# Ray 1.7.0 — Ray-1.7.0

- Product: Ray (https://whatsnew.fyi/product/ray)
- Vendor: Anyscale
- Date: 2021-10-07
- Version: 1.7.0
- Original notes: https://github.com/ray-project/ray/releases/tag/ray-1.7.0
- Permalink: https://whatsnew.fyi/product/ray/releases/1.7.0

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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- **added** — Ray SGD v2 is now available in alpha with new APIs focused on ease of use and composability
- **added** — Ray Workflows is now available in alpha for large-scale data science, ML, and long-running business workflows
- **added** — Major enhancements to C++ API with new distributed system building capabilities
- **changed** — Ray Autoscaler now defaults head node type to 0 max_workers
- **added** — Ray Client now forwards ray.init() args to remote server
- **added** — Ray Client now allows multiple client connections from one driver
- **added** — gRPC channel credentials can now be configured from ray.init in Ray Client
- **added** — Ray Client will attempt to recover connections on certain gRPC failures
- **changed** — Ray Client now uses a single RPC to fetch ClientObjectRefs passed in a list
- **fixed** — Fixed syncing files with Docker head node
- **fixed** — Fixed mismatched debug log ID formats in Ray Client
- **added** — Add support for reading partitioned Parquet datasets
- **added** — Add dataset unioning capability
- **added** — Add support for splitting a dataset at row indices
- **added** — Add from_numpy() and to_numpy() APIs for Ray Data Processing
- **added** — Add support for splitting a dataset pipeline at row indices
- **added** — Add Modin integration with from_modin() and to_modin() APIs
- **added** — Add support for datasets with tensor columns
- **added** — Add RayDP (Spark-on-Ray) integration with from_spark() and to_spark() APIs
- **added** — RLlib now supports multi-GPU for DDPG

##### Highlights
- Ray SGD v2 is now in alpha! The v2 version introduces APIs that focus on ease of use and composability. Check out the docs [here](https://docs.ray.io/en/releases-1.7.0/raysgd/v2/raysgd.html), and the migration guide from v1 to v2 [here](https://docs.ray.io/en/releases-1.7.0/raysgd/v2/migration-guide.html).
  - If you are using Ray SGD v2, we’d love to hear your feedback [here](https://forms.gle/PXFcJmHwszCwQhqX7)!
- Ray Workflows is now in alpha! Check out the docs [here](https://docs.ray.io/en/releases-1.7.0/workflows/concepts.html) and try it out for your large-scale data science, ML, and long-running business workflows. Thanks to our early adopters for the feedback so far and the ongoing contributions from IBM Research.
- We have made major enhancements to C++ API! While we are still busy hardening the feature for production usage, please check out the docs [here](https://docs.ray.io/en/latest/index.html#getting-started-with-ray), try it out, and help provide feedback!
##### Ray Autoscaler
💫Enhancements: 
- Improvement to logging and code structure #18180
- Default head node type to 0 max_workers #17757
- Modifications to accommodate custom node providers #17312

🔨 Fixes: 
- Helm chart configuration fixes #17678 #18123
- GCP autoscaler config fix #18653
- Allow attaching to uninitialized head node for debugging #17688
- Syncing files with Docker head node fixed #16515
##### Ray Client
🎉 New Features:
- `ray.init()` args can be forwarded to remote server (#17776)
- Allow multiple client connections from one driver (#17942)
- gRPC channel credentials can now be configured from ray.init (#18425, #18365)
- Ray Client will attempt to recover connections on certain gRPC failures (#18329)

💫Enhancements
- Less confusing client RPC errors (#18278)
- Use a single RPC to fetch ClientObjectRefs passed in a list (#16944)
- Increase timeout for ProxyManager.get_channel (#18350)

🔨 Fixes:
- Fix mismatched debug log ID formats (#17597)
- Fix confusing error messages when client scripts exit (#17969)
##### Ray Core
🎉 New Features:
- Major enhancements in the C++ API!
  - This API library enables you to build a C++ distributed system easily, just like the Python API and the Java API.
  - Run `pip install -U ray[cpp]` to install Ray with C++ API support.
  - Run `ray cpp --help` to learn how to use it.
  - For more details, check out the docs [here](https://docs.ray.io/en/latest/index.html#getting-started-with-ray) and see the tab “C++”.
 
🔨 Fixes:
- Bug fixes for thread-safety / reference count issues / placement group (#18401, #18746, #18312, #17802, #18526, #17863, #18419, #18463, #18193, #17774, #17772, #17670, #17620, #18584, #18646, #17634, #17732)
- Better format for object loss errors / task & actor logs (#18742, #18577, #18105, #18292, #17971, #18166)
- Improved the ray status output for placement groups (#18289, #17892)
- Improved the function export performance (#18284)
- Support more Ray core metrics such as RPC call latencies (#17578)
- Improved error messages and logging for runtime environments (#18451, #18092, #18088, #18084, #18496, #18083)
##### Ray Data Processing
🎉 New Features:
- Add support for reading partitioned Parquet datasets (#17716)
- Add dataset unioning (#17793)
- Add support for splitting a dataset at row indices (#17990)
- Add from_numpy() and to_numpy() APIs (#18146)
- Add support for splitting a dataset pipeline at row indices (#18243)
- Add Modin integration (from_modin() and to_modin()) (#18122)
- Add support for datasets with tensor columns (#18301)
- Add RayDP (Spark-on-Ray) integration (from_spark() and to_spark()) (#17340)

💫Enhancements
- Drop empty tables when read Parquet fragments in order to properly support filter expressions when reading partitioned Parquet datasets (#18098)
- Retry application-level errors in Datasets (#18296)
- Create a directory on write if it doesn’t exist (#18435)
- URL encode paths if

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