120 lines
3.6 KiB
Go
120 lines
3.6 KiB
Go
// 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/juju/errors"
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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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// 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) {
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for inputIdx, outputIdxes := range e.inputIdxToOutputIdxes {
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output.SwapColumn(outputIdxes[0], input, inputIdx)
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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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}
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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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err := evalOneColumn(ctx, e.exprs[i], iter, output, e.outputIdxes[i])
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if err != nil {
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return errors.Trace(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 errors.Trace(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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// EvaluatorSuit 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 EvaluatorSuit 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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// NewEvaluatorSuit creates an EvaluatorSuit to evaluate all the exprs.
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func NewEvaluatorSuit(exprs []Expression) *EvaluatorSuit {
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e := &EvaluatorSuit{}
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for i, expr := range exprs {
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switch x := expr.(type) {
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case *Column:
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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 := x.Index, i
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e.columnEvaluator.inputIdxToOutputIdxes[inputIdx] = append(e.columnEvaluator.inputIdxToOutputIdxes[inputIdx], outputIdx)
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default:
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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, x)
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e.defaultEvaluator.outputIdxes = append(e.defaultEvaluator.outputIdxes, i)
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}
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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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// Run evaluates all the expressions hold by this EvaluatorSuit.
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// NOTE: "defaultEvaluator" must be evaluated before "columnEvaluator".
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func (e *EvaluatorSuit) 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 errors.Trace(err)
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}
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}
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if e.columnEvaluator != nil {
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e.columnEvaluator.run(ctx, input, output)
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}
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return nil
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}
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