alexeykudinkin commented on code in PR #5224:
URL: https://github.com/apache/hudi/pull/5224#discussion_r843030033
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hudi-spark-datasource/hudi-spark-common/src/main/scala/org/apache/spark/sql/hudi/DataSkippingUtils.scala:
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@@ -211,10 +211,10 @@ object DataSkippingUtils extends Logging {
.map(colName => GreaterThan(genColNumNullsExpr(colName), Literal(0)))
// Filter "colA is not null"
- // Translates to "colA_nullCount = 0" for index lookup
+ // Translates to "colA_nullCount < colA_valueCount" for index lookup
case IsNotNull(attribute: AttributeReference) =>
getTargetIndexedColumnName(attribute, indexSchema)
- .map(colName => EqualTo(genColNumNullsExpr(colName), Literal(0)))
+ .map(colName => LessThan(genColNumNullsExpr(colName),
genColValueCountExpr))
Review Comment:
Ha! Great question.
The reason is logical fallacy: "colA is not null" != "there is no null in
colA", instead it's "colA contains non-null" (you can check out some other
expressions, there are many expressions in this list that carry such
properties):
- "is null" means that the column has to contain null values (ie
`nullCount` > 0)
- "is not null" means that the column has to contain non-null values (ie
`nullCount` < `valueCount`)
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