[DOCS] Add docs for AWS S3 IO (#1855)

Integration docs on how to use Daft with AWS S3. Thanks @jaychia for
paving the way with your azure docs.

docs/source/user_guide/integrations.rst

@@ -5,3 +5,4 @@ Integrations
 
     integrations/iceberg
     integrations/microsoft-azure
+    integrations/aws

docs/source/user_guide/integrations/aws.rst

@@ -0,0 +1,53 @@
+Amazon Web Services
+===================
+
+Daft is able to read/write data to/from AWS S3, and understands natively the URL protocol ``s3://`` as referring to data that resides
+in S3.
+
+Authorization/Authentication
+----------------------------
+
+In AWS S3, data is stored under the hierarchy of:
+
+1. Bucket: The container for data storage, which is the top-level namespace for data storage in S3.
+2. Object Key: The unique identifier for a piece of data within a bucket.
+
+URLs to data in S3 come in the form: ``s3://{BUCKET}/{OBJECT_KEY}``.
+
+Rely on Environment
+*******************
+
+You can configure the AWS `CLI <https://docs.aws.amazon.com/cli/latest/userguide/cli-chap-configure.html>`_ to have Daft automatically discover credentials.
+Alternatively, you may specifiy your credentials in `environment variables <https://docs.aws.amazon.com/cli/latest/userguide/cli-configure-envvars.html>`_: ``AWS_ACCESS_KEY_ID``, ``AWS_SECRET_ACCESS_KEY``, and ``AWS_SESSION_TOKEN``.
+
+Please be aware that when doing so in a distributed environment such as Ray, Daft will pick these credentials up from worker machines and thus each worker machine needs to be appropriately provisioned.
+
+If instead you wish to have Daft use credentials from the "driver", you may wish to manually specify your credentials.
+
+Manually specify credentials
+****************************
+
+You may also choose to pass these values into your Daft I/O function calls using an :class:`daft.io.S3Config` config object.
+
+:func:`daft.set_planning_config` is a convenient way to set your :class:`daft.io.IOConfig` as the default config to use on any subsequent Daft method calls.
+
+.. code:: python
+
+    from daft.io import IOConfig, S3Config
+
+    # Supply actual values for the se
+    io_config = IOConfig(s3=S3Config(key_id="key_id", session_token="session_token", secret_key="secret_key"))
+
+    # Globally set the default IOConfig for any subsequent I/O calls
+    daft.set_planning_config(default_io_config=io_config)
+
+    # Perform some I/O operation
+    df = daft.read_parquet("s3://my_bucket/my_path/**/*")
+
+Alternatively, Daft supports overriding the default IOConfig per-operation by passing it into the ``io_config=`` keyword argument. This is extremely flexible as you can
+pass a different :class:`daft.io.S3Config` per function call if you wish!
+
+.. code:: python
+
+    # Perform some I/O operation but override the IOConfig
+    df2 = daft.read_csv("s3://my_bucket/my_other_path/**/*", io_config=io_config)