spark-instrumented-optimizer/docs/sql-data-sources-binaryFile.md at v3.2.0

Gengliang Wang 78a403fab9 [SPARK-27627][SQL] Make option "pathGlobFilter" as a general option for all file sources

## What changes were proposed in this pull request?

### Background:
The data source option `pathGlobFilter` is introduced for Binary file format: https://github.com/apache/spark/pull/24354 , which can be used for filtering file names, e.g. reading `.png` files only while there is `.json` files in the same directory.

### Proposal:
Make the option `pathGlobFilter` as a general option for all file sources. The path filtering should happen in the path globbing on Driver.

### Motivation:
Filtering the file path names in file scan tasks on executors is kind of ugly.

### Impact:
1. The splitting of file partitions will be more balanced.
2. The metrics of file scan will be more accurate.
3. Users can use the option for reading other file sources.

## How was this patch tested?

Unit tests

Closes #24518 from gengliangwang/globFilter.

Authored-by: Gengliang Wang <gengliang.wang@databricks.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>

2019-05-09 08:41:43 +09:00

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layout	title	displayTitle	license
global	Binary File Data Source	Binary File Data Source	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

To read whole binary files, you need to specify the data source format as binaryFile. To load files with paths matching a given glob pattern while keeping the behavior of partition discovery, you can use the general data source option pathGlobFilter. For example, the following code reads all PNG files from the input directory:

{% highlight scala %}

spark.read.format("binaryFile").option("pathGlobFilter", "*.png").load("/path/to/data")

{% endhighlight %}

{% highlight java %}

spark.read().format("binaryFile").option("pathGlobFilter", "*.png").load("/path/to/data");

{% endhighlight %}

{% highlight python %}

spark.read.format("binaryFile").option("pathGlobFilter", "*.png").load("/path/to/data")

{% endhighlight %}

{% highlight r %}

read.df("/path/to/data", source = "binaryFile", pathGlobFilter = "*.png")

{% endhighlight %}

Binary file data source does not support writing a DataFrame back to the original files.

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