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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. //! Traits for physical query plan, supporting parallel execution for partitioned relations. use std::cell::RefCell; use std::rc::Rc; use std::sync::{Arc, Mutex}; use crate::error::Result; use crate::logicalplan::ScalarValue; use arrow::array::ArrayRef; use arrow::datatypes::{DataType, Field, Schema, SchemaRef}; use arrow::record_batch::{RecordBatch, RecordBatchReader}; /// Partition-aware execution plan for a relation pub trait ExecutionPlan { /// Get the schema for this execution plan fn schema(&self) -> SchemaRef; /// Get the partitions for this execution plan. Each partition can be executed in parallel. fn partitions(&self) -> Result<Vec<Arc<dyn Partition>>>; } /// Represents a partition of an execution plan that can be executed on a thread pub trait Partition: Send + Sync { /// Execute this partition and return an iterator over RecordBatch fn execute(&self) -> Result<Arc<Mutex<dyn RecordBatchReader + Send + Sync>>>; } /// Expression that can be evaluated against a RecordBatch pub trait PhysicalExpr: Send + Sync { /// Get the name to use in a schema to represent the result of this expression fn name(&self) -> String; /// Get the data type of this expression, given the schema of the input fn data_type(&self, input_schema: &Schema) -> Result<DataType>; /// Decide whehter this expression is nullable, given the schema of the input fn nullable(&self, input_schema: &Schema) -> Result<bool>; /// Evaluate an expression against a RecordBatch fn evaluate(&self, batch: &RecordBatch) -> Result<ArrayRef>; /// Generate schema Field type for this expression fn to_schema_field(&self, input_schema: &Schema) -> Result<Field> { Ok(Field::new( &self.name(), self.data_type(input_schema)?, self.nullable(input_schema)?, )) } } /// Aggregate expression that can be evaluated against a RecordBatch pub trait AggregateExpr: Send + Sync { /// Get the name to use in a schema to represent the result of this expression fn name(&self) -> String; /// Get the data type of this expression, given the schema of the input fn data_type(&self, input_schema: &Schema) -> Result<DataType>; /// Evaluate the expression being aggregated fn evaluate_input(&self, batch: &RecordBatch) -> Result<ArrayRef>; /// Create an accumulator for this aggregate expression fn create_accumulator(&self) -> Rc<RefCell<dyn Accumulator>>; /// Create an aggregate expression for combining the results of accumulators from partitions. /// For example, to combine the results of a parallel SUM we just need to do another SUM, but /// to combine the results of parallel COUNT we would also use SUM. fn create_reducer(&self, column_index: usize) -> Arc<dyn AggregateExpr>; } /// Aggregate accumulator pub trait Accumulator { /// Update the accumulator based on a row in a batch fn accumulate_scalar(&mut self, value: Option<ScalarValue>) -> Result<()>; /// Update the accumulator based on an array in a batch fn accumulate_batch(&mut self, array: &ArrayRef) -> Result<()>; /// Get the final value for the accumulator fn get_value(&self) -> Result<Option<ScalarValue>>; } pub mod common; pub mod csv; pub mod datasource; pub mod expressions; pub mod hash_aggregate; pub mod limit; pub mod math_expressions; pub mod memory; pub mod merge; pub mod parquet; pub mod projection; pub mod selection; pub mod sort; pub mod udf;