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Move sql_compound_identifier_to_expr to ExprPlanner #11487

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147 changes: 146 additions & 1 deletion datafusion/core/tests/optimizer_integration.rs
Original file line number Diff line number Diff line change
Expand Up @@ -44,6 +44,8 @@ use datafusion_sql::sqlparser::parser::Parser;
use datafusion_sql::TableReference;

use chrono::DateTime;
use datafusion_expr::planner::ExprPlanner;
use datafusion_functions::core::planner::CoreFunctionPlanner;
use datafusion_functions::datetime;

#[cfg(test)]
Expand Down Expand Up @@ -115,6 +117,139 @@ fn concat_ws_literals() -> Result<()> {
Ok(())
}

#[test]
fn anti_join_with_join_filter() -> Result<()> {
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why are these tests moved? Does that mean we can't plan SQL with identifiers like test.col_int32 without an Expr planner?

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For the earlier implementation, I also moved plannig of basic SQL like column references to expr planner, we had to move these test cases from optimizer crate to core to avoid optimizer crate dependecy on functions.

Since we have moved that out of planner, ideally i should moved the testcases back. My bad, i missed them. Thanks for catching this. I have fixed this.

// regression test for https://github.com/apache/datafusion/issues/2888
let sql = "SELECT col_utf8 FROM test WHERE NOT EXISTS (\
SELECT col_utf8 FROM test t2 WHERE test.col_int32 = t2.col_int32 \
AND test.col_uint32 != t2.col_uint32)";
let plan = test_sql(sql)?;
let expected = "Projection: test.col_utf8\
\n LeftAnti Join: test.col_int32 = __correlated_sq_1.col_int32 Filter: test.col_uint32 != __correlated_sq_1.col_uint32\
\n TableScan: test projection=[col_int32, col_uint32, col_utf8]\
\n SubqueryAlias: __correlated_sq_1\
\n SubqueryAlias: t2\
\n TableScan: test projection=[col_int32, col_uint32]";
assert_eq!(expected, format!("{plan:?}"));
Ok(())
}

#[test]
fn where_exists_distinct() -> Result<()> {
let sql = "SELECT col_int32 FROM test WHERE EXISTS (\
SELECT DISTINCT col_int32 FROM test t2 WHERE test.col_int32 = t2.col_int32)";
let plan = test_sql(sql)?;
let expected = "LeftSemi Join: test.col_int32 = __correlated_sq_1.col_int32\
\n TableScan: test projection=[col_int32]\
\n SubqueryAlias: __correlated_sq_1\
\n Aggregate: groupBy=[[t2.col_int32]], aggr=[[]]\
\n SubqueryAlias: t2\
\n TableScan: test projection=[col_int32]";
assert_eq!(expected, format!("{plan:?}"));
Ok(())
}

#[test]
fn propagate_empty_relation() {
let sql = "SELECT test.col_int32 FROM test JOIN ( SELECT col_int32 FROM test WHERE false ) AS ta1 ON test.col_int32 = ta1.col_int32;";
let plan = test_sql(sql).unwrap();
// when children exist EmptyRelation, it will bottom-up propagate.
let expected = "EmptyRelation";
assert_eq!(expected, format!("{plan:?}"));
}

#[test]
fn join_keys_in_subquery_alias() {
let sql = "SELECT * FROM test AS A, ( SELECT col_int32 as key FROM test ) AS B where A.col_int32 = B.key;";
let plan = test_sql(sql).unwrap();
let expected = "Inner Join: a.col_int32 = b.key\
\n SubqueryAlias: a\
\n Filter: test.col_int32 IS NOT NULL\
\n TableScan: test projection=[col_int32, col_uint32, col_utf8, col_date32, col_date64, col_ts_nano_none, col_ts_nano_utc]\
\n SubqueryAlias: b\
\n Projection: test.col_int32 AS key\
\n Filter: test.col_int32 IS NOT NULL\
\n TableScan: test projection=[col_int32]";

