Files
tidb/pkg/planner/core/stats.go

749 lines
29 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,
// 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.
package core
import (
"fmt"
"math"
"slices"
"strconv"
"strings"
"github.com/pingcap/errors"
"github.com/pingcap/tidb/pkg/domain"
"github.com/pingcap/tidb/pkg/expression"
"github.com/pingcap/tidb/pkg/infoschema"
"github.com/pingcap/tidb/pkg/kv"
"github.com/pingcap/tidb/pkg/meta/model"
"github.com/pingcap/tidb/pkg/parser/ast"
"github.com/pingcap/tidb/pkg/parser/mysql"
"github.com/pingcap/tidb/pkg/planner/cardinality"
"github.com/pingcap/tidb/pkg/planner/core/base"
"github.com/pingcap/tidb/pkg/planner/core/cost"
"github.com/pingcap/tidb/pkg/planner/core/operator/logicalop"
"github.com/pingcap/tidb/pkg/planner/property"
"github.com/pingcap/tidb/pkg/planner/util"
"github.com/pingcap/tidb/pkg/planner/util/debugtrace"
"github.com/pingcap/tidb/pkg/sessionctx"
"github.com/pingcap/tidb/pkg/sessionctx/stmtctx"
"github.com/pingcap/tidb/pkg/statistics"
"github.com/pingcap/tidb/pkg/statistics/asyncload"
"github.com/pingcap/tidb/pkg/table"
"github.com/pingcap/tidb/pkg/types"
h "github.com/pingcap/tidb/pkg/util/hint"
"github.com/pingcap/tidb/pkg/util/logutil"
"github.com/pingcap/tidb/pkg/util/ranger"
"go.uber.org/zap"
)
// RecursiveDeriveStats4Test is a exporter just for test.
func RecursiveDeriveStats4Test(p base.LogicalPlan) (*property.StatsInfo, error) {
return p.RecursiveDeriveStats(nil)
}
// GetStats4Test is a exporter just for test.
func GetStats4Test(p base.LogicalPlan) *property.StatsInfo {
return p.StatsInfo()
}
func deriveStats4LogicalTableScan(lp base.LogicalPlan) (_ *property.StatsInfo, err error) {
ts := lp.(*logicalop.LogicalTableScan)
initStats(ts.Source, nil)
// PushDownNot here can convert query 'not (a != 1)' to 'a = 1'.
exprCtx := ts.SCtx().GetExprCtx()
for i, expr := range ts.AccessConds {
// TODO The expressions may be shared by TableScan and several IndexScans, there would be redundant
// `PushDownNot` function call in multiple `DeriveStats` then.
ts.AccessConds[i] = expression.PushDownNot(exprCtx, expr)
}
ts.SetStats(deriveStatsByFilter(ts.Source, ts.AccessConds, nil))
// ts.Handle could be nil if PK is Handle, and PK column has been pruned.
// TODO: support clustered index.
if ts.HandleCols != nil {
// TODO: restrict mem usage of table ranges.
ts.Ranges, _, _, err = ranger.BuildTableRange(ts.AccessConds, ts.SCtx().GetRangerCtx(), ts.HandleCols.GetCol(0).RetType, 0)
} else {
isUnsigned := false
if ts.Source.TableInfo.PKIsHandle {
if pkColInfo := ts.Source.TableInfo.GetPkColInfo(); pkColInfo != nil {
isUnsigned = mysql.HasUnsignedFlag(pkColInfo.GetFlag())
}
}
ts.Ranges = ranger.FullIntRange(isUnsigned)
}
if err != nil {
return nil, err
}
return ts.StatsInfo(), nil
}
func deriveStats4LogicalIndexScan(lp base.LogicalPlan, selfSchema *expression.Schema) (*property.StatsInfo, error) {
is := lp.(*logicalop.LogicalIndexScan)
initStats(is.Source, nil)
exprCtx := is.SCtx().GetExprCtx()
for i, expr := range is.AccessConds {
is.AccessConds[i] = expression.PushDownNot(exprCtx, expr)
}
is.SetStats(deriveStatsByFilter(is.Source, is.AccessConds, nil))
if len(is.AccessConds) == 0 {
is.Ranges = ranger.FullRange()
}
is.IdxCols, is.IdxColLens = expression.IndexInfo2PrefixCols(is.Columns, selfSchema.Columns, is.Index)
is.FullIdxCols, is.FullIdxColLens = expression.IndexInfo2Cols(is.Columns, selfSchema.Columns, is.Index)
if !is.Index.Unique && !is.Index.Primary && len(is.Index.Columns) == len(is.IdxCols) {
handleCol := is.GetPKIsHandleCol(selfSchema)
if handleCol != nil && !mysql.HasUnsignedFlag(handleCol.RetType.GetFlag()) {
is.IdxCols = append(is.IdxCols, handleCol)
is.IdxColLens = append(is.IdxColLens, types.UnspecifiedLength)
}
}
return is.StatsInfo(), nil
}
func deriveStats4DataSource(lp base.LogicalPlan, colGroups [][]*expression.Column) (*property.StatsInfo, error) {
ds := lp.(*logicalop.DataSource)
if ds.StatsInfo() != nil && len(colGroups) == 0 {
return ds.StatsInfo(), nil
}
initStats(ds, colGroups)
if ds.StatsInfo() != nil {
// Just reload the GroupNDVs.
