UBarney commented on code in PR #16210:
URL: https://github.com/apache/datafusion/pull/16210#discussion_r2142968386
##########
datafusion/physical-plan/src/joins/nested_loop_join.rs:
##########
@@ -178,6 +187,18 @@ pub struct NestedLoopJoinExec {
metrics: ExecutionPlanMetricsSet,
/// Cache holding plan properties like equivalences, output partitioning
etc.
cache: PlanProperties,
+ /// Null matching behavior: If `null_equals_null` is true, rows that have
+ /// `null`s in both left and right equijoin columns will be matched.
+ /// Otherwise, rows that have `null`s in the join columns will not be
+ /// matched and thus will not appear in the output.
+ null_equals_null: bool,
+ /// Set of equijoin columns from the relations: `(left_col, right_col)`
+ ///
+ /// This is optional as a nested loop join can be passed a 'on' clause
+ /// in the case that a Hash Join cost is more expensive than a
+ /// nested loop join or when a user would like to pick nested loop
+ /// join by hint
+ on: Option<Vec<(PhysicalExprRef, PhysicalExprRef)>>,
Review Comment:
> we can do the null_equals_null check
We can do this by merging on condition into filter.
For example: filter: `t1.a < t2.a, on: t1.c = t2.c` -> `filter: t1.a < t2.a
and (t1.c = t2.c or (is_null(t1.c) and (is_null(t2.c))))`
> this is how it is implemented for the other joins as well
Hash Joins and Sort-Merge Joins are fundamentally reliant on equality
conditions. Their high-speed mechanisms (hashing, merging) are impossible
without them.
But for nlj separating equality conditions doesn't improve performance
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
To unsubscribe, e-mail: [email protected]
For queries about this service, please contact Infrastructure at:
[email protected]
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
