Github user tanejagagan commented on a diff in the pull request:
https://github.com/apache/spark/pull/17174#discussion_r105333124
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/TypeCoercion.scala
---
@@ -324,14 +324,22 @@ object TypeCoercion {
// We should cast all relative timestamp/date/string comparison into
string comparisons
// This behaves as a user would expect because timestamp strings
sort lexicographically.
// i.e. TimeStamp(2013-01-01 00:00 ...) < "2014" = true
- case p @ BinaryComparison(left @ StringType(), right @ DateType()) =>
- p.makeCopy(Array(left, Cast(right, StringType)))
- case p @ BinaryComparison(left @ DateType(), right @ StringType()) =>
- p.makeCopy(Array(Cast(left, StringType), right))
- case p @ BinaryComparison(left @ StringType(), right @
TimestampType()) =>
- p.makeCopy(Array(left, Cast(right, StringType)))
- case p @ BinaryComparison(left @ TimestampType(), right @
StringType()) =>
- p.makeCopy(Array(Cast(left, StringType), right))
+ // If StringType is foldable then we need to cast String to Date or
Timestamp type
+ // which would give order of magnitude performance gain as well as
preserve the behavior
+ // achieved by expressed above
+ // TimeStamp(2013-01-01 00:00 ...) < Cast( "2014" as timestamp) =
true
+ case p @ BinaryComparison(left @ StringType(), right) if
dateOrTimestampType(right) =>
+ if (left.foldable) {
+ p.makeCopy(Array(Cast(left, right.dataType), right))
--- End diff --
Yes.. You can explicitly cast the string to timestamp and then speed up
will be much faster. By default without casting query just runs fine silently ,
pick up a very bad plan, with no indication to user whatsoever and about order
of magnitude slower
Some of the other issue related to comparison such as` time < 'abc' `will
also run just fine which i think should be fail fast and let user know about
the issue with casting
Other problem is with BI tools which generate these SQLs where user do not
have direct control on the SQL.
We came across this issue when the same query in Impala was running 10
times faster than in Spark and investigation of the that resulted in this bug
and therefore fix
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