# Ray 2.35.0 — Ray-2.35.0

- Product: Ray (https://whatsnew.fyi/product/ray)
- Vendor: Anyscale
- Date: 2024-08-28
- Version: 2.35.0
- Original notes: https://github.com/ray-project/ray/releases/tag/ray-2.35.0
- Permalink: https://whatsnew.fyi/product/ray/releases/2.35.0

What's New is an index, not a publisher: every entry below links to the vendor's own release notes, which are the authoritative source. Entries are labelled where they are hand-curated sample data, pre-releases, or drawn from a secondary source such as a developer blog.

Reuse: the summaries, labels and curation here are © What's New. Quote freely with attribution and a link back; wholesale republication of the corpus is not permitted — terms: https://whatsnew.fyi/terms. The vendors' own release notes remain their publishers'.

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- **changed** — pip install ray[all] will no longer include ray[cpp] and the ray-cpp package; use pip install ray[cpp-all] to install everything including ray-cpp
- **changed** — Upgrade supported Arrow version from 16 to 17
- **added** — Add support for reading from Iceberg in Ray Data
- **changed** — Various progress bar UX improvements in Ray Data
- **changed** — Try get size_bytes from metadata and consolidate metadata methods in Ray Data
- **changed** — Improve warning message when read task is large in Ray Data
- **changed** — Extend API to enable passing sample weights via ray.dataset.to_tf
- **changed** — Add a parameter to allow overriding LanceDB scanner options in Ray Data
- **added** — Add failure retry logic for read_lance in Ray Data
- **fixed** — Change type of DataContext.retried_io_errors from tuple to list in Ray Data
- **fixed** — Change pickling log level from warning to debug in Ray Data
- **fixed** — Add validation for shuffle arg in Ray Data
- **fixed** — Fix validation bug when size=0 in ActorPoolStrategy in Ray Data
- **fixed** — Fix exception in async map in Ray Data
- **fixed** — Fix wrong metrics group for Object Store Memory metrics on Ray Data Dashboard
- **fixed** — Handle errors in SplitCoordinator when generating a new epoch in Ray Data
- **changed** — Updates to support xgboost==2.1.0 in Ray Train
- **added** — Add hardware stats in Ray Train
- **fixed** — Fix WandB metric overlap after restore from checkpoint in Tune
- **changed** — Improve handling of replica death and replica unavailability in deployment handle routers before controller restarts replica in Ray Serve
- **deprecated** — Deprecate passing arguments that contain DeploymentResponses in nested objects to downstream deployment handle calls in Ray Serve

**Notice**: Starting from this release, `pip install ray[all]` will not include `ray[cpp]`, and will not install the respective `ray-cpp` package. To install everything that includes `ray-cpp`, one can use `pip install ray[cpp-all]` instead.

#### Ray Libraries<a id="ray-libraries"></a>

##### Ray Data<a id="ray-data"></a>
🎉 New Features:
- Upgrade supported Arrow version from 16 to 17 (#47034)
- Add support for reading from Iceberg (#46889)

💫 Enhancements:
- Various Progress Bar UX improvements (#46816, #46801, #46826, #46692, #46699, #46974, #46928, #47029, #46924, #47120, #47095, #47106)
- Try get `size_bytes` from metadata and consolidate metadata methods (#46862)
- Improve warning message when read task is large (#46942)
- Extend API to enable passing sample weights via ray.dataset.to_tf (#45701)
- Add a parameter to allow overriding LanceDB scanner options (#46975)
- Add failure retry logic for read_lance (#46976)
- Clarify warning for reading old Parquet data (#47049)
- Move datasource implementations to `_internal` subpackage (#46825)
- Handle logs from tensor extensions (#46943)

🔨 Fixes:
- Change type of `DataContext.retried_io_errors` from tuple to list (#46884)
- Make Parquet tests more robust and expose Parquet logic (#46944)
- Change pickling log level from warning to debug (#47032)
- Add validation for shuffle arg (#47055)
- Fix validation bug when size=0 in ActorPoolStrategy (#47072)
- Fix exception in async map (#47110)
- Fix wrong metrics group for `Object Store Memory` metrics on Ray Data Dashboard (#47170)
- Handle errors in SplitCoordinator when generating a new epoch (#47176)

📖 Documentation:
- Auto-gen GroupedData api (#46925)
- Fix signature of `Rule.plan` (#47094)

##### Ray Train<a id="ray-train"></a>
💫 Enhancements:
- [train] Updates to support xgboost==2.1.0 (#46667)
- [train] Add hardware stats (#46719)

##### Ray Tune<a id="ray-tune"></a>
🔨 Fixes:
- [RLlib; Tune] Fix WandB metric overlap after restore from checkpoint. (#46897)

##### Ray Serve<a id="ray-serve"></a>
💫 Enhancements:
- Improved handling of replica death and replica unavailability in deployment handle routers before controller restarts replica (#47008)
- Eagerly create routers in proxy for better GCS fault tolerance (#47031)
- Immediately send ping in router when receiving new replica set (#47053)

🏗 Architecture refactoring:
- Deprecate passing arguments that contain `DeploymentResponses` in nested objects to downstream deployment handle calls (#46806)

##### RLlib<a id="rllib"></a>

🎉 New Features:
- Offline RL on the new API stack:
  - Record offline data (#46818, #47046, #47133, #47155) and support to directly read from episodes. (#46865)
  - RLUnplugged example. (#46792)
  - Progress on BC/MARWIL migration: #44970, #47154, #46799
  - Progress on CQL migration:  #46969, #47105

💫 Enhancements:
- Add ObservationPreprocessor (ConnectorV2). (#47077)

🔨 Fixes:
- New API stack: Fix IMPALA/APPO + LSTM for single- and multi-GPU. (#47132, #47158)
- Various bug fixes: #46898, #47047, #46963, #47021, #46897
- Add more control to Algorithm.add_module/policy methods. (#46932, #46836)

📖 Documentation:
- Example scripts for new API stack:
  - Curiosity (inverse dynamics model-based) RLModule example. (#46841)
  - Add example script for Env with protobuf observation space. (#47071)
- New API stack documentation:
  - Cleanup old API stack docs (rllib-dev.rst). (#47172)
  - Episodes (SingleAgentEpisode). (#46985)
  - Redo rllib-algorithms.rst page. (#46916)

🏗 Architecture refactoring:
- Rename MultiAgent...RLModule... into MultiRL...Module for more generality. (#46840)
- Add learner_only flag to RLModuleConfig/Spec and simplify creation of RLModule specs from algo-config. (#46900)

##### Ray Core<a id="ray-core"></a>
💫 Enhancements:
- Emit total lineage bytes metrics (#46725)
- Adding accelerator type H100 (#46823)
- More structured logging in c

_[Truncated at 4000 characters — full notes: https://github.com/ray-project/ray/releases/tag/ray-2.35.0]_