assert_eq!(expected, format!("{plan:?}"));
}

#[test]
fn join_keys_in_subquery_alias_1() {
let sql = "SELECT * FROM test AS A, ( SELECT test.col_int32 AS key FROM test JOIN test AS C on test.col_int32 = C.col_int32 ) AS B where A.col_int32 = B.key;";
let plan = test_sql(sql).unwrap();
let expected = "Inner Join: a.col_int32 = b.key\
\n SubqueryAlias: a\
\n Filter: test.col_int32 IS NOT NULL\
\n TableScan: test projection=[col_int32, col_uint32, col_utf8, col_date32, col_date64, col_ts_nano_none, col_ts_nano_utc]\
\n SubqueryAlias: b\
\n Projection: test.col_int32 AS key\
\n Inner Join: test.col_int32 = c.col_int32\
\n Filter: test.col_int32 IS NOT NULL\
\n TableScan: test projection=[col_int32]\
\n SubqueryAlias: c\
\n Filter: test.col_int32 IS NOT NULL\
\n TableScan: test projection=[col_int32]";
assert_eq!(expected, format!("{plan:?}"));
}

#[test]
// issue: https://github.com/apache/datafusion/issues/5334
fn test_same_name_but_not_ambiguous() {
let sql = "SELECT t1.col_int32 AS col_int32 FROM test t1 intersect SELECT col_int32 FROM test t2";
let plan = test_sql(sql).unwrap();
let expected = "LeftSemi Join: t1.col_int32 = t2.col_int32\
\n Aggregate: groupBy=[[t1.col_int32]], aggr=[[]]\
\n SubqueryAlias: t1\
\n TableScan: test projection=[col_int32]\
\n SubqueryAlias: t2\
\n TableScan: test projection=[col_int32]";
assert_eq!(expected, format!("{plan:?}"));
}

#[test]
fn test_propagate_empty_relation_inner_join_and_unions() {
let sql = "\
SELECT A.col_int32 FROM test AS A \
INNER JOIN ( \
SELECT col_int32 FROM test WHERE 1 = 0 \
) AS B ON A.col_int32 = B.col_int32 \
UNION ALL \
SELECT test.col_int32 FROM test WHERE 1 = 1 \
UNION ALL \
SELECT test.col_int32 FROM test WHERE 0 = 0 \
UNION ALL \
SELECT test.col_int32 FROM test WHERE test.col_int32 < 0 \
UNION ALL \
SELECT test.col_int32 FROM test WHERE 1 = 0";

let plan = test_sql(sql).unwrap();
let expected = "\
Union\
\n TableScan: test projection=[col_int32]\
\n TableScan: test projection=[col_int32]\
\n Filter: test.col_int32 < Int32(0)\
\n TableScan: test projection=[col_int32]";
assert_eq!(expected, format!("{plan:?}"));
}

#[test]
fn semi_join_with_join_filter() -> Result<()> {
// regression test for https://github.com/apache/datafusion/issues/2888
let sql = "SELECT col_utf8 FROM test WHERE EXISTS (\
SELECT col_utf8 FROM test t2 WHERE test.col_int32 = t2.col_int32 \
AND test.col_uint32 != t2.col_uint32)";
let plan = test_sql(sql)?;
let expected = "Projection: test.col_utf8\
\n LeftSemi Join: test.col_int32 = __correlated_sq_1.col_int32 Filter: test.col_uint32 != __correlated_sq_1.col_uint32\
\n TableScan: test projection=[col_int32, col_uint32, col_utf8]\
\n SubqueryAlias: __correlated_sq_1\
\n SubqueryAlias: t2\
\n TableScan: test projection=[col_int32, col_uint32]";
assert_eq!(expected, format!("{plan:?}"));
Ok(())
}

fn quick_test(sql: &str, expected_plan: &str) {
let plan = test_sql(sql).unwrap();
assert_eq!(expected_plan, format!("{:?}", plan));
Expand All @@ -131,7 +266,8 @@ fn test_sql(sql: &str) -> Result<LogicalPlan> {
.with_udf(datetime::now())
.with_udf(datafusion_functions::core::arrow_cast())
.with_udf(datafusion_functions::string::concat())
.with_udf(datafusion_functions::string::concat_ws());
.with_udf(datafusion_functions::string::concat_ws())
.with_expr_planner(Arc::new(CoreFunctionPlanner::default()));
let sql_to_rel = SqlToRel::new(&context_provider);
let plan = sql_to_rel.sql_statement_to_plan(statement.clone()).unwrap();

