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https://issues.apache.org/jira/browse/SPARK-29280?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Nicholas Chammas updated SPARK-29280:
-------------------------------------
Affects Version/s: (was: 3.0.0)
3.1.0
> DataFrameReader should support a compression option
> ---------------------------------------------------
>
> Key: SPARK-29280
> URL: https://issues.apache.org/jira/browse/SPARK-29280
> Project: Spark
> Issue Type: Improvement
> Components: Input/Output
> Affects Versions: 3.1.0
> Reporter: Nicholas Chammas
> Priority: Minor
>
> [DataFrameWriter|http://spark.apache.org/docs/latest/api/python/pyspark.sql.html#pyspark.sql.DataFrameWriter]
> supports a {{compression}} option, but
> [DataFrameReader|http://spark.apache.org/docs/latest/api/python/pyspark.sql.html#pyspark.sql.DataFrameReader]
> doesn't. The lack of a {{compression}} option in the reader causes some
> friction in the following cases:
> # You want to read some data compressed with a codec that Spark does not
> [load by
> default|http://spark.apache.org/docs/latest/configuration.html#compression-and-serialization].
> # You want to read some data with a codec that overrides one of the built-in
> codecs that Spark supports.
> # You want to explicitly instruct Spark on what codec to use on read when it
> will not be able to correctly auto-detect it (e.g. because the file extension
> is [missing,|https://stackoverflow.com/q/52011697/877069]
> [non-standard|https://stackoverflow.com/q/44372995/877069], or
> [incorrect|https://stackoverflow.com/q/49110384/877069]).
> Case #2 came up in SPARK-29102. There is a very handy library called
> [SplittableGzip|https://github.com/nielsbasjes/splittablegzip] that lets you
> load a single gzipped file using multiple concurrent tasks. (You can see the
> details of how it works and why it's useful in the project README and in
> SPARK-29102.)
> To use this codec, I had to set {{io.compression.codecs}}. I guess this is a
> Hadoop filesystem API setting, since it [doesn't appear to be documented by
> Spark|http://spark.apache.org/docs/latest/configuration.html]. Confusingly,
> there is also a setting called {{spark.io.compression.codec}}, which seems to
> be for a different purpose.
> It would be much clearer for the user and more consistent with the writer
> interface if the reader let you directly specify the codec.
> For example, I think all of the following should be possible:
> {code:python}
> spark.read.option('compression', 'lz4').csv(...)
> spark.read.csv(...,
> compression='nl.basjes.hadoop.io.compress.SplittableGzipCodec')
> spark.read.json(..., compression='none')
> {code}
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