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datafusion-physical-expr/src/coercion_rule/aggregate_rule.rs
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,262 @@ | ||
| // 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. | ||
|
|
||
| //! Support the coercion rule for aggregate function. | ||
|
|
||
| use crate::expressions::{ | ||
| is_approx_percentile_cont_supported_arg_type, is_avg_support_arg_type, | ||
| is_correlation_support_arg_type, is_covariance_support_arg_type, | ||
| is_stddev_support_arg_type, is_sum_support_arg_type, is_variance_support_arg_type, | ||
| try_cast, | ||
| }; | ||
| use crate::PhysicalExpr; | ||
| use arrow::datatypes::DataType; | ||
| use arrow::datatypes::Schema; | ||
| use datafusion_common::{DataFusionError, Result}; | ||
| use datafusion_expr::AggregateFunction; | ||
| use datafusion_expr::{Signature, TypeSignature}; | ||
| use std::ops::Deref; | ||
| use std::sync::Arc; | ||
|
|
||
| /// Returns the coerced data type for each `input_types`. | ||
| /// Different aggregate function with different input data type will get corresponding coerced data type. | ||
| pub fn coerce_types( | ||
| agg_fun: &AggregateFunction, | ||
| input_types: &[DataType], | ||
| signature: &Signature, | ||
| ) -> Result<Vec<DataType>> { | ||
| // Validate input_types matches (at least one of) the func signature. | ||
| check_arg_count(agg_fun, input_types, &signature.type_signature)?; | ||
|
|
||
| match agg_fun { | ||
| AggregateFunction::Count | AggregateFunction::ApproxDistinct => { | ||
| Ok(input_types.to_vec()) | ||
| } | ||
| AggregateFunction::ArrayAgg => Ok(input_types.to_vec()), | ||
| AggregateFunction::Min | AggregateFunction::Max => { | ||
| // min and max support the dictionary data type | ||
| // unpack the dictionary to get the value | ||
| get_min_max_result_type(input_types) | ||
| } | ||
| AggregateFunction::Sum => { | ||
| // Refer to https://www.postgresql.org/docs/8.2/functions-aggregate.html doc | ||
| // smallint, int, bigint, real, double precision, decimal, or interval. | ||
| if !is_sum_support_arg_type(&input_types[0]) { | ||
| return Err(DataFusionError::Plan(format!( | ||
| "The function {:?} does not support inputs of type {:?}.", | ||
| agg_fun, input_types[0] | ||
| ))); | ||
| } | ||
| Ok(input_types.to_vec()) | ||
| } | ||
| AggregateFunction::Avg => { | ||
| // Refer to https://www.postgresql.org/docs/8.2/functions-aggregate.html doc | ||
| // smallint, int, bigint, real, double precision, decimal, or interval | ||
| if !is_avg_support_arg_type(&input_types[0]) { | ||
| return Err(DataFusionError::Plan(format!( | ||
| "The function {:?} does not support inputs of type {:?}.", | ||
| agg_fun, input_types[0] | ||
| ))); | ||
| } | ||
| Ok(input_types.to_vec()) | ||
| } | ||
| AggregateFunction::Variance => { | ||
| if !is_variance_support_arg_type(&input_types[0]) { | ||
| return Err(DataFusionError::Plan(format!( | ||
| "The function {:?} does not support inputs of type {:?}.", | ||
| agg_fun, input_types[0] | ||
| ))); | ||
| } | ||
| Ok(input_types.to_vec()) | ||
| } | ||
| AggregateFunction::VariancePop => { | ||
| if !is_variance_support_arg_type(&input_types[0]) { | ||
| return Err(DataFusionError::Plan(format!( | ||
| "The function {:?} does not support inputs of type {:?}.", | ||
| agg_fun, input_types[0] | ||
| ))); | ||
| } | ||
| Ok(input_types.to_vec()) | ||
| } | ||
| AggregateFunction::Covariance => { | ||
| if !is_covariance_support_arg_type(&input_types[0]) { | ||
| return Err(DataFusionError::Plan(format!( | ||
| "The function {:?} does not support inputs of type {:?}.", | ||
| agg_fun, input_types[0] | ||
| ))); | ||
| } | ||
| Ok(input_types.to_vec()) | ||
| } | ||
| AggregateFunction::CovariancePop => { | ||
| if !is_covariance_support_arg_type(&input_types[0]) { | ||
| return Err(DataFusionError::Plan(format!( | ||
| "The function {:?} does not support inputs of type {:?}.", | ||
| agg_fun, input_types[0] | ||
| ))); | ||
| } | ||
| Ok(input_types.to_vec()) | ||
| } | ||
| AggregateFunction::Stddev => { | ||
| if !is_stddev_support_arg_type(&input_types[0]) { | ||
| return Err(DataFusionError::Plan(format!( | ||
| "The function {:?} does not support inputs of type {:?}.", | ||
| agg_fun, input_types[0] | ||
| ))); | ||
| } | ||
| Ok(input_types.to_vec()) | ||
| } | ||
| AggregateFunction::StddevPop => { | ||
| if !is_stddev_support_arg_type(&input_types[0]) { | ||
| return Err(DataFusionError::Plan(format!( | ||
| "The function {:?} does not support inputs of type {:?}.", | ||
| agg_fun, input_types[0] | ||
| ))); | ||
| } | ||
| Ok(input_types.to_vec()) | ||
| } | ||
| AggregateFunction::Correlation => { | ||
| if !is_correlation_support_arg_type(&input_types[0]) { | ||
