docs: update ray integration and move schema evolution doc to a separate doc (#3530)

* Move `object store config` into a new page
* Update ray doc to include official lance sink / source
* Move `schema evolution` to separate doc

Author: eddyxu

docs/conf.py

@@ -55,6 +55,7 @@ def setup(app):
     "numpy": ("https://numpy.org/doc/stable/", None),
     "pyarrow": ("https://arrow.apache.org/docs/", None),
     "pandas": ("https://pandas.pydata.org/pandas-docs/stable/", None),
+    "ray": ("https://docs.ray.io/en/latest/", None),
 }
 
 

docs/index.rst

@@ -43,14 +43,16 @@ Preview releases receive the same level of testing as regular releases.
    :maxdepth: 2
 
    Quickstart <./notebooks/quickstart>
-   ./read_and_write
+   ./introduction/read_and_write
+   ./introduction/schema_evolution
 
 .. toctree::
    :caption: Advanced Usage
    :maxdepth: 1
 
    Lance Format Spec <./format>
    Blob API <./blob>
+   Object Store Configuration <./object_store>
    Performance Guide <./performance>
    Tokenizer <./tokenizer>
    Extension Arrays <./arrays>

docs/integrations/ray.rst

@@ -1,27 +1,35 @@
 Lance ❤️ Ray
 --------------------
 
-Ray effortlessly scale up ML workload to large distributed compute environment.
+`Ray <https://www.anyscale.com/product/open-source/ray>`_ effortlessly scale up ML workload to large distributed
+compute environment.
 
-`Ray Data <https://docs.ray.io/en/latest/data/data.html>`_ can be directly written in Lance format by using the
-:class:`lance.ray.sink.LanceDatasink` class. For example:
+Lance format is one of the official `Ray data sources <https://docs.ray.io/en/latest/data/api/input_output.html#lance>`_:
 
-.. code-block:: bash
+* Lance Data Source :py:meth:`ray.data.read_lance`
+* Lance Data Sink :py:meth:`ray.data.Dataste.write_lance`
 
-    pip install pylance[ray]
+.. testsetup::
 
+    shutil.rmtree("./alice_bob_and_charlie.lance", ignore_errors=True)
 
-``Ray Data Dataset`` can be written to Lance format using the following code:
-
-.. code-block:: python
+.. testcode::
 
     import ray
-    from lance.ray.sink import LanceDatasink
 
     ray.init()
 
-    sink = LanceDatasink("s3://bucket/to/data.lance")
-    ray.data.range(10).map(
-        lambda x: {"id": x["id"], "str": f"str-{x['id']}"}
-    ).write_datasink(sink)
+    data = [
+        {"id": 1, "name": "alice"},
+        {"id": 2, "name": "bob"},
+        {"id": 3, "name": "charlie"}
+    ]
+    ray.data.from_items(data).write_lance("./alice_bob_and_charlie.lance")
+
+    # It can be read via lance directly
+    tbl = lance.dataset("./alice_bob_and_charlie.lance").to_table()
+    assert tbl == pa.Table.from_pylist(data)
 
+    # Or via Ray.data.read_lance
+    pd_df = ray.data.read_lance("./alice_bob_and_charlie.lance").to_pandas()
+    assert tbl == pa.Table.from_pandas(pd_df)