viirya opened a new pull request, #44480:
URL: https://github.com/apache/spark/pull/44480
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### What changes were proposed in this pull request?
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This patch adds one more case to the optimization rule
`UnwrapCastInBinaryComparison`. The added case handles unwrapping cast in
binary comparison between timestamp and timestamp_ntz types.
### Why are the changes needed?
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We encountered a case that a predicate on a timestamp_ntz column is not
pushed down. The query plan looks like:
```
== Analyzed Logical Plan ==
batch: timestamp
Project [batch#26466]
+- Filter (batch#26466 >= cast(2023-12-21 10:00:00 as timestamp))
+- SubqueryAlias spark_catalog.default.timestamp_view
+- View (`spark_catalog`.`default`.`timestamp_view`, [batch#26466])
+- Project [cast(batch#26467 as timestamp) AS batch#26466]
+- Project [cast(batch#26463 as timestamp) AS batch#26467]
+- SubqueryAlias spark_catalog.default.table_timestamp
+- Relation
spark_catalog.default.table_timestamp[batch#26463] parquet
== Optimized Logical Plan ==
Project [cast(batch#26463 as timestamp) AS batch#26466]
+- Filter (isnotnull(batch#26463) AND (cast(batch#26463 as timestamp) >=
2023-12-21 10:00:00))
+- Relation spark_catalog.default.table_timestamp[batch#26463] parquet
```
The predicate compares a timestamp_ntz column with a literal value. As the
column is wrapped in a cast expression to timestamp type, the literal (string)
is wrapped with a cast to timestamp type. The literal with cast is foldable so
it is evaluated to literal of timestamp earlier. So the predicate becomes
`cast(batch#26463 as timestamp) >= 2023-12-21 10:00:00`. As the cast is in
column side, it cannot be pushed down to data source/table.
We have an optimization rule `UnwrapCastInBinaryComparison` that handles
similar cases but it doesn't cover timestamp types.
After this patch, the query plan looks like:
```
== Analyzed Logical Plan ==
batch: timestamp
Project [batch#26446]
+- Filter (batch#26446 >= cast(2023-12-21 10:00:00 as timestamp))
+- SubqueryAlias spark_catalog.default.timestamp_view
+- View (`spark_catalog`.`default`.`timestamp_view`, [batch#26446])
+- Project [cast(batch#26447 as timestamp) AS batch#26446]
+- Project [cast(batch#26443 as timestamp) AS batch#26447]
+- SubqueryAlias spark_catalog.default.table_timestamp
+- Relation
spark_catalog.default.table_timestamp[batch#26443] parquet
== Optimized Logical Plan ==
Project [cast(batch#26443 as timestamp) AS batch#26446]
+- Filter (isnotnull(batch#26443) AND (batch#26443 >= 2023-12-21 10:00:00))
+- Relation spark_catalog.default.table_timestamp[batch#26443] parquet
```
### Does this PR introduce _any_ user-facing change?
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Yes. Casts between timestamp and timestamp_ntz in binary comparison will be
unwrap if possible.
### How was this patch tested?
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Added unit test.
### Was this patch authored or co-authored using generative AI tooling?
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No
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