Ted-Jiang commented on code in PR #2156:
URL: https://github.com/apache/arrow-datafusion/pull/2156#discussion_r845198369
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datafusion/physical-expr/src/expressions/in_list.rs:
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@@ -32,13 +33,19 @@ use arrow::{
record_batch::RecordBatch,
};
-use crate::PhysicalExpr;
+use crate::{expressions, PhysicalExpr};
use arrow::array::*;
use arrow::buffer::{Buffer, MutableBuffer};
use datafusion_common::ScalarValue;
use datafusion_common::{DataFusionError, Result};
use datafusion_expr::ColumnarValue;
+/// Size at which to use a Set rather than Vec for `IN` / `NOT IN`
+/// Value chosen to be consistent with Spark
+///
https://github.com/apache/spark/blob/4e95738fdfc334c25f44689ff8c2db5aa7c726f2/sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala#L259-L265
+/// TODO: add switch codeGen in In_List
+static OPTIMIZER_INSET_THRESHOLD: usize = 10;
Review Comment:
`X`: cost time. `Y`: filter value numbers
`Blue`: is use List, `orange`: is use Set.
I did a benchMark in my local, use `select count(*) from orders where
o_orderkey in (x1, x2, ..., xn)`
Obviously, Set has a fixed gradient, List cost time increases with the
parameter number.
The intersection of the two lines is located is between 10～20 （same as Spark
set 10).
So, i decided set `OPTIMIZER_INSET_THRESHOLD ` = 10 align with spark.
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