[doc] Bump dataset to beta for 1.8 and add backlink to SGD (ray-proje…

…ct#19332)
krfricke · Oct 13, 2021 · 430a5f4 · 430a5f4
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diff --git a/README.rst b/README.rst
@@ -22,7 +22,7 @@ Ray is packaged with the following libraries for accelerating machine learning w
 - `Tune`_: Scalable Hyperparameter Tuning
 - `RLlib`_: Scalable Reinforcement Learning
 - `RaySGD <https://docs.ray.io/en/master/raysgd/raysgd.html>`__: Distributed Training Wrappers
-- `Datasets`_: Flexible Distributed Data Loading (alpha)
+- `Datasets`_: Flexible Distributed Data Loading (beta)
 
 As well as libraries for taking ML and distributed apps to production:
 

diff --git a/doc/source/data/dataset.rst b/doc/source/data/dataset.rst
@@ -5,7 +5,7 @@ Datasets: Flexible Distributed Data Loading
 
 .. tip::
 
- Datasets is available as **alpha** in Ray 1.6+. Please file feature requests and bug reports on GitHub Issues or join the discussion on the `Ray Slack <https://forms.gle/9TSdDYUgxYs8SA9e8>`__.
+ Datasets is available as **beta** in Ray 1.8+. Please file feature requests and bug reports on GitHub Issues or join the discussion on the `Ray Slack <https://forms.gle/9TSdDYUgxYs8SA9e8>`__.
 
 Ray Datasets are the standard way to load and exchange data in Ray libraries and applications. Datasets provide basic distributed data transformations such as ``map``, ``filter``, and ``repartition``, and are compatible with a variety of file formats, datasources, and distributed frameworks.
 
@@ -16,7 +16,7 @@ Ray Datasets are the standard way to load and exchange data in Ray libraries and
 
 Concepts
 --------
-Ray Datasets implement `Distributed Arrow <https://arrow.apache.org/>`__. A Dataset consists of a list of Ray object references to *blocks*. Each block holds a set of items in either an `Arrow table <https://arrow.apache.org/docs/python/data.html#tables>`__ or a Python list (for Arrow incompatible objects). Having multiple blocks in a dataset allows for parallel transformation and ingest of the data.
+Ray Datasets implement `Distributed Arrow <https://arrow.apache.org/>`__. A Dataset consists of a list of Ray object references to *blocks*. Each block holds a set of items in either an `Arrow table <https://arrow.apache.org/docs/python/data.html#tables>`__ or a Python list (for Arrow incompatible objects). Having multiple blocks in a dataset allows for parallel transformation and ingest of the data (e.g., into :ref:`Ray SGD <sgd-v2-docs>` for ML training).
 
 The following figure visualizes a Dataset that has three Arrow table blocks, each block holding 1000 rows each:
 

diff --git a/doc/source/ray-libraries.rst b/doc/source/ray-libraries.rst
@@ -10,7 +10,7 @@ Ray also comes packaged with several libraries solving problems in the machine l
 - :doc:`../tune/index`
 - :ref:`rllib-index`
 - :ref:`sgd-index`
-- :ref:`datasets` (alpha)
+- :ref:`datasets` (beta)
 
 As well as libraries for taking ML and distributed apps to production:
 

diff --git a/doc/source/ray-overview/basics.rst b/doc/source/ray-overview/basics.rst
@@ -16,7 +16,7 @@ On top of **Ray Core** are several libraries for solving problems in machine lea
 - :doc:`../tune/index`
 - :ref:`rllib-index`
 - :ref:`sgd-index`
-- :ref:`datasets` (alpha)
+- :ref:`datasets` (beta)
 
 As well as libraries for taking ML and distributed apps to production: