[GitHub] [arrow] kiszk commented on a change in pull request #10333: ARROW-12607: [Website] Doc section for Dataset Java bindings

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kiszk commented on a change in pull request #10333:
URL: https://github.com/apache/arrow/pull/10333#discussion_r632973238



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File path: docs/source/java/dataset.rst
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+.. Licensed to the Apache Software Foundation (ASF) under one
+.. or more contributor license agreements.  See the NOTICE file
+.. distributed with this work for additional information
+.. regarding copyright ownership.  The ASF licenses this file
+.. to you under the Apache License, Version 2.0 (the
+.. "License"); you may not use this file except in compliance
+.. with the License.  You may obtain a copy of the License at
+
+..   http://www.apache.org/licenses/LICENSE-2.0
+
+.. Unless required by applicable law or agreed to in writing,
+.. software distributed under the License is distributed on an
+.. "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+.. KIND, either express or implied.  See the License for the
+.. specific language governing permissions and limitations
+.. under the License.
+
+===========
+Dataset
+===========
+
+.. warning::
+
+    Experimental: The Java module ``dataset`` is currently under early development. API might be changed in each release of Apache Arrow until it gets mature.
+
+Dataset is an universal layer in Apache Arrow for querying data in different formats or in different paritionning strategies. Usually the data to be queried is
+supposed to be located from a traditional file system, but Dataset API is not designed only for querying files but can be extended to serve all possible data sources
+such as from inter-process communication or from other network locations, etc. 
+
+Getting Started
+===========
+
+Below shows a simplest example of using Dataset to query a Parquet file in Java:
+
+.. code-block:: Java
+
+    // read data from file /opt/example.parquet
+    String uri = "file:///opt/example.parquet";
+    BufferAllocator allocator = new RootAllocator(Long.MAX_VALUE);
+    DatasetFactory factory = new FileSystemDatasetFactory(allocator, NativeMemoryPool.getDefault(),
+        FileFormat.PARQUET, uri);
+    Dataset dataset = factory.finish();
+    Scanner scanner = dataset.newScan(new ScanOptions(new String[0], 100));
+    List<ArrowRecordBatch> batches = StreamSupport.stream(scanner.scan().spliterator(), false)
+        .flatMap(t -> stream(t.execute()))
+        .collect(Collectors.toList());
+    
+    // do something with read record batches, for example:
+    analyzeArrowData(batches);
+    
+    // finished the analysis of the data, close all resources:
+    AutoCloseables.close(batches);
+    AutoCloseables.close(factory, dataset, scanner);
+
+.. note::
+    ``ArrowRecordBatch`` is a low-level composite Arrow data exchange format that doesn't provide API to read typed data from it directly. It's recommended
+    to use utilities ``VectorLoader`` to load it into a schema aware container ``VectorSchemaRoot`` by which user could be able to access decoded data
+    conveniently in Java.
+
+.. seealso::
+   Load record batches with :doc:`VectorSchemaRoot <vector_schema_root>`.
+
+Schema
+===========
+
+Schema of the data to be queried can be inspected via method ``DatasetFactory#inspect()`` before actually reading it. For example:
+
+.. code-block:: Java
+
+    // read data from local file /opt/example.parquet
+    String uri = "file:///opt/example.parquet";
+    BufferAllocator allocator = new RootAllocator(Long.MAX_VALUE);
+    DatasetFactory factory = new FileSystemDatasetFactory(allocator, NativeMemoryPool.getDefault(),
+        FileFormat.PARQUET, uri);
+    
+    // inspect schema
+    Schema schema = factory.inspect();
+ 
+For some of the data format that is compatible with a user-defined schema, user can use method ``DatasetFactory#inspect(Schema schema)`` to create the dataset:
+
+.. code-block:: Java
+
+    Schema schema = createUserSchema()
+    Dataset dataset = factory.finish(schema);
+
+Otherwise when the non-parameter method ``DatasetFactory#inspect()`` is called, schema will be inferred automatically from data source. The same as the result of
+``DatasetFactory#inspect()``.
+
+Also, if projector is specified during scanning (see next section :ref:`Projection`), the actual schema of output data can be got within method ``Scanner::schema()``:
+
+.. code-block:: Java
+
+    Scanner scanner = dataset.newScan(new ScanOptions(new String[] {"id", "name"}, 100));
+    Schema projectedSchema = scanner.schema();
+ 
+Projection
+===========
+
+User can specify projections in ScanOptions. For ``FileSystemDataset``, only column projection is allowed for now. Which means, only column names

Review comment:
       nit: now. -> now,  ??




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