Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/17148#discussion_r104493019
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/statsEstimation/FilterEstimation.scala
---
@@ -414,53 +436,63 @@ case class FilterEstimation(plan: Filter,
catalystConf: CatalystConf) extends Lo
literal: Literal,
update: Boolean): Option[Double] = {
- var percent = 1.0
val colStat = colStatsMap(attr)
- val statsRange =
- Range(colStat.min, colStat.max,
attr.dataType).asInstanceOf[NumericRange]
+ val statsRange = Range(colStat.min, colStat.max,
attr.dataType).asInstanceOf[NumericRange]
+ val max = BigDecimal(statsRange.max)
+ val min = BigDecimal(statsRange.min)
+ val ndv = BigDecimal(colStat.distinctCount)
// determine the overlapping degree between predicate range and
column's range
- val literalValueBD = BigDecimal(literal.value.toString)
+ val numericLiteral = if (literal.dataType == BooleanType) {
+ if (literal.value.asInstanceOf[Boolean]) BigDecimal(1) else
BigDecimal(0)
+ } else {
+ BigDecimal(literal.value.toString)
+ }
val (noOverlap: Boolean, completeOverlap: Boolean) = op match {
case _: LessThan =>
- (literalValueBD <= statsRange.min, literalValueBD > statsRange.max)
+ (numericLiteral <= min, numericLiteral > max)
case _: LessThanOrEqual =>
- (literalValueBD < statsRange.min, literalValueBD >= statsRange.max)
+ (numericLiteral < min, numericLiteral >= max)
case _: GreaterThan =>
- (literalValueBD >= statsRange.max, literalValueBD < statsRange.min)
+ (numericLiteral >= max, numericLiteral < min)
case _: GreaterThanOrEqual =>
- (literalValueBD > statsRange.max, literalValueBD <= statsRange.min)
+ (numericLiteral > max, numericLiteral <= min)
}
+ var percent = BigDecimal(1.0)
if (noOverlap) {
percent = 0.0
} else if (completeOverlap) {
percent = 1.0
} else {
- // this is partial overlap case
- val literalDouble = literalValueBD.toDouble
- val maxDouble = BigDecimal(statsRange.max).toDouble
- val minDouble = BigDecimal(statsRange.min).toDouble
-
+ // This is the partial overlap case:
// Without advanced statistics like histogram, we assume uniform
data distribution.
// We just prorate the adjusted range over the initial range to
compute filter selectivity.
- // For ease of computation, we convert all relevant numeric values
to Double.
+ assert(max > min)
percent = op match {
case _: LessThan =>
- (literalDouble - minDouble) / (maxDouble - minDouble)
+ if (numericLiteral == max) {
--- End diff --
can you add some comments to explain this special case?
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