[SPARK-27472] add user guide for binary file data source

## What changes were proposed in this pull request?

Add user guide for binary file data source.

<img width="826" alt="Screen Shot 2019-04-28 at 10 21 26 PM" src="https://user-images.githubusercontent.com/829644/56877594-0488d300-6a04-11e9-9064-5047dfedd913.png">

## How was this patch tested?

(Please explain how this patch was tested. E.g. unit tests, integration tests, manual tests)
(If this patch involves UI changes, please attach a screenshot; otherwise, remove this)

Please review http://spark.apache.org/contributing.html before opening a pull request.

Closes #24484 from mengxr/SPARK-27472.

Authored-by: Xiangrui Meng <meng@databricks.com>
Signed-off-by: Xiangrui Meng <meng@databricks.com>
This commit is contained in:
Xiangrui Meng 2019-04-29 08:58:56 -07:00
parent 76785cd6f0
commit fbc7942683
2 changed files with 81 additions and 0 deletions

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@ -0,0 +1,80 @@
---
layout: global
title: Binary File Data Source
displayTitle: Binary File Data Source
license: |
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.
---
Since Spark 3.0, Spark supports binary file data source,
which reads binary files and converts each file into a single record that contains the raw content
and metadata of the file.
It produces a DataFrame with the following columns and possibly partition columns:
* `path`: StringType
* `modificationTime`: TimestampType
* `length`: LongType
* `content`: BinaryType
It supports the following read option:
<table class="table">
<tr><th><b>Property Name</b></th><th><b>Default</b></th><th><b>Meaning</b></th></tr>
<tr>
<td><code>pathGlobFilter</code></td>
<td>none (accepts all)</td>
<td>
An optional glob pattern to only include files with paths matching the pattern.
The syntax follows <code>org.apache.hadoop.fs.GlobFilter</code>.
It does not change the behavior of partition discovery.
</td>
</tr>
</table>
To read whole binary files, you need to specify the data source `format` as `binaryFile`.
For example, the following code reads all PNG files from the input directory:
<div class="codetabs">
<div data-lang="scala" markdown="1">
{% highlight scala %}
spark.read.format("binaryFile").option("pathGlobFilter", "*.png").load("/path/to/data")
{% endhighlight %}
</div>
<div data-lang="java" markdown="1">
{% highlight java %}
spark.read().format("binaryFile").option("pathGlobFilter", "*.png").load("/path/to/data");
{% endhighlight %}
</div>
<div data-lang="python" markdown="1">
{% highlight python %}
spark.read.format("binaryFile").option("pathGlobFilter", "*.png").load("/path/to/data")
{% endhighlight %}
</div>
<div data-lang="r" markdown="1">
{% highlight r %}
read.df("/path/to/data", source = "binaryFile", pathGlobFilter = "*.png")
{% endhighlight %}
</div>
</div>
Binary file data source does not support writing a DataFrame back to the original files.

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@ -54,4 +54,5 @@ goes into specific options that are available for the built-in data sources.
* [Compatibility with Databricks spark-avro](sql-data-sources-avro.html#compatibility-with-databricks-spark-avro)
* [Supported types for Avro -> Spark SQL conversion](sql-data-sources-avro.html#supported-types-for-avro---spark-sql-conversion)
* [Supported types for Spark SQL -> Avro conversion](sql-data-sources-avro.html#supported-types-for-spark-sql---avro-conversion)
* [Whole Binary Files](sql-data-sources-binaryFile.html)
* [Troubleshooting](sql-data-sources-troubleshooting.html)