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org.apache.spark.sql.catalyst.optimizer

UnwrapCastInBinaryComparison

object UnwrapCastInBinaryComparison extends Rule[LogicalPlan]

Unwrap casts in binary comparison or In/InSet operations with patterns like following:

- BinaryComparison(Cast(fromExp, toType), Literal(value, toType)) - BinaryComparison(Literal(value, toType), Cast(fromExp, toType)) - In(Cast(fromExp, toType), Seq(Literal(v1, toType), Literal(v2, toType), ...) - InSet(Cast(fromExp, toType), Set(v1, v2, ...))

This rule optimizes expressions with the above pattern by either replacing the cast with simpler constructs, or moving the cast from the expression side to the literal side, which enables them to be optimized away later and pushed down to data sources.

Currently this only handles cases where: 1). fromType (of fromExp) and toType are of numeric types (i.e., short, int, float, decimal, etc) or boolean type 2). fromType can be safely coerced to toType without precision loss (e.g., short to int, int to long, but not long to int, nor int to boolean)

If the above conditions are satisfied, the rule checks to see if the literal value is within range (min, max), where min and max are the minimum and maximum value of fromType, respectively. If this is true then it means we may safely cast value to fromType and thus able to move the cast to the literal side. That is:

cast(fromExp, toType) op value ==> fromExp op cast(value, fromType)

Note there are some exceptions to the above: if casting from value to fromType causes rounding up or down, the above conversion will no longer be valid. Instead, the rule does the following:

if casting value to fromType causes rounding up:

  • cast(fromExp, toType) > value ==> fromExp >= cast(value, fromType)
  • cast(fromExp, toType) >= value ==> fromExp >= cast(value, fromType)
  • cast(fromExp, toType) === value ==> if(isnull(fromExp), null, false)
  • cast(fromExp, toType) <=> value ==> false (if fromExp is deterministic)
  • cast(fromExp, toType) <= value ==> fromExp < cast(value, fromType)
  • cast(fromExp, toType) < value ==> fromExp < cast(value, fromType)

Similarly for the case when casting value to fromType causes rounding down.

If the value is not within range (min, max), the rule breaks the scenario into different cases and try to replace each with simpler constructs.

if value > max, the cases are of following:

  • cast(fromExp, toType) > value ==> if(isnull(fromExp), null, false)
  • cast(fromExp, toType) >= value ==> if(isnull(fromExp), null, false)
  • cast(fromExp, toType) === value ==> if(isnull(fromExp), null, false)
  • cast(fromExp, toType) <=> value ==> false (if fromExp is deterministic)
  • cast(fromExp, toType) <= value ==> if(isnull(fromExp), null, true)
  • cast(fromExp, toType) < value ==> if(isnull(fromExp), null, true)

if value == max, the cases are of following:

  • cast(fromExp, toType) > value ==> if(isnull(fromExp), null, false)
  • cast(fromExp, toType) >= value ==> fromExp == max
  • cast(fromExp, toType) === value ==> fromExp == max
  • cast(fromExp, toType) <=> value ==> fromExp <=> max
  • cast(fromExp, toType) <= value ==> if(isnull(fromExp), null, true)
  • cast(fromExp, toType) < value ==> fromExp =!= max

Similarly for the cases when value == min and value < min.

Further, the above if(isnull(fromExp), null, false) is represented using conjunction and(isnull(fromExp), null), to enable further optimization and filter pushdown to data sources. Similarly, if(isnull(fromExp), null, true) is represented with or(isnotnull(fromExp), null).

For In/InSet operation, first the rule transform the expression to Equals: Seq( EqualTo(Cast(fromExp, toType), Literal(v1, toType)), EqualTo(Cast(fromExp, toType), Literal(v2, toType)), ... ) and using the same rule with BinaryComparison show as before to optimize each EqualTo.

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  1. final def !=(arg0: Any): Boolean
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  3. final def ==(arg0: Any): Boolean
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  5. final def asInstanceOf[T0]: T0
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  8. final def eq(arg0: AnyRef): Boolean
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