Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/17736
yea, much clearer now, and the string literal in Spark 2.0 looks more
reasonable.
For the regex, I think it's unfair to compare `df.filter("value rlike
'^\\x20[\\x20-\\x23]+$'")` with
`df.filter($"value".rlike("^\\x20[\\x20-\\x23]+$"))`, because java string
literal also plays a role here.
Think about a SQL shell, users can write `SELECT ... WHERE value RLIKE
'^\\x20[\\x20-\\x23]+$'`, which is consistent with the java version, so I think
the current SQL parser is corrected.
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