| return Err(DataFusionError::Plan(format!( | ||
| "The function {:?} does not support inputs of type {:?}.", | ||
| agg_fun, input_types[0] | ||
| ))); | ||
| } | ||
| Ok(input_types.to_vec()) | ||
| } | ||
| AggregateFunction::ApproxPercentileCont => { | ||
| if !is_approx_percentile_cont_supported_arg_type(&input_types[0]) { | ||
| return Err(DataFusionError::Plan(format!( | ||
| "The function {:?} does not support inputs of type {:?}.", | ||
| agg_fun, input_types[0] | ||
| ))); | ||
| } | ||
| if !matches!(input_types[1], DataType::Float64) { | ||
| return Err(DataFusionError::Plan(format!( | ||
| "The percentile argument for {:?} must be Float64, not {:?}.", | ||
| agg_fun, input_types[1] | ||
| ))); | ||
| } | ||
| Ok(input_types.to_vec()) | ||
| } | ||
| AggregateFunction::ApproxMedian => { | ||
| if !is_approx_percentile_cont_supported_arg_type(&input_types[0]) { | ||
| return Err(DataFusionError::Plan(format!( | ||
| "The function {:?} does not support inputs of type {:?}.", | ||
| agg_fun, input_types[0] | ||
| ))); | ||
| } | ||
| Ok(input_types.to_vec()) | ||
| } | ||
| } | ||
| } | ||
|
|
||
| /// Validate the length of `input_types` matches the `signature` for `agg_fun`. | ||
| /// | ||
| /// This method DOES NOT validate the argument types - only that (at least one, | ||
| /// in the case of [`TypeSignature::OneOf`]) signature matches the desired | ||
| /// number of input types. | ||
| fn check_arg_count( | ||
| agg_fun: &AggregateFunction, | ||
| input_types: &[DataType], | ||
| signature: &TypeSignature, | ||
| ) -> Result<()> { | ||
| match signature { | ||
| TypeSignature::Uniform(agg_count, _) | TypeSignature::Any(agg_count) => { | ||
| if input_types.len() != *agg_count { | ||
| return Err(DataFusionError::Plan(format!( | ||
| "The function {:?} expects {:?} arguments, but {:?} were provided", | ||
| agg_fun, | ||
| agg_count, | ||
| input_types.len() | ||
| ))); | ||
| } | ||
| } | ||
| TypeSignature::Exact(types) => { | ||
| if types.len() != input_types.len() { | ||
| return Err(DataFusionError::Plan(format!( | ||
| "The function {:?} expects {:?} arguments, but {:?} were provided", | ||
| agg_fun, | ||
| types.len(), | ||
| input_types.len() | ||
| ))); | ||
| } | ||
| } | ||
| TypeSignature::OneOf(variants) => { | ||
| let ok = variants | ||
| .iter() | ||
| .any(|v| check_arg_count(agg_fun, input_types, v).is_ok()); | ||
| if !ok { | ||
| return Err(DataFusionError::Plan(format!( | ||
| "The function {:?} does not accept {:?} function arguments.", | ||
| agg_fun, | ||
| input_types.len() | ||
| ))); | ||
| } | ||
| } | ||
| _ => { | ||
| return Err(DataFusionError::Internal(format!( | ||
| "Aggregate functions do not support this {:?}", | ||
| signature | ||
| ))); | ||
| } | ||
| } | ||
| Ok(()) | ||
| } | ||
|
|
||
| fn get_min_max_result_type(input_types: &[DataType]) -> Result<Vec<DataType>> { | ||
| // make sure that the input types only has one element. | ||
| assert_eq!(input_types.len(), 1); | ||
| // min and max support the dictionary data type | ||
| // unpack the dictionary to get the value | ||
| match &input_types[0] { | ||
| DataType::Dictionary(_, dict_value_type) => { | ||
| // TODO add checker, if the value type is complex data type | ||
| Ok(vec![dict_value_type.deref().clone()]) | ||
| } | ||
| // TODO add checker for datatype which min and max supported | ||
| // For example, the `Struct` and `Map` type are not supported in the MIN and MAX function | ||
| _ => Ok(input_types.to_vec()), | ||
| } | ||
| } | ||
|
|
||
| /// Returns the coerced exprs for each `input_exprs`. | ||
| /// Get the coerced data type from `aggregate_rule::coerce_types` and add `try_cast` if the | ||
| /// data type of `input_exprs` need to be coerced. | ||
| pub fn coerce_exprs( | ||
| agg_fun: &AggregateFunction, | ||
| input_exprs: &[Arc<dyn PhysicalExpr>], | ||
| schema: &Schema, | ||
| signature: &Signature, | ||
| ) -> Result<Vec<Arc<dyn PhysicalExpr>>> { | ||
| if input_exprs.is_empty() { | ||
| return Ok(vec![]); | ||
| } | ||
| let input_types = input_exprs | ||
| .iter() | ||
| .map(|e| e.data_type(schema)) | ||
| .collect::<Result<Vec<_>>>()?; | ||
|
|
||
| // get the coerced data types | ||
| let coerced_types = coerce_types(agg_fun, &input_types, signature)?; | ||
|
|
||
| // try cast if need | ||
| input_exprs | ||
| .iter() | ||
| .zip(coerced_types.into_iter()) | ||
| .map(|(expr, coerced_type)| try_cast(expr.clone(), schema, coerced_type)) | ||
| .collect::<Result<Vec<_>>>() | ||
| } |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
|
|
@@ -20,4 +20,5 @@ | |
| //! Aggregate function rule | ||
| //! Binary operation rule | ||
|
|
||
| pub mod aggregate_rule; | ||
| pub mod binary_rule; | ||
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