lidavidm commented on code in PR #14382:
URL: https://github.com/apache/arrow/pull/14382#discussion_r993805820
##########
docs/source/java/dataset.rst:
##########
@@ -32,31 +32,50 @@ 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.
+.. contents::
+
Getting Started
===============
+Currently supported file formats are:
+
+- Apache Arrow (`.arrow`)
+- Apache ORC (`.orc`)
+- Apache Parquet (`.parquet`)
+- Comma-Separated Values (`.csv`)
+
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(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);
+ ScanOptions options = new ScanOptions(/*batchSize*/ 5);
Review Comment:
For the first example, can we use realistic-ish parameters? A batch size of
5 is far too small.
##########
docs/source/java/dataset.rst:
##########
@@ -32,31 +32,50 @@ 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.
+.. contents::
+
Getting Started
===============
+Currently supported file formats are:
+
+- Apache Arrow (`.arrow`)
Review Comment:
reST uses double backticks.
##########
docs/source/java/dataset.rst:
##########
@@ -65,6 +84,9 @@ Below shows a simplest example of using Dataset to query a
Parquet file in Java:
aware container ``VectorSchemaRoot`` by which user could be able to access
decoded data conveniently in Java.
+ The ``ScanOptions`` `batchSize` argument takes effect only if it is set to
a value
Review Comment:
reST uses double backticks.
##########
docs/source/java/dataset.rst:
##########
@@ -228,3 +250,25 @@ native objects after using. For example:
AutoCloseables.close(factory, dataset, scanner);
If user forgets to close them then native object leakage might be caused.
+
+Development Guidelines
+======================
+
+* Related to the note about ScanOptions batchSize argument: Let's try to read
a Parquet file with gzip compression and 3 row groups:
+
+ .. code-block::
+
+ # Let configure ScanOptions as:
+ ScanOptions options = new ScanOptions(/*batchSize*/ 32768);
+
+ $ parquet-tools meta data4_3rg_gzip.parquet
+ file schema: schema
+ age: OPTIONAL INT64 R:0 D:1
+ name: OPTIONAL BINARY L:STRING R:0 D:1
+ row group 1: RC:4 TS:182 OFFSET:4
+ row group 2: RC:4 TS:190 OFFSET:420
+ row group 3: RC:3 TS:179 OFFSET:838
+
+ In this case, we are configuring ScanOptions batchSize argument equals to
Review Comment:
This is a pretty confusing way to think about it. The batch size parameter
controls the _maximum_ batch size only. If the underlying file has smaller
batches, those will not be consolidated.
##########
docs/source/java/dataset.rst:
##########
@@ -32,31 +32,50 @@ 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.
+.. contents::
+
Getting Started
===============
+Currently supported file formats are:
+
+- Apache Arrow (`.arrow`)
+- Apache ORC (`.orc`)
+- Apache Parquet (`.parquet`)
+- Comma-Separated Values (`.csv`)
+
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(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);
+ ScanOptions options = new ScanOptions(/*batchSize*/ 5);
+ try (
+ BufferAllocator allocator = new RootAllocator();
Review Comment:
The allocator should be within a try-with-resources block (ideally
everything should be)
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