Github user wzhfy commented on a diff in the pull request:
https://github.com/apache/spark/pull/19783#discussion_r153974940
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/statsEstimation/FilterEstimation.scala
---
@@ -471,37 +508,47 @@ case class FilterEstimation(plan: Filter) extends
Logging {
percent = 1.0
} else {
// 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.
- assert(max > min)
- percent = op match {
- case _: LessThan =>
- if (numericLiteral == max) {
- // If the literal value is right on the boundary, we can minus
the part of the
- // boundary value (1/ndv).
- 1.0 - 1.0 / ndv
- } else {
- (numericLiteral - min) / (max - min)
- }
- case _: LessThanOrEqual =>
- if (numericLiteral == min) {
- // The boundary value is the only satisfying value.
- 1.0 / ndv
- } else {
- (numericLiteral - min) / (max - min)
- }
- case _: GreaterThan =>
- if (numericLiteral == min) {
- 1.0 - 1.0 / ndv
- } else {
- (max - numericLiteral) / (max - min)
- }
- case _: GreaterThanOrEqual =>
- if (numericLiteral == max) {
- 1.0 / ndv
- } else {
- (max - numericLiteral) / (max - min)
- }
+
+ if (colStat.histogram.isEmpty) {
+ // Without advanced statistics like histogram, we assume uniform
data distribution.
+ // We just prorate the adjusted range over the initial range to
compute filter selectivity.
+ assert(max > min)
+ percent = op match {
+ case _: LessThan =>
+ if (numericLiteral == max) {
+ // If the literal value is right on the boundary, we can
minus the part of the
+ // boundary value (1/ndv).
+ 1.0 - 1.0 / ndv
+ } else {
+ (numericLiteral - min) / (max - min)
+ }
+ case _: LessThanOrEqual =>
+ if (numericLiteral == min) {
+ // The boundary value is the only satisfying value.
+ 1.0 / ndv
+ } else {
+ (numericLiteral - min) / (max - min)
+ }
+ case _: GreaterThan =>
+ if (numericLiteral == min) {
+ 1.0 - 1.0 / ndv
+ } else {
+ (max - numericLiteral) / (max - min)
+ }
+ case _: GreaterThanOrEqual =>
+ if (numericLiteral == max) {
+ 1.0 / ndv
+ } else {
+ (max - numericLiteral) / (max - min)
+ }
+ }
+ } else {
+ val numericHistogram = colStat.histogram.get
+ val datum = EstimationUtils.toDecimal(literal.value,
literal.dataType).toDouble
+ val maxDouble = EstimationUtils.toDecimal(colStat.max.get,
literal.dataType).toDouble
+ val minDouble = EstimationUtils.toDecimal(colStat.min.get,
literal.dataType).toDouble
--- End diff --
`max, min` is good enough I think
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