petern48 commented on code in PR #18481:
URL: https://github.com/apache/datafusion/pull/18481#discussion_r2488987167
##########
datafusion/physical-plan/src/joins/nested_loop_join.rs:
##########
@@ -1455,7 +1484,11 @@ impl NestedLoopJoinStream {
if let Some(batch) = self.output_buffer.next_completed_batch() {
// HACK: this is not part of `BaselineMetrics` yet, so update
it
// manually
- self.join_metrics.output_batches.add(1);
+ self.metrics.join_metrics.output_batches.add(1);
+
+ // Update output rows for selectivity metric
+ let output_rows = batch.num_rows();
+ self.metrics.selectivity.add_part(output_rows);
Review Comment:
Update `output_rows` at flush time.
##########
datafusion/physical-plan/src/joins/nested_loop_join.rs:
##########
@@ -1108,6 +1128,16 @@ impl NestedLoopJoinStream {
Ok(false) => {
// Left exhausted, transition to FetchingRight
self.left_probe_idx = 0;
+
+ // Selectivity Metric: Update total possibilities for the
batch (left_rows * right_rows)
+ if let (Ok(left_data), Some(right_batch)) =
+ (self.get_left_data(), self.current_right_batch.as_ref())
+ {
+ let left_rows = left_data.batch().num_rows();
+ let right_rows = right_batch.num_rows();
+ self.metrics.selectivity.add_total(left_rows * right_rows);
+ }
Review Comment:
I originally tried to get the values and calculate `num_left * num_right` at
the end (in a `drop()` method, similar to how it was done
[here](https://github.com/apache/datafusion/blob/59316de977245efd606b9643520ff89f96657e53/datafusion/physical-plan/src/joins/utils.rs#L1334-L1351)
for `BuildProbeJoinMetrics`. But found it difficult to get the correctness
consistently right since these are all multiple streams.
Instead, I'm doing it incrementally. The basic idea here is that for each
right batch, we `add_total()` the size of the full left buffer times the
num_rows in the current batch. Doing that num_batches times gives us the
equivalent of `num_right * num_left`.
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