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https://issues.apache.org/jira/browse/SPARK-22236?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16579974#comment-16579974
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Ondrej Kokes commented on SPARK-22236:
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Multiline=true by default would cause some slowdown, but data quality would
either increase or stay the same - it would never go down. So the discussion
there is mostly about performance.
With escape changes, while we would see improvements in data quality on the
input side, *people with preexisting datasets exported by Spark would suffer
(unexpected) data loss,* because the escaping strategy would potentially differ
from the time the data was written.
I think that's a bit more important aspect to consider.
> CSV I/O: does not respect RFC 4180
> ----------------------------------
>
> Key: SPARK-22236
> URL: https://issues.apache.org/jira/browse/SPARK-22236
> Project: Spark
> Issue Type: Improvement
> Components: Input/Output
> Affects Versions: 2.2.0
> Reporter: Ondrej Kokes
> Priority: Minor
>
> When reading or writing CSV files with Spark, double quotes are escaped with
> a backslash by default. However, the appropriate behaviour as set out by RFC
> 4180 (and adhered to by many software packages) is to escape using a second
> double quote.
> This piece of Python code demonstrates the issue
> {code}
> import csv
> with open('testfile.csv', 'w') as f:
> cw = csv.writer(f)
> cw.writerow(['a 2.5" drive', 'another column'])
> cw.writerow(['a "quoted" string', '"quoted"'])
> cw.writerow([1,2])
> with open('testfile.csv') as f:
> print(f.read())
> # "a 2.5"" drive",another column
> # "a ""quoted"" string","""quoted"""
> # 1,2
> spark.read.csv('testfile.csv').collect()
> # [Row(_c0='"a 2.5"" drive"', _c1='another column'),
> # Row(_c0='"a ""quoted"" string"', _c1='"""quoted"""'),
> # Row(_c0='1', _c1='2')]
> # explicitly stating the escape character fixed the issue
> spark.read.option('escape', '"').csv('testfile.csv').collect()
> # [Row(_c0='a 2.5" drive', _c1='another column'),
> # Row(_c0='a "quoted" string', _c1='"quoted"'),
> # Row(_c0='1', _c1='2')]
> {code}
> The same applies to writes, where reading the file written by Spark may
> result in garbage.
> {code}
> df = spark.read.option('escape', '"').csv('testfile.csv') # reading the file
> correctly
> df.write.format("csv").save('testout.csv')
> with open('testout.csv/part-....csv') as f:
> cr = csv.reader(f)
> print(next(cr))
> print(next(cr))
> # ['a 2.5\\ drive"', 'another column']
> # ['a \\quoted\\" string"', '\\quoted\\""']
> {code}
> The culprit is in
> [CSVOptions.scala|https://github.com/apache/spark/blob/7d0a3ef4ced9684457ad6c5924c58b95249419e1/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/csv/CSVOptions.scala#L91],
> where the default escape character is overridden.
> While it's possible to work with CSV files in a "compatible" manner, it would
> be useful if Spark had sensible defaults that conform to the above-mentioned
> RFC (as well as W3C recommendations). I realise this would be a breaking
> change and thus if accepted, it would probably need to result in a warning
> first, before moving to a new default.
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