Files
tidb/executor/analyze.go
2017-03-22 22:16:45 +08:00

179 lines
4.6 KiB
Go

// Copyright 2017 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 executor
import (
"fmt"
"math/rand"
"github.com/juju/errors"
"github.com/pingcap/tidb/ast"
"github.com/pingcap/tidb/context"
"github.com/pingcap/tidb/expression"
"github.com/pingcap/tidb/meta"
"github.com/pingcap/tidb/model"
"github.com/pingcap/tidb/plan/statistics"
"github.com/pingcap/tidb/plan/statscache"
"github.com/pingcap/tidb/util/sqlexec"
"github.com/pingcap/tidb/util/types"
)
var _ Executor = &AnalyzeExec{}
// AnalyzeExec represents Analyze executor.
type AnalyzeExec struct {
schema *expression.Schema
tblInfo *model.TableInfo
ctx context.Context
idxOffsets []int
colOffsets []int
pkOffset int
Srcs []Executor
}
const (
maxSampleCount = 10000
defaultBucketCount = 256
)
// Schema implements the Executor Schema interface.
func (e *AnalyzeExec) Schema() *expression.Schema {
return e.schema
}
// Close implements the Executor Close interface.
func (e *AnalyzeExec) Close() error {
for _, src := range e.Srcs {
err := src.Close()
if err != nil {
return errors.Trace(err)
}
}
return nil
}
// Next implements the Executor Next interface.
func (e *AnalyzeExec) Next() (*Row, error) {
for _, src := range e.Srcs {
ae := src.(*AnalyzeExec)
var count int64 = -1
var sampleRows []*ast.Row
if ae.colOffsets != nil {
rs := &recordSet{executor: ae.Srcs[len(ae.Srcs)-1]}
var err error
count, sampleRows, err = collectSamples(rs)
if err != nil {
return nil, errors.Trace(err)
}
}
columnSamples := rowsToColumnSamples(sampleRows)
var pkRS ast.RecordSet
if ae.pkOffset != -1 {
offset := len(ae.Srcs) - 1
if ae.colOffsets != nil {
offset--
}
pkRS = &recordSet{executor: ae.Srcs[offset]}
}
idxRS := make([]ast.RecordSet, 0, len(ae.idxOffsets))
for i := range ae.idxOffsets {
idxRS = append(idxRS, &recordSet{executor: ae.Srcs[i]})
}
err := ae.buildStatisticsAndSaveToKV(count, columnSamples, idxRS, pkRS)
if err != nil {
return nil, errors.Trace(err)
}
}
return nil, nil
}
func (e *AnalyzeExec) buildStatisticsAndSaveToKV(count int64, columnSamples [][]types.Datum, idxRS []ast.RecordSet, pkRS ast.RecordSet) error {
txn := e.ctx.Txn()
statBuilder := &statistics.Builder{
Ctx: e.ctx,
TblInfo: e.tblInfo,
StartTS: int64(txn.StartTS()),
Count: count,
NumBuckets: defaultBucketCount,
ColumnSamples: columnSamples,
ColOffsets: e.colOffsets,
IdxRecords: idxRS,
IdxOffsets: e.idxOffsets,
PkRecords: pkRS,
PkOffset: e.pkOffset,
}
t, err := statBuilder.NewTable()
if err != nil {
return errors.Trace(err)
}
version := e.ctx.Txn().StartTS()
statscache.SetStatisticsTableCache(e.tblInfo.ID, t, version)
tpb, err := t.ToPB()
if err != nil {
return errors.Trace(err)
}
m := meta.NewMeta(txn)
err = m.SetTableStats(e.tblInfo.ID, tpb)
if err != nil {
return errors.Trace(err)
}
insertSQL := fmt.Sprintf("insert into mysql.stats_meta (version, table_id) values (%d, %d) on duplicate key update version = %d", version, e.tblInfo.ID, version)
_, _, err = e.ctx.(sqlexec.RestrictedSQLExecutor).ExecRestrictedSQL(e.ctx, insertSQL)
if err != nil {
return errors.Trace(err)
}
return nil
}
// collectSamples collects sample from the result set, using Reservoir Sampling algorithm.
// See https://en.wikipedia.org/wiki/Reservoir_sampling
func collectSamples(e ast.RecordSet) (count int64, samples []*ast.Row, err error) {
for {
row, err := e.Next()
if err != nil {
return count, samples, errors.Trace(err)
}
if row == nil {
break
}
if len(samples) < maxSampleCount {
samples = append(samples, row)
} else {
shouldAdd := rand.Int63n(count) < maxSampleCount
if shouldAdd {
idx := rand.Intn(maxSampleCount)
samples[idx] = row
}
}
count++
}
return count, samples, nil
}
func rowsToColumnSamples(rows []*ast.Row) [][]types.Datum {
if len(rows) == 0 {
return nil
}
columnSamples := make([][]types.Datum, len(rows[0].Data))
for i := range columnSamples {
columnSamples[i] = make([]types.Datum, len(rows))
}
for j, row := range rows {
for i, val := range row.Data {
columnSamples[i][j] = val
}
}
return columnSamples
}