Ted-Jiang commented on code in PR #2794:
URL: https://github.com/apache/arrow-datafusion/pull/2794#discussion_r907044238
##########
datafusion/expr/src/binary_rule.rs:
##########
@@ -185,6 +186,17 @@ fn comparison_order_coercion(
.or_else(|| null_coercion(lhs_type, rhs_type))
}
+fn string_numeric_coercion(lhs_type: &DataType, rhs_type: &DataType) ->
Option<DataType> {
+ use arrow::datatypes::DataType::*;
+ match (lhs_type, rhs_type) {
Review Comment:
I test in `748b6a65a5fa801595fd80a3c7b2728be3c9cdaa`(not this commit)
```
explain select * from part where p_partkey in (1, 2, '3');
+---------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| plan_type | plan
|
+---------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| logical_plan | Projection: #part.p_partkey, #part.p_name, #part.p_mfgr,
#part.p_brand, #part.p_type, #part.p_size, #part.p_container,
#part.p_retailprice, #part.p_comment
|
| | Filter: #part.p_partkey IN ([Int64(1), Int64(2),
Utf8("3")])
|
| | TableScan: part projection=Some([p_partkey, p_name,
p_mfgr, p_brand, p_type, p_size, p_container, p_retailprice, p_comment]),
partial_filters=[#part.p_partkey IN ([Int64(1), Int64(2), Utf8("3")])]
|
| physical_plan | ProjectionExec: expr=[p_partkey@0 as p_partkey, p_name@1
as p_name, p_mfgr@2 as p_mfgr, p_brand@3 as p_brand, p_type@4 as p_type,
p_size@5 as p_size, p_container@6 as p_container, p_retailprice@7 as
p_retailprice, p_comment@8 as p_comment] |
| | CoalesceBatchesExec: target_batch_size=4096
|
| | FilterExec: p_partkey@0 IN ([Literal { value: Int64(1)
}, Literal { value: Int64(2) }, CastExpr { expr: Literal { value: Utf8("3") },
cast_type: Int64, cast_options: CastOptions { safe: false } }])
|
| | RepartitionExec: partitioning=RoundRobinBatch(16)
|
| | ParquetExec: limit=None,
partitions=[/Users/yangjiang/test-data/tpch-1g-oneFile/part/part-00000-3a3c2777-00d3-4c27-b917-4ff2145123dc-c000.snappy.parquet],
projection=[p_partkey, p_name, p_mfgr, p_brand, p_type, p_size, p_container,
p_retailprice, p_comment] |
| |
|
+---------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
```
`int, int,utf8` cast to -> `int, int, int`,
In my opinion, after apply this patch it will get int, int,utf8` cast to
-> `utf8, utf8, utf8`
I think when list_values_size is large, we will construct a hashSet in
https://github.com/apache/arrow-datafusion/pull/2156, change to `int` will get
better performance in build hasSet, Am i right? 😄
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