Bump ray[default,rllib] from 2.5.0 to 2.9.0

[dependabot[bot]]

Bumps ray[default,rllib] from 2.5.0 to 2.9.0.

Release notes

Sourced from ray[default,rllib]'s releases.

Ray-2.9.0

Release Highlights

• This release contains fixes for the Ray Dashboard. Additional context can be found here: https://www.anyscale.com/blog/update-on-ray-cves-cve-2023-6019-cve-2023-6020-cve-2023-6021-cve-2023-48022-cve-2023-48023 
• Ray Train has now upgraded support for spot node preemption -- allowing Ray Train to handle preemption node failures differently than application errors.
• Ray is now compatible with Pydantic versions =2.5.0, addressing a piece of user feedback we’ve consistently received.
• The Ray Dashboard now has a page for Ray Data to monitor real-time execution metrics.
• Streaming generator is now officially a public API (#41436, #38784). Streaming generator allows writing streaming applications easily on top of Ray via Python generator API and has been used for Ray Serve and Ray data for several releases. See the documentation for details. 
• We’ve added experimental support for new accelerators: Intel GPU (#38553), Intel Gaudi Accelerators (#40561), and Huawei Ascend NPU (#41256).

Ray Libraries

Ray Data

🎉 New Features:

• Add the dashboard for Ray Data to monitor real-time execution metrics and log file for debugging (https://docs.ray.io/en/master/data/monitoring-your-workload.html).
• Introduce concurrency argument to replace ComputeStrategy in map-like APIs (#41461)
• Allow task failures during execution (#41226)
• Support PyArrow 14.0.1 (#41036)
• Add new API for reading and writing Datasource (ray-project/ray#40296)
• Enable group-by over multiple keys in datasets (#37832)
• Add support for multiple group keys in map_groups (#40778)

💫 Enhancements:

• Optimize OpState.outqueue_num_blocks (#41748)
• Improve stall detection for StreamingOutputsBackpressurePolicy (#41637)
• Enable read-only Datasets to be executed on new execution backend (#41466, #41597)
• Inherit block size from downstream ops (#41019)
• Use runtime object memory for scheduling (#41383)
• Add retries to file writes (#41263)
• Make range datasource streaming (#41302)
• Test core performance metrics (#40757)
• Allow ConcurrencyCapBackpressurePolicy._cap_multiplier to be set to 1.0 (#41222)
• Create StatsManager to manage _StatsActor remote calls (#40913)
• Expose max_retry_cnt parameter for BigQuery Write (#41163)
• Add rows outputted to data metrics (#40280)
• Add fault tolerance to remote tasks (#41084)
• Add operator-level dropdown to ray data overview (#40981)
• Avoid slicing too-small blocks (#40840)
• Ray Data jobs detail table (#40756)
• Update default shuffle block size to 1GB (#40839)
• Log progress bar to data logs (#40814)
• Operator level metrics (#40805)

🔨 Fixes:

• Partial fix for Dataset.context not being sealed after creation (#41569)
• Fix the issue that DataContext is not propagated when using streaming_split (#41473)
• Fix Parquet partition filter bug (#40947)
• Fix split read output blocks (#41070)
• Fix BigQueryDatasource fault tolerance bugs (#40986)

... (truncated)

Commits

• 9be5a16 disable StreamingOutputBackpressurePolicy (#42000)
• 15a558e [Core] improve agent health checking mechanism (#41935) (#41964)
• d0300cf [Data] Remove ActorPoolStrategy from documentation (#41948) (#41963)
• 2b1c4f8 [serve] Gracefully stop replicas that fail health checks (#41877) (#41896)
• 7d53e8a [Core] Fix check failure when sync and async tasks are mixed up (#41724) (#41...
• 8c63f91 [core][performance] Only do PlasmaReleaseReply when client knows it's fallbac...
• 2dbb778 [Core] Disallow callable for job submission api (#41788) (#41947)
• 3e9a9ed [Tune; RLlib] Fix tune_rllib client release test. (#41871) (#41951)
• a99bb34 Revert "[release] Fix golden_notebook_torch_tune_serve_test missing argument ...
• 6faef85 [Core] Make PythonGcsClient to be thread safe (#41777) (#41931)
• Additional commits viewable in compare view

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