selectivity := ds.StatsInfo().RowCount / ds.TableStats.RowCount
ds.SetStats(ds.TableStats.Scale(selectivity))
return ds.StatsInfo(), nil
}
if ds.SCtx().GetSessionVars().StmtCtx.EnableOptimizerDebugTrace {
debugtrace.EnterContextCommon(ds.SCtx())
defer debugtrace.LeaveContextCommon(ds.SCtx())
}
// two preprocess here.
// 1: PushDownNot here can convert query 'not (a != 1)' to 'a = 1'.
// 2: EliminateNoPrecisionCast here can convert query 'cast(c<int> as bigint) = 1' to 'c = 1' to leverage access range.
exprCtx := ds.SCtx().GetExprCtx()
for i, expr := range ds.PushedDownConds {
ds.PushedDownConds[i] = expression.PushDownNot(exprCtx, expr)
ds.PushedDownConds[i] = expression.EliminateNoPrecisionLossCast(exprCtx, ds.PushedDownConds[i])
}
for _, path := range ds.PossibleAccessPaths {
if path.IsTablePath() {
continue
}
err := fillIndexPath(ds, path, ds.PushedDownConds)
if err != nil {
return nil, err
}
}
// TODO: Can we move ds.deriveStatsByFilter after pruning by heuristics? In this way some computation can be avoided
// when ds.PossibleAccessPaths are pruned.
ds.SetStats(deriveStatsByFilter(ds, ds.PushedDownConds, ds.PossibleAccessPaths))
err := derivePathStatsAndTryHeuristics(ds)
if err != nil {
return nil, err
}
if err := generateIndexMergePath(ds); err != nil {
return nil, err
}
if ds.SCtx().GetSessionVars().StmtCtx.EnableOptimizerDebugTrace {
debugTraceAccessPaths(ds.SCtx(), ds.PossibleAccessPaths)
}
ds.AccessPathMinSelectivity = getMinSelectivityFromPaths(ds.PossibleAccessPaths, float64(ds.TblColHists.RealtimeCount))
return ds.StatsInfo(), nil
}
func fillIndexPath(ds *logicalop.DataSource, path *util.AccessPath, conds []expression.Expression) error {
if ds.SCtx().GetSessionVars().StmtCtx.EnableOptimizerDebugTrace {
debugtrace.EnterContextCommon(ds.SCtx())
defer debugtrace.LeaveContextCommon(ds.SCtx())
}
path.Ranges = ranger.FullRange()
path.CountAfterAccess = float64(ds.StatisticTable.RealtimeCount)
path.IdxCols, path.IdxColLens = expression.IndexInfo2PrefixCols(ds.Columns, ds.Schema().Columns, path.Index)
path.FullIdxCols, path.FullIdxColLens = expression.IndexInfo2Cols(ds.Columns, ds.Schema().Columns, path.Index)
if !path.Index.Unique && !path.Index.Primary && len(path.Index.Columns) == len(path.IdxCols) {
handleCol := ds.GetPKIsHandleCol()
if handleCol != nil && !mysql.HasUnsignedFlag(handleCol.RetType.GetFlag()) {
alreadyHandle := false
for _, col := range path.IdxCols {
if col.ID == model.ExtraHandleID || col.EqualColumn(handleCol) {
alreadyHandle = true
}
}
// Don't add one column twice to the index. May cause unexpected errors.
