wgtmac commented on PR #1028:
URL: https://github.com/apache/parquet-mr/pull/1028#issuecomment-1432527608
> I did a quick test using Spark
>
> ```
> Seq("A", "A",
null).toDF("column").repartition(1).write.mode("overwrite").parquet("t")
> spark.read.parquet("t").where("NOT (column <=> 'A')").show //
this returns null
> spark.read.parquet("t").where("NOT (column = 'A')").show //
this returns empty
> spark.read.parquet("t").where("column IN ('A')").show // this
returns A A
> spark.read.parquet("t").where("column NOT IN ('A')").show //
this returns empty
> ```
>
> If we only has `A` and `null` for `column` and we have predicate `column
not in ('A')`, should we return empty instead of null?
IIUC,
- `col IN (A, B)` is equal to `col = A OR col = B`
- `col NOT IN (A, B)` is equal to `col <> A AND col <> B`. where `col <> A`
means `col IS NOT NULL and col != A`
So my answer to your question above is empty. @huaxingao
It seems that we lose the chance to skip the row group with this fix.
@gszadovszky
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