# Ray 1.10.0 — Ray-1.10.0

- Product: Ray (https://whatsnew.fyi/product/ray)
- Vendor: Anyscale
- Date: 2022-02-04
- Version: 1.10.0
- Original notes: https://github.com/ray-project/ray/releases/tag/ray-1.10.0
- Permalink: https://whatsnew.fyi/product/ray/releases/1.10.0

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'.

---

- **added** — Ray Windows support is now in beta with a significant fraction of the Ray test suite passing on Windows
- **added** — runtime_env pip field now installs pip packages in existing environment instead of isolated environment
- **added** — Stats framework for debugging Datasets performance
- **added** — New config helper for enabling the Dask-on-Ray scheduler
- **added** — Support for RE3 exploration algorithm in RLlib for tf
- **added** — TrialCheckpoint class making checkpoint down/upload easier in Tune
- **added** — Random state to BasicVariantGenerator in Tune
- **added** — Multi-objective support for Optuna in Tune
- **added** — Logs can be streamed from job submission server with ray job logs command
- **changed** — Client task options are encoded with pickle instead of json
- **changed** — Allow runtime_env working_dir and py_modules to be pathlib.Path type
- **changed** — Reduce memory usage during conversion to Pandas DataFrame in Ray Data Processing
- **changed** — Refactor runtime_env to use protobuf for multi-language support
- **changed** — Refactor table block structure to support more tabular block formats
- **changed** — Add autoscaler update time to prometheus metrics
- **changed** — Fewer non terminated nodes calls in autoscaler update
- **changed** — Add environment variable to skip local runtime_env garbage collection
- **changed** — Improved reference counting for runtime_env resources
- **fixed** — Fix bug where specifying runtime_env conda/pip per-job using local requirements file with Ray Client on remote cluster didn't work
- **security** — Security fixes for log4j2 bumped to version 2.17.1

##### Highlights

- 🎉 Ray Windows support is now in beta – a significant fraction of the Ray test suite is now passing on Windows. We are eager to learn about your experience with Ray 1.10 on Windows, please file issues you encounter at https://github.com/ray-project/ray/issues. In the upcoming releases we will spend more time on making Ray Serve and Runtime Environment tests pass on Windows and on polishing things.

##### Ray Autoscaler
💫Enhancements:
- Add autoscaler update time to prometheus metrics (#20831)
- Fewer non terminated nodes calls in autoscaler update (#20359, #20623)

🔨 Fixes: 
- GCP TPU autoscaling fix (#20311)
- Scale-down stability fix (#21204)
- Report node launch failure in driver logs (#20814)


##### Ray Client
💫Enhancements
- Client task options are encoded with pickle instead of json (#20930)


##### Ray Core
🎉 New Features:
- `runtime_env`’s `pip` field now installs pip packages in your existing environment instead of installing them in a new isolated environment. (#20341)

🔨 Fixes:
- Fix bug where specifying runtime_env conda/pip per-job using local requirements file using Ray Client on a remote cluster didn’t work (#20855)
- Security fixes for `log4j2` – the `log4j2` version has been bumped to 2.17.1 (#21373)

💫Enhancements:
- Allow runtime_env working_dir and py_modules to be pathlib.Path type (#20853, #20810)
- Add environment variable to skip local runtime_env garbage collection (#21163)
- Change runtime_env error log to debug log (#20875)
- Improved reference counting for runtime_env resources (#20789)

🏗 Architecture refactoring:
- Refactor runtime_env to use protobuf for multi-language support (#19511)

📖Documentation:
- Add more comprehensive runtime_env documentation (#20222, #21131, #20352)


##### Ray Data Processing
🎉 New Features:
- Added stats framework for debugging Datasets performance (#20867, #21070)
- [Dask-on-Ray] New config helper for enabling the Dask-on-Ray scheduler (#21114)

💫Enhancements:
- Reduce memory usage during when converting to a Pandas DataFrame (#20921)

🔨 Fixes:
- Fix slow block evaluation when splitting (#20693)
- Fix boundary sampling concatenation on non-uniform blocks (#20784)
- Fix boolean tensor column slicing (#20905)

🏗 Architecture refactoring:
- Refactor table block structure to support more tabular block formats (#20721)


##### RLlib

🎉 New Features:
- Support for RE3 exploration algorithm (for tf only). (#19551)
- Environment pre-checks, better failure behavior and enhanced environment API. (#20481, #20832, #20868, #20785, #21027, #20811)

🏗 Architecture refactoring:
- Evaluation: Support evaluation setting that makes sure `train` doesn't ever have to wait for `eval` to finish (b/c of long episodes). (#20757); Always attach latest eval metrics. (#21011)
- Soft-deprecate `build_trainer()` utility function in favor of sub-classing `Trainer` directly (and overriding some of its methods). (#20635, #20636, #20633, #20424, #20570, #20571, #20639, #20725)
- Experimental no-flatten option for actions/prev-actions. (#20918)
- Use `SampleBatch` instead of an input dict whenever possible. (#20746)
- Switch off `Preprocessors` by default for `PGTrainer` (experimental). (#21008)
- Toward a Replay Buffer API (cleanups; docstrings; renames; move into `rllib/execution/buffers` dir) (#20552)

📖Documentation:
- Overhaul of auto-API reference pages. (#19786, #20537, #20538, #20486, #20250)
- README and RLlib landing page overhaul (#20249).
- Added example containing code to compute an adapted (time-dependent) GAE used by the PPO algorithm (#20850).

🔨 Fixes:
- Smaller fixes and enhancements: #20704, #20541, #20793, #20743.


##### Tune
🎉 New Features:
- Introduce TrialCheckpoint class, making checkpoint down/upload easie (#20585)
- Add random state to `BasicVariantGenerator` (#20926)
- Multi-objective support for Optuna (#20489)

💫Enhancements:
- Add `set_max_concu

_[Truncated at 4000 characters — full notes: https://github.com/ray-project/ray/releases/tag/ray-1.10.0]_