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evaluator.go
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/
evaluator.go
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// Copyright 2018 PingCAP, Inc.
//
// Licensed 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,
// See the License for the specific language governing permissions and
// limitations under the License.
package expression
import (
"github.com/juju/errors"
"github.com/pingcap/tidb/sessionctx"
"github.com/pingcap/tidb/util/chunk"
)
type columnEvaluator struct {
inputIdxToOutputIdxes map[int][]int
}
// run evaluates "Column" expressions.
// NOTE: It should be called after all the other expressions are evaluated
// since it will change the content of the input Chunk.
func (e *columnEvaluator) run(ctx sessionctx.Context, input, output *chunk.Chunk) {
for inputIdx, outputIdxes := range e.inputIdxToOutputIdxes {
output.SwapColumn(outputIdxes[0], input, inputIdx)
for i, length := 1, len(outputIdxes); i < length; i++ {
output.MakeRef(outputIdxes[0], outputIdxes[i])
}
}
}
type defaultEvaluator struct {
outputIdxes []int
exprs []Expression
vectorizable bool
}
func (e *defaultEvaluator) run(ctx sessionctx.Context, input, output *chunk.Chunk) error {
iter := chunk.NewIterator4Chunk(input)
if e.vectorizable {
for i := range e.outputIdxes {
err := evalOneColumn(ctx, e.exprs[i], iter, output, e.outputIdxes[i])
if err != nil {
return errors.Trace(err)
}
}
return nil
}
for row := iter.Begin(); row != iter.End(); row = iter.Next() {
for i := range e.outputIdxes {
err := evalOneCell(ctx, e.exprs[i], row, output, e.outputIdxes[i])
if err != nil {
return errors.Trace(err)
}
}
}
return nil
}
// EvaluatorSuit is responsible for the evaluation of a list of expressions.
// It separates them to "column" and "other" expressions and evaluates "other"
// expressions before "column" expressions.
type EvaluatorSuit struct {
*columnEvaluator // Evaluator for column expressions.
*defaultEvaluator // Evaluator for other expressions.
}
// NewEvaluatorSuit creates an EvaluatorSuit to evaluate all the exprs.
func NewEvaluatorSuit(exprs []Expression) *EvaluatorSuit {
e := &EvaluatorSuit{}
for i, expr := range exprs {
switch x := expr.(type) {
case *Column:
if e.columnEvaluator == nil {
e.columnEvaluator = &columnEvaluator{inputIdxToOutputIdxes: make(map[int][]int)}
}
inputIdx, outputIdx := x.Index, i
e.columnEvaluator.inputIdxToOutputIdxes[inputIdx] = append(e.columnEvaluator.inputIdxToOutputIdxes[inputIdx], outputIdx)
default:
if e.defaultEvaluator == nil {
e.defaultEvaluator = &defaultEvaluator{
outputIdxes: make([]int, 0, len(exprs)),
exprs: make([]Expression, 0, len(exprs)),
}
}
e.defaultEvaluator.exprs = append(e.defaultEvaluator.exprs, x)
e.defaultEvaluator.outputIdxes = append(e.defaultEvaluator.outputIdxes, i)
}
}
if e.defaultEvaluator != nil {
e.defaultEvaluator.vectorizable = Vectorizable(e.defaultEvaluator.exprs)
}
return e
}
// Run evaluates all the expressions hold by this EvaluatorSuit.
// NOTE: "defaultEvaluator" must be evaluated before "columnEvaluator".
func (e *EvaluatorSuit) Run(ctx sessionctx.Context, input, output *chunk.Chunk) error {
if e.defaultEvaluator != nil {
err := e.defaultEvaluator.run(ctx, input, output)
if err != nil {
return errors.Trace(err)
}
}
if e.columnEvaluator != nil {
e.columnEvaluator.run(ctx, input, output)
}
return nil
}