Expand All @@ -151,13 +287,18 @@ fn test_sql(sql: &str) -> Result<LogicalPlan> {
struct MyContextProvider {
options: ConfigOptions,
udfs: HashMap<String, Arc<ScalarUDF>>,
expr_planners: Vec<Arc<dyn ExprPlanner>>,
}

impl MyContextProvider {
fn with_udf(mut self, udf: Arc<ScalarUDF>) -> Self {
self.udfs.insert(udf.name().to_string(), udf);
self
}
fn with_expr_planner(mut self, planner: Arc<dyn ExprPlanner>) -> Self {
self.expr_planners.push(planner);
self
}
}

impl ContextProvider for MyContextProvider {
Expand Down Expand Up @@ -226,6 +367,10 @@ impl ContextProvider for MyContextProvider {
fn udwf_names(&self) -> Vec<String> {
Vec::new()
}

fn get_expr_planners(&self) -> &[Arc<dyn ExprPlanner>] {
&self.expr_planners
}
}

struct MyTableSource {
Expand Down
19 changes: 18 additions & 1 deletion datafusion/expr/src/planner.rs
Original file line number Diff line number Diff line change
Expand Up @@ -19,7 +19,7 @@

use std::sync::Arc;

use arrow::datatypes::{DataType, SchemaRef};
use arrow::datatypes::{DataType, Field, SchemaRef};
use datafusion_common::{
config::ConfigOptions, file_options::file_type::FileType, not_impl_err, DFSchema,
Result, TableReference,
Expand Down Expand Up @@ -180,6 +180,23 @@ pub trait ExprPlanner: Send + Sync {
fn plan_make_map(&self, args: Vec<Expr>) -> Result<PlannerResult<Vec<Expr>>> {
Ok(PlannerResult::Original(args))
}

/// Plans compound identifier eg `db.schema.table` for non-empty nested names
///
/// Note:
/// Currently compound identifier for outer query schema is not supported.
///
/// Returns planned expression
fn plan_compound_identifier(
&self,
_field: &Field,
_qualifier: Option<&TableReference>,
_nested_names: &[String],
) -> Result<PlannerResult<Vec<Expr>>> {
not_impl_err!(
"Default planner compound identifier hasn't been implemented for ExprPlanner"
)
}
}

/// An operator with two arguments to plan
Expand Down
1 change: 0 additions & 1 deletion datafusion/functions/src/core/mod.rs
Original file line number Diff line number Diff line change
Expand Up @@ -100,7 +100,6 @@ pub fn functions() -> Vec<Arc<ScalarUDF>> {
nvl2(),
arrow_typeof(),
named_struct(),
get_field(),
coalesce(),
map(),
]
Expand Down
27 changes: 25 additions & 2 deletions datafusion/functions/src/core/planner.rs
Original file line number Diff line number Diff line change
Expand Up @@ -15,11 +15,12 @@
// specific language governing permissions and limitations
// under the License.

use datafusion_common::DFSchema;
use arrow::datatypes::Field;
use datafusion_common::Result;
use datafusion_common::{not_impl_err, Column, DFSchema, ScalarValue, TableReference};
use datafusion_expr::expr::ScalarFunction;
use datafusion_expr::planner::{ExprPlanner, PlannerResult, RawDictionaryExpr};
use datafusion_expr::Expr;
use datafusion_expr::{lit, Expr};

use super::named_struct;

Expand Down Expand Up @@ -62,4 +63,26 @@ impl ExprPlanner for CoreFunctionPlanner {
ScalarFunction::new_udf(crate::string::overlay(), args),
)))
}

fn plan_compound_identifier(
&self,
field: &Field,
qualifier: Option<&TableReference>,
nested_names: &[String],
) -> Result<PlannerResult<Vec<Expr>>> {
// TODO: remove when can support multiple nested identifiers
if nested_names.len() > 1 {
return not_impl_err!(
"Nested identifiers not yet supported for column {}",
Column::from((qualifier, field)).quoted_flat_name()
);
}
let nested_name = nested_names[0].to_string();

let col = Expr::Column(Column::from((qualifier, field)));
let get_field_args = vec![col, lit(ScalarValue::from(nested_name))];
Ok(PlannerResult::Planned(Expr::ScalarFunction(
ScalarFunction::new_udf(crate::core::get_field(), get_field_args),
)))
}
}
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