houqp commented on a change in pull request #55:
URL: https://github.com/apache/arrow-datafusion/pull/55#discussion_r619864093
##########
File path: datafusion/src/execution/dataframe_impl.rs
##########
@@ -252,7 +252,12 @@ mod tests {
let right = test_table()?.select_columns(&["c1", "c3"])?;
let left_rows = left.collect().await?;
let right_rows = right.collect().await?;
- let join = left.join(right, JoinType::Inner, &["c1"], &["c1"])?;
+ let join = left.join(
+ right,
+ JoinType::Inner,
+ vec![Column::from_name("c1".to_string())],
Review comment:
That's a great idea!
##########
File path: datafusion/src/physical_optimizer/coalesce_batches.rs
##########
@@ -58,7 +59,17 @@ impl PhysicalOptimizerRule for CoalesceBatches {
// See https://issues.apache.org/jira/browse/ARROW-11068
let wrap_in_coalesce = plan_any.downcast_ref::<FilterExec>().is_some()
|| plan_any.downcast_ref::<HashJoinExec>().is_some()
- || plan_any.downcast_ref::<RepartitionExec>().is_some();
+ || {
+ match plan_any.downcast_ref::<RepartitionExec>() {
+ Some(p) => match p.partitioning() {
+ // do not coalesce hash partitions since other plans
like partitioned hash
Review comment:
Good call, I started with handling this in `HashJoinStream`, but
couldn't get it to work in all cases due to a small bug. I took a second look
at my first attempt and noticed it could be fixed by changing 3 characters :P I
have now reverted my change in the coalesce optimizer and added back my initial
fix through
https://github.com/apache/arrow-datafusion/pull/55/commits/696f8e04178fef877a658d0ef08c3c4ceebfcfdf.
Let me know if this fix aligns with what you have in mind. Also I suck at
naming, `preserve_left` is the best I can come up with, suggestions welcome :)
##########
File path: datafusion/src/execution/dataframe_impl.rs
##########
@@ -252,7 +252,12 @@ mod tests {
let right = test_table()?.select_columns(&["c1", "c3"])?;
let left_rows = left.collect().await?;
let right_rows = right.collect().await?;
- let join = left.join(right, JoinType::Inner, &["c1"], &["c1"])?;
+ let join = left.join(
+ right,
+ JoinType::Inner,
+ vec![Column::from_name("c1".to_string())],
Review comment:
Turns out it is not possible to use `Vec<impl Into<Column>>` in the
signature because Dataframe is used as trait object. I changed the signature
back to `&[&str]` for dataframe API and switched to `Vec<impl Into<Column>>` in
the logical plan builder to keep the high level API simple.
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