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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.
//! SQL planning extensions like [`NestedFunctionPlanner`] and [`FieldAccessPlanner`]
use arrow::datatypes::DataType;
use datafusion_common::ExprSchema;
use datafusion_common::{plan_err, utils::list_ndims, DFSchema, Result};
use datafusion_expr::expr::ScalarFunction;
use datafusion_expr::expr::{AggregateFunction, AggregateFunctionParams};
use datafusion_expr::AggregateUDF;
use datafusion_expr::{
planner::{ExprPlanner, PlannerResult, RawBinaryExpr, RawFieldAccessExpr},
sqlparser, Expr, ExprSchemable, GetFieldAccess,
};
use datafusion_functions::core::get_field as get_field_inner;
use datafusion_functions::expr_fn::get_field;
use datafusion_functions_aggregate::nth_value::nth_value_udaf;
use std::sync::Arc;
use crate::map::map_udf;
use crate::{
array_has::{array_has_all, array_has_udf},
expr_fn::{array_append, array_concat, array_prepend},
extract::{array_element, array_slice},
make_array::make_array,
};
#[derive(Debug)]
pub struct NestedFunctionPlanner;
impl ExprPlanner for NestedFunctionPlanner {
fn plan_binary_op(
&self,
expr: RawBinaryExpr,
schema: &DFSchema,
) -> Result<PlannerResult<RawBinaryExpr>> {
let RawBinaryExpr { op, left, right } = expr;
if op == sqlparser::ast::BinaryOperator::StringConcat {
let left_type = left.get_type(schema)?;
let right_type = right.get_type(schema)?;
let left_list_ndims = list_ndims(&left_type);
let right_list_ndims = list_ndims(&right_type);
// Rewrite string concat operator to function based on types
// if we get list || list then we rewrite it to array_concat()
// if we get list || non-list then we rewrite it to array_append()
// if we get non-list || list then we rewrite it to array_prepend()
// if we get string || string then we rewrite it to concat()
// We determine the target function to rewrite based on the list n-dimension, the check is not exact but sufficient.
// The exact validity check is handled in the actual function, so even if there is 3d list appended with 1d list, it is also fine to rewrite.
if left_list_ndims + right_list_ndims == 0 {
// TODO: concat function ignore null, but string concat takes null into consideration
// we can rewrite it to concat if we can configure the behaviour of concat function to the one like `string concat operator`
} else if left_list_ndims == right_list_ndims {
return Ok(PlannerResult::Planned(array_concat(vec![left, right])));
} else if left_list_ndims > right_list_ndims {
return Ok(PlannerResult::Planned(array_append(left, right)));
} else if left_list_ndims < right_list_ndims {
return Ok(PlannerResult::Planned(array_prepend(left, right)));
}
} else if matches!(
op,
sqlparser::ast::BinaryOperator::AtArrow
| sqlparser::ast::BinaryOperator::ArrowAt
) {
let left_type = left.get_type(schema)?;
let right_type = right.get_type(schema)?;
let left_list_ndims = list_ndims(&left_type);
let right_list_ndims = list_ndims(&right_type);
// if both are list
if left_list_ndims > 0 && right_list_ndims > 0 {
if op == sqlparser::ast::BinaryOperator::AtArrow {
// array1 @> array2 -> array_has_all(array1, array2)
return Ok(PlannerResult::Planned(array_has_all(left, right)));
} else {
// array1 <@ array2 -> array_has_all(array2, array1)
return Ok(PlannerResult::Planned(array_has_all(right, left)));
}
}
}
Ok(PlannerResult::Original(RawBinaryExpr { op, left, right }))
}
fn plan_array_literal(
&self,
exprs: Vec<Expr>,
_schema: &DFSchema,
) -> Result<PlannerResult<Vec<Expr>>> {
Ok(PlannerResult::Planned(make_array(exprs)))
}
fn plan_make_map(&self, args: Vec<Expr>) -> Result<PlannerResult<Vec<Expr>>> {
if args.len() % 2 != 0 {
return plan_err!("make_map requires an even number of arguments");
}
let (keys, values): (Vec<_>, Vec<_>) =
args.into_iter().enumerate().partition(|(i, _)| i % 2 == 0);
let keys = make_array(keys.into_iter().map(|(_, e)| e).collect());
let values = make_array(values.into_iter().map(|(_, e)| e).collect());
Ok(PlannerResult::Planned(Expr::ScalarFunction(
ScalarFunction::new_udf(map_udf(), vec![keys, values]),
)))
}
fn plan_any(&self, expr: RawBinaryExpr) -> Result<PlannerResult<RawBinaryExpr>> {
if expr.op == sqlparser::ast::BinaryOperator::Eq {
Ok(PlannerResult::Planned(Expr::ScalarFunction(
ScalarFunction::new_udf(
array_has_udf(),
// left and right are reversed here so `needle=any(haystack)` -> `array_has(haystack, needle)`
vec![expr.right, expr.left],
),
)))
} else {
plan_err!("Unsupported AnyOp: '{}', only '=' is supported", expr.op)
}
}
}
#[derive(Debug)]
pub struct FieldAccessPlanner;
impl ExprPlanner for FieldAccessPlanner {
fn plan_field_access(
&self,
expr: RawFieldAccessExpr,
schema: &DFSchema,
) -> Result<PlannerResult<RawFieldAccessExpr>> {
let RawFieldAccessExpr { expr, field_access } = expr;
match field_access {
// expr["field"] => get_field(expr, "field")
GetFieldAccess::NamedStructField { name } => {
Ok(PlannerResult::Planned(get_field(expr, name)))
}
// expr[idx] ==> array_element(expr, idx)
GetFieldAccess::ListIndex { key: index } => {
match expr {
// Special case for array_agg(expr)[index] to NTH_VALUE(expr, index)
Expr::AggregateFunction(AggregateFunction {
func,
params:
AggregateFunctionParams {
args,
distinct,
filter,
order_by,
null_treatment,
},
}) if is_array_agg(&func) => Ok(PlannerResult::Planned(
Expr::AggregateFunction(AggregateFunction::new_udf(
nth_value_udaf(),
args.into_iter().chain(std::iter::once(*index)).collect(),
distinct,
filter,
order_by,
null_treatment,
)),
)),
// special case for map access with
Expr::Column(ref c)
if matches!(schema.data_type(c)?, DataType::Map(_, _)) =>
{
Ok(PlannerResult::Planned(Expr::ScalarFunction(
ScalarFunction::new_udf(
get_field_inner(),
vec![expr, *index],
),
)))
}
_ => Ok(PlannerResult::Planned(array_element(expr, *index))),
}
}
// expr[start, stop, stride] ==> array_slice(expr, start, stop, stride)
GetFieldAccess::ListRange {
start,
stop,
stride,
} => Ok(PlannerResult::Planned(array_slice(
expr,
*start,
*stop,
Some(*stride),
))),
}
}
}
fn is_array_agg(func: &Arc<AggregateUDF>) -> bool {
func.name() == "array_agg"
}