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https://issues.apache.org/jira/browse/SPARK-20055?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16193355#comment-16193355
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Andrew Ash commented on SPARK-20055:
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What I would find most useful is a list of available options and their
behaviors, like https://github.com/databricks/spark-csv#features
Even though that project has been in-lined into Apache Spark, that github page
is still the best reference for csv options
> Documentation for CSV datasets in SQL programming guide
> -------------------------------------------------------
>
> Key: SPARK-20055
> URL: https://issues.apache.org/jira/browse/SPARK-20055
> Project: Spark
> Issue Type: Improvement
> Components: Documentation
> Affects Versions: 2.2.0
> Reporter: Hyukjin Kwon
>
> I guess things commonly used and important are documented there rather than
> documenting everything and every option in the programming guide -
> http://spark.apache.org/docs/latest/sql-programming-guide.html.
> It seems JSON datasets
> http://spark.apache.org/docs/latest/sql-programming-guide.html#json-datasets
> are documented whereas CSV datasets are not.
> Nowadays, they are pretty similar in APIs and options. Some options are
> notable for both, In particular, ones such as {{wholeFile}}. Moreover,
> several options such as {{inferSchema}} and {{header}} are important in CSV
> that affect the type/column name of data.
> In that sense, I think we might better document CSV datasets with some
> examples too because I believe reading CSV is pretty much common use cases.
> Also, I think we could also leave some pointers for options of API
> documentations for both (rather than duplicating the documentation).
> So, my suggestion is,
> - Add CSV Datasets section.
> - Add links for options for both JSON and CSV that point each API
> documentation
> - Fix trivial minor fixes together in both sections.
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