you don't have the access to it, we will shortly find a reviewer and assign them to your PR. -->
## Why are these changes needed?
This PR adds the hiredis dependency for non M1 machines.
This removes the `redis < 4.0` pin.
Since hiredis doesn't have M1 mac wheels yet, so users there will have extra warning messages in their outputs if they use redis 4.0.
<!-- Please give a short summary of the change and the problem this solves. -->
## 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 :(
Co-authored-by: Alex Wu <alex@anyscale.com>
Ray currently does not filter GCP TPU nodes based on the cluster name, resulting in conflicts when multiple ray clusters are running on the same GCP account.
This change updates the TPU behavior to match the GCP compute node behavior, i.e. filtering to TPU nodes for the current cluster.
<!-- Please add a reviewer to the assignee section when you create a PR. If you don't have the access to it, we will shortly find a reviewer and assign them to your PR. -->
## 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?
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.