if !alreadyHandle {
path.IdxCols = append(path.IdxCols, handleCol)
path.IdxColLens = append(path.IdxColLens, types.UnspecifiedLength)
// Also updates the map that maps the index id to its prefix column ids.
if len(ds.TableStats.HistColl.Idx2ColUniqueIDs[path.Index.ID]) == len(path.Index.Columns) {
ds.TableStats.HistColl.Idx2ColUniqueIDs[path.Index.ID] = append(ds.TableStats.HistColl.Idx2ColUniqueIDs[path.Index.ID], handleCol.UniqueID)
}
}
}
}
err := detachCondAndBuildRangeForPath(ds.SCtx(), path, conds, ds.TableStats.HistColl)
return err
}
// deriveIndexPathStats will fulfill the information that the AccessPath need.
// conds is the conditions used to generate the DetachRangeResult for path.
// isIm indicates whether this function is called to generate the partial path for IndexMerge.
func deriveIndexPathStats(ds *logicalop.DataSource, path *util.AccessPath, _ []expression.Expression, isIm bool) {
if ds.SCtx().GetSessionVars().StmtCtx.EnableOptimizerDebugTrace {
debugtrace.EnterContextCommon(ds.SCtx())
defer debugtrace.LeaveContextCommon(ds.SCtx())
}
if path.EqOrInCondCount == len(path.AccessConds) {
accesses, remained := path.SplitCorColAccessCondFromFilters(ds.SCtx(), path.EqOrInCondCount)
path.AccessConds = append(path.AccessConds, accesses...)
path.TableFilters = remained
if len(accesses) > 0 && ds.StatisticTable.Pseudo {
path.CountAfterAccess = cardinality.PseudoAvgCountPerValue(ds.StatisticTable)
} else {
selectivity := path.CountAfterAccess / float64(ds.StatisticTable.RealtimeCount)
for i := range accesses {
col := path.IdxCols[path.EqOrInCondCount+i]
ndv := cardinality.EstimateColumnNDV(ds.StatisticTable, col.ID)
ndv *= selectivity
if ndv < 1 {
ndv = 1.0
}
path.CountAfterAccess = path.CountAfterAccess / ndv
}
}
}
var indexFilters []expression.Expression
indexFilters, path.TableFilters = splitIndexFilterConditions(ds, path.TableFilters, path.FullIdxCols, path.FullIdxColLens)
path.IndexFilters = append(path.IndexFilters, indexFilters...)
// If the `CountAfterAccess` is less than `stats.RowCount`, there must be some inconsistent stats info.
// We prefer the `stats.RowCount` because it could use more stats info to calculate the selectivity.
if path.CountAfterAccess < ds.StatsInfo().RowCount && !isIm {
path.CountAfterAccess = math.Min(ds.StatsInfo().RowCount/cost.SelectionFactor, float64(ds.StatisticTable.RealtimeCount))
}
if path.IndexFilters != nil {
selectivity, _, err := cardinality.Selectivity(ds.SCtx(), ds.TableStats.HistColl, path.IndexFilters, nil)
if err != nil {
logutil.BgLogger().Debug("calculate selectivity failed, use selection factor", zap.Error(err))
selectivity = cost.SelectionFactor
}
if isIm {
path.CountAfterIndex = path.CountAfterAccess * selectivity
} else {
path.CountAfterIndex = math.Max(path.CountAfterAccess*selectivity, ds.StatsInfo().RowCount)
}
} else {
path.CountAfterIndex = path.CountAfterAccess
}
}
// deriveTablePathStats will fulfill the information that the AccessPath need.
// isIm indicates whether this function is called to generate the partial path for IndexMerge.
func deriveTablePathStats(ds *logicalop.DataSource, path *util.AccessPath, conds []expression.Expression, isIm bool) error {
if ds.SCtx().GetSessionVars().StmtCtx.EnableOptimizerDebugTrace {
debugtrace.EnterContextCommon(ds.SCtx())
defer debugtrace.LeaveContextCommon(ds.SCtx())
}
if path.IsCommonHandlePath {
return deriveCommonHandleTablePathStats(ds, path, conds, isIm)
}
var err error
path.CountAfterAccess = float64(ds.StatisticTable.RealtimeCount)
path.TableFilters = conds
var