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134 lines
4.1 KiB
134 lines
4.1 KiB
// Copyright 2018 PingCAP, Inc.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// See the License for the specific language governing permissions and
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// limitations under the License.
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package expression
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import (
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"github.com/pingcap/tidb/sessionctx"
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"github.com/pingcap/tidb/util/chunk"
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)
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type columnEvaluator struct {
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inputIdxToOutputIdxes map[int][]int
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}
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// run evaluates "Column" expressions.
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// NOTE: It should be called after all the other expressions are evaluated
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//
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// since it will change the content of the input Chunk.
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func (e *columnEvaluator) run(ctx sessionctx.Context, input, output *chunk.Chunk) error {
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for inputIdx, outputIdxes := range e.inputIdxToOutputIdxes {
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if err := output.SwapColumn(outputIdxes[0], input, inputIdx); err != nil {
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return err
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}
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for i, length := 1, len(outputIdxes); i < length; i++ {
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output.MakeRef(outputIdxes[0], outputIdxes[i])
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}
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}
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return nil
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}
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type defaultEvaluator struct {
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outputIdxes []int
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exprs []Expression
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vectorizable bool
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}
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func (e *defaultEvaluator) run(ctx sessionctx.Context, input, output *chunk.Chunk) error {
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iter := chunk.NewIterator4Chunk(input)
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if e.vectorizable {
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for i := range e.outputIdxes {
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if ctx.GetSessionVars().EnableVectorizedExpression && e.exprs[i].Vectorized() {
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if err := evalOneVec(ctx, e.exprs[i], input, output, e.outputIdxes[i]); err != nil {
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return err
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}
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continue
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}
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err := evalOneColumn(ctx, e.exprs[i], iter, output, e.outputIdxes[i])
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if err != nil {
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return err
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}
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}
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return nil
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}
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for row := iter.Begin(); row != iter.End(); row = iter.Next() {
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for i := range e.outputIdxes {
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err := evalOneCell(ctx, e.exprs[i], row, output, e.outputIdxes[i])
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if err != nil {
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return err
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}
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}
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}
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return nil
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}
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// EvaluatorSuite is responsible for the evaluation of a list of expressions.
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// It separates them to "column" and "other" expressions and evaluates "other"
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// expressions before "column" expressions.
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type EvaluatorSuite struct {
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*columnEvaluator // Evaluator for column expressions.
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*defaultEvaluator // Evaluator for other expressions.
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}
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// NewEvaluatorSuite creates an EvaluatorSuite to evaluate all the exprs.
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// avoidColumnEvaluator can be removed after column pool is supported.
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func NewEvaluatorSuite(exprs []Expression, avoidColumnEvaluator bool) *EvaluatorSuite {
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e := &EvaluatorSuite{}
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for i := 0; i < len(exprs); i++ {
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if col, isCol := exprs[i].(*Column); isCol && !avoidColumnEvaluator {
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if e.columnEvaluator == nil {
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e.columnEvaluator = &columnEvaluator{inputIdxToOutputIdxes: make(map[int][]int)}
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}
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inputIdx, outputIdx := col.Index, i
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e.columnEvaluator.inputIdxToOutputIdxes[inputIdx] = append(e.columnEvaluator.inputIdxToOutputIdxes[inputIdx], outputIdx)
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continue
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}
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if e.defaultEvaluator == nil {
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e.defaultEvaluator = &defaultEvaluator{
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outputIdxes: make([]int, 0, len(exprs)),
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exprs: make([]Expression, 0, len(exprs)),
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}
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}
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e.defaultEvaluator.exprs = append(e.defaultEvaluator.exprs, exprs[i])
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e.defaultEvaluator.outputIdxes = append(e.defaultEvaluator.outputIdxes, i)
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}
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if e.defaultEvaluator != nil {
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e.defaultEvaluator.vectorizable = Vectorizable(e.defaultEvaluator.exprs)
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}
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return e
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}
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// Vectorizable checks whether this EvaluatorSuite can use vectorizd execution mode.
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func (e *EvaluatorSuite) Vectorizable() bool {
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return e.defaultEvaluator == nil || e.defaultEvaluator.vectorizable
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}
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// Run evaluates all the expressions hold by this EvaluatorSuite.
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// NOTE: "defaultEvaluator" must be evaluated before "columnEvaluator".
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func (e *EvaluatorSuite) Run(ctx sessionctx.Context, input, output *chunk.Chunk) error {
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if e.defaultEvaluator != nil {
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err := e.defaultEvaluator.run(ctx, input, output)
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if err != nil {
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return err
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}
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}
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if e.columnEvaluator != nil {
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return e.columnEvaluator.run(ctx, input, output)
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}
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return nil
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}
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