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// Licensed to the Apache Software Foundation (ASF) under one
// or more contributor license agreements. See the NOTICE file
// distributed with this work for additional information
// regarding copyright ownership. The ASF licenses this file
// to you under the Apache License, Version 2.0 (the
// "License"); you may not use this file except in compliance
// with the License. You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing,
// software distributed under the License is distributed on an
// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
// KIND, either express or implied. See the License for the
// specific language governing permissions and limitations
// under the License.
//! Rewrite for order by expressions
use crate::expr::{Alias, Sort};
use crate::expr_rewriter::normalize_col;
use crate::{Cast, Expr, ExprSchemable, LogicalPlan, TryCast};
use datafusion_common::tree_node::{Transformed, TreeNode};
use datafusion_common::{Column, Result};
/// Rewrite sort on aggregate expressions to sort on the column of aggregate output
/// For example, `max(x)` is written to `col("MAX(x)")`
pub fn rewrite_sort_cols_by_aggs(
exprs: impl IntoIterator<Item = impl Into<Expr>>,
plan: &LogicalPlan,
) -> Result<Vec<Expr>> {
exprs
.into_iter()
.map(|e| {
let expr = e.into();
match expr {
Expr::Sort(Sort {
expr,
asc,
nulls_first,
}) => {
let sort = Expr::Sort(Sort::new(
Box::new(rewrite_sort_col_by_aggs(*expr, plan)?),
asc,
nulls_first,
));
Ok(sort)
}
expr => Ok(expr),
}
})
.collect()
}
fn rewrite_sort_col_by_aggs(expr: Expr, plan: &LogicalPlan) -> Result<Expr> {
let plan_inputs = plan.inputs();
// Joins, and Unions are not yet handled (should have a projection
// on top of them)
if plan_inputs.len() == 1 {
let proj_exprs = plan.expressions();
rewrite_in_terms_of_projection(expr, proj_exprs, plan_inputs[0])
} else {
Ok(expr)
}
}
/// Rewrites a sort expression in terms of the output of the previous [`LogicalPlan`]
///
/// Example:
///
/// Given an input expression such as `col(a) + col(b) + col(c)`
///
/// into `col(a) + col("b + c")`
///
/// Remember that:
/// 1. given a projection with exprs: [a, b + c]
/// 2. t produces an output schema with two columns "a", "b + c"
fn rewrite_in_terms_of_projection(
expr: Expr,
proj_exprs: Vec<Expr>,
input: &LogicalPlan,
) -> Result<Expr> {
// assumption is that each item in exprs, such as "b + c" is
// available as an output column named "b + c"
expr.transform(&|expr| {
// search for unnormalized names first such as "c1" (such as aliases)
if let Some(found) = proj_exprs.iter().find(|a| (**a) == expr) {
let col = Expr::Column(
found
.to_field(input.schema())
.map(|f| f.qualified_column())?,
);
return Ok(Transformed::Yes(col));
}
// if that doesn't work, try to match the expression as an
// output column -- however first it must be "normalized"
// (e.g. "c1" --> "t.c1") because that normalization is done
// at the input of the aggregate.
let normalized_expr = if let Ok(e) = normalize_col(expr.clone(), input) {
e
} else {
// The expr is not based on Aggregate plan output. Skip it.
return Ok(Transformed::No(expr));
};
// expr is an actual expr like min(t.c2), but we are looking
// for a column with the same "MIN(C2)", so translate there
let name = normalized_expr.display_name()?;
let search_col = Expr::Column(Column {
relation: None,
name,
});
// look for the column named the same as this expr
if let Some(found) = proj_exprs.iter().find(|a| expr_match(&search_col, a)) {
let found = found.clone();
return Ok(Transformed::Yes(match normalized_expr {
Expr::Cast(Cast { expr: _, data_type }) => Expr::Cast(Cast {
expr: Box::new(found),
data_type,
}),
Expr::TryCast(TryCast { expr: _, data_type }) => Expr::TryCast(TryCast {
expr: Box::new(found),
data_type,
}),
_ => found,
}));
}
Ok(Transformed::No(expr))
})
}
/// Does the underlying expr match e?
/// so avg(c) as average will match avgc
fn expr_match(needle: &Expr, expr: &Expr) -> bool {
// check inside aliases
if let Expr::Alias(Alias { expr, .. }) = &expr {
expr.as_ref() == needle
} else {
expr == needle
}
}
#[cfg(test)]
mod test {
use std::ops::Add;
use std::sync::Arc;
use arrow::datatypes::{DataType, Field, Schema};
use crate::{
avg, cast, col, lit, logical_plan::builder::LogicalTableSource, min, try_cast,
LogicalPlanBuilder,
};
use super::*;
#[test]
fn rewrite_sort_cols_by_agg() {
// gby c1, agg: min(c2)
let agg = make_input()
.aggregate(
// gby: c1
vec![col("c1")],
// agg: min(c2)
vec![min(col("c2"))],
)
.unwrap()
.build()
.unwrap();
let cases = vec![
TestCase {
desc: "c1 --> c1",
input: sort(col("c1")),
expected: sort(col("c1")),
},
TestCase {
desc: "c1 + c2 --> c1 + c2",
input: sort(col("c1") + col("c1")),
expected: sort(col("c1") + col("c1")),
},
TestCase {
desc: r#"min(c2) --> "min(c2)"#,
input: sort(min(col("c2"))),
expected: sort(min(col("c2"))),
},
TestCase {
desc: r#"c1 + min(c2) --> "c1 + min(c2)"#,
input: sort(col("c1") + min(col("c2"))),
expected: sort(col("c1") + min(col("c2"))),
},
];
for case in cases {
case.run(&agg)
}
}
#[test]
fn rewrite_sort_cols_by_agg_alias() {
let agg = make_input()
.aggregate(
// gby c1
vec![col("c1")],
// agg: min(c2), avg(c3)
vec![min(col("c2")), avg(col("c3"))],
)
.unwrap()
// projects out an expression "c1" that is different than the column "c1"
.project(vec![
// c1 + 1 as c1,
col("c1").add(lit(1)).alias("c1"),
// min(c2)
min(col("c2")),
// avg("c3") as average
avg(col("c3")).alias("average"),
])
.unwrap()
.build()
.unwrap();
let cases = vec![
TestCase {
desc: "c1 --> c1 -- column *named* c1 that came out of the projection, (not t.c1)",
input: sort(col("c1")),
// should be "c1" not t.c1
expected: sort(col("c1")),
},
TestCase {
desc: r#"min(c2) --> "MIN(c2)" -- (column *named* "min(t.c2)"!)"#,
input: sort(min(col("c2"))),
expected: sort(col("MIN(t.c2)")),
},
TestCase {
desc: r#"c1 + min(c2) --> "c1 + MIN(c2)" -- (column *named* "min(t.c2)"!)"#,
input: sort(col("c1") + min(col("c2"))),
// should be "c1" not t.c1
expected: sort(col("c1") + col("MIN(t.c2)")),
},
TestCase {
desc: r#"avg(c3) --> "AVG(t.c3)" as average (column *named* "AVG(t.c3)", aliased)"#,
input: sort(avg(col("c3"))),
expected: sort(col("AVG(t.c3)").alias("average")),
},
];
for case in cases {
case.run(&agg)
}
}
#[test]
fn preserve_cast() {
let plan = make_input()
.project(vec![col("c2").alias("c2")])
.unwrap()
.project(vec![col("c2").alias("c2")])
.unwrap()
.build()
.unwrap();
let cases = vec![
TestCase {
desc: "Cast is preserved by rewrite_sort_cols_by_aggs",
input: sort(cast(col("c2"), DataType::Int64)),
expected: sort(cast(col("c2").alias("c2"), DataType::Int64)),
},
TestCase {
desc: "TryCast is preserved by rewrite_sort_cols_by_aggs",
input: sort(try_cast(col("c2"), DataType::Int64)),
expected: sort(try_cast(col("c2").alias("c2"), DataType::Int64)),
},
];
for case in cases {
case.run(&plan)
}
}
struct TestCase {
desc: &'static str,
input: Expr,
expected: Expr,
}
impl TestCase {
/// calls rewrite_sort_cols_by_aggs for expr and compares it to expected_expr
fn run(self, input_plan: &LogicalPlan) {
let Self {
desc,
input,
expected,
} = self;
println!("running: '{desc}'");
let mut exprs =
rewrite_sort_cols_by_aggs(vec![input.clone()], input_plan).unwrap();
assert_eq!(exprs.len(), 1);
let rewritten = exprs.pop().unwrap();
assert_eq!(
rewritten, expected,
"\n\ninput:{input:?}\nrewritten:{rewritten:?}\nexpected:{expected:?}\n"
);
}
}
/// Scan of a table: t(c1 int, c2 varchar, c3 float)
fn make_input() -> LogicalPlanBuilder {
let schema = Arc::new(Schema::new(vec![
Field::new("c1", DataType::Int32, true),
Field::new("c2", DataType::Utf8, true),
Field::new("c3", DataType::Float64, true),
]));
let projection = None;
LogicalPlanBuilder::scan(
"t",
Arc::new(LogicalTableSource::new(schema)),
projection,
)
.unwrap()
}
fn sort(expr: Expr) -> Expr {
let asc = true;
let nulls_first = true;
expr.sort(asc, nulls_first)
}
}