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native/core/src/execution/planner.rs

Lines changed: 7 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -1209,9 +1209,11 @@ impl PhysicalPlanner {
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}
12101210
OpStruct::Filter(filter) => {
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assert_eq!(children.len(), 1);
1212+
dbg!(filter);
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let (scans, child) = self.create_plan(&children[0], inputs, partition_count)?;
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let predicate =
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self.create_expr(filter.predicate.as_ref().unwrap(), child.schema())?;
1216+
dbg!(&predicate);
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let filter: Arc<dyn ExecutionPlan> =
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match (filter.wrap_child_in_copy_exec, filter.use_datafusion_filter) {
@@ -1223,7 +1225,7 @@ impl PhysicalPlanner {
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predicate,
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Self::wrap_in_copy_exec(Arc::clone(&child.native_plan)),
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)?),
1226-
(false, true) => Arc::new(DataFusionFilterExec::try_new(
1228+
(false, true) => Arc::new(CometFilterExec::try_new(
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predicate,
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Arc::clone(&child.native_plan),
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)?),
@@ -1233,6 +1235,8 @@ impl PhysicalPlanner {
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)?),
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};
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1238+
dbg!(&filter);
1239+
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Ok((
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scans,
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Arc::new(SparkPlan::new(spark_plan.plan_id, filter, vec![child])),
@@ -1363,6 +1367,7 @@ impl PhysicalPlanner {
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))
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}
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OpStruct::NativeScan(scan) => {
1370+
dbg!(scan);
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let data_schema = convert_spark_types_to_arrow_schema(scan.data_schema.as_slice());
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let required_schema: SchemaRef =
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convert_spark_types_to_arrow_schema(scan.required_schema.as_slice());
@@ -1493,6 +1498,7 @@ impl PhysicalPlanner {
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// The `ScanExec` operator will take actual arrays from Spark during execution
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let scan =
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ScanExec::new(self.exec_context_id, input_source, &scan.source, data_types)?;
1501+
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Ok((
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vec![scan.clone()],
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Arc::new(SparkPlan::new(spark_plan.plan_id, Arc::new(scan), vec![])),

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