alamb commented on code in PR #4447:
URL: https://github.com/apache/arrow-datafusion/pull/4447#discussion_r1038761919
##########
datafusion/optimizer/src/push_down_filter.rs:
##########
@@ -881,40 +880,30 @@ mod tests {
}
#[test]
- fn filter_keep_agg() -> Result<()> {
- let table_scan = test_table_scan()?;
- let plan = LogicalPlanBuilder::from(table_scan)
- .aggregate(vec![col("a")], vec![sum(col("b")).alias("b")])?
- .filter(col("b").gt(lit(10i64)))?
+ fn push_agg_need_replace_expr() -> Result<()> {
+ let plan = LogicalPlanBuilder::from(test_table_scan()?)
+ .aggregate(vec![add(col("b"), col("a"))], vec![sum(col("a")),
col("b")])?
+ .filter(col("test.b + test.a").gt(lit(10i64)))?
.build()?;
- // filter of aggregate is after aggregation since they are
non-commutative
- let expected = "\
- Filter: b > Int64(10)\
- \n Aggregate: groupBy=[[test.a]], aggr=[[SUM(test.b) AS b]]\
- \n TableScan: test";
+ let expected =
+ "Aggregate: groupBy=[[test.b + test.a]], aggr=[[SUM(test.a),
test.b]]\
+ \n Filter: test.b + test.a > Int64(10)\
+ \n TableScan: test";
assert_optimized_plan_eq(&plan, expected)
}
#[test]
- fn filter_keep_partial_agg() -> Result<()> {
+ fn filter_keep_agg() -> Result<()> {
let table_scan = test_table_scan()?;
- let f1 = col("c").eq(lit(1i64)).and(col("b").gt(lit(2i64)));
- let f2 = col("c").eq(lit(1i64)).and(col("b").gt(lit(3i64)));
- let filter = f1.or(f2);
let plan = LogicalPlanBuilder::from(table_scan)
.aggregate(vec![col("a")], vec![sum(col("b")).alias("b")])?
- .filter(filter)?
+ .filter(col("b").gt(lit(10i64)))?
.build()?;
// filter of aggregate is after aggregation since they are
non-commutative
- // (c =1 AND b > 2) OR (c = 1 AND b > 3)
- // rewrite to CNF
- // (c = 1 OR c = 1) [can pushDown] AND (c = 1 OR b > 3) AND (b > 2 OR
C = 1) AND (b > 2 OR b > 3)
-
let expected = "\
- Filter: (test.c = Int64(1) OR b > Int64(3)) AND (b > Int64(2) OR
test.c = Int64(1)) AND (b > Int64(2) OR b > Int64(3))\
- \n Aggregate: groupBy=[[test.a]], aggr=[[SUM(test.b) AS b]]\
- \n Filter: test.c = Int64(1) OR test.c = Int64(1)\
- \n TableScan: test";
+ Filter: b > Int64(10)\
Review Comment:
I agree this new plan is correct
##########
datafusion/optimizer/src/push_down_filter.rs:
##########
@@ -641,20 +633,27 @@ impl OptimizerRule for PushDownFilter {
let mut keep_predicates = vec![];
let mut push_predicates = vec![];
for expr in predicates {
- let columns = expr.to_columns()?;
- if columns.is_empty()
- || !columns
- .intersection(&used_columns)
- .collect::<HashSet<_>>()
- .is_empty()
- {
- keep_predicates.push(expr);
- } else {
+ let cols = expr.to_columns()?;
+ if cols.iter().all(|c| group_expr_columns.contains(c)) {
push_predicates.push(expr);
+ } else {
+ keep_predicates.push(expr);
}
}
- let child = match conjunction(push_predicates) {
+ // As for plan Filter: Column(a+b) > 0 -- Agg:
groupby:[Column(a)+Column(b)]
Review Comment:
Nice -- this is getting quite sophisticated.
##########
datafusion/optimizer/src/push_down_filter.rs:
##########
@@ -881,40 +880,30 @@ mod tests {
}
#[test]
- fn filter_keep_agg() -> Result<()> {
- let table_scan = test_table_scan()?;
- let plan = LogicalPlanBuilder::from(table_scan)
- .aggregate(vec![col("a")], vec![sum(col("b")).alias("b")])?
- .filter(col("b").gt(lit(10i64)))?
+ fn push_agg_need_replace_expr() -> Result<()> {
+ let plan = LogicalPlanBuilder::from(test_table_scan()?)
+ .aggregate(vec![add(col("b"), col("a"))], vec![sum(col("a")),
col("b")])?
+ .filter(col("test.b + test.a").gt(lit(10i64)))?
.build()?;
- // filter of aggregate is after aggregation since they are
non-commutative
- let expected = "\
- Filter: b > Int64(10)\
- \n Aggregate: groupBy=[[test.a]], aggr=[[SUM(test.b) AS b]]\
- \n TableScan: test";
+ let expected =
+ "Aggregate: groupBy=[[test.b + test.a]], aggr=[[SUM(test.a),
test.b]]\
+ \n Filter: test.b + test.a > Int64(10)\
Review Comment:
👍 very nice
##########
datafusion/optimizer/src/push_down_filter.rs:
##########
@@ -641,20 +633,27 @@ impl OptimizerRule for PushDownFilter {
let mut keep_predicates = vec![];
let mut push_predicates = vec![];
for expr in predicates {
- let columns = expr.to_columns()?;
- if columns.is_empty()
- || !columns
- .intersection(&used_columns)
- .collect::<HashSet<_>>()
- .is_empty()
- {
- keep_predicates.push(expr);
- } else {
+ let cols = expr.to_columns()?;
+ if cols.iter().all(|c| group_expr_columns.contains(c)) {
push_predicates.push(expr);
+ } else {
+ keep_predicates.push(expr);
}
}
- let child = match conjunction(push_predicates) {
+ // As for plan Filter: Column(a+b) > 0 -- Agg:
groupby:[Column(a)+Column(b)]
+ // After push, we need to replace `a+b` with
Column(a)+Column(b)
+ // So we need create a replace_map, add {`a+b` -->
Expr(Column(a)+Column(b))}
+ let mut replace_map = HashMap::new();
+ for expr in &agg.group_expr {
+ replace_map.insert(expr.display_name()?, expr.clone());
Review Comment:
Double checked that `display_name` is the right one:
https://docs.rs/datafusion/14.0.0/datafusion/prelude/enum.Expr.html#method.display_name
👍
##########
datafusion/optimizer/tests/integration-test.rs:
##########
@@ -304,6 +304,18 @@ fn join_keys_in_subquery_alias_1() {
assert_eq!(expected, format!("{:?}", plan));
}
+#[test]
+fn push_down_filter_groupby_expr_contains_alias() {
+ let sql = "SELECT * FROM (SELECT (col_int32 + col_uint32) AS c, count(*)
FROM test GROUP BY 1) where c > 3";
+ let plan = test_sql(sql).unwrap();
+ let expected = "Projection: c, COUNT(UInt8(1))\
+ \n Projection: test.col_int32 + test.col_uint32 AS c, COUNT(UInt8(1))\
+ \n Aggregate: groupBy=[[test.col_int32 + CAST(test.col_uint32 AS
Int32)]], aggr=[[COUNT(UInt8(1))]]\
+ \n Filter: test.col_int32 + CAST(test.col_uint32 AS Int32) > Int32(3)\
Review Comment:
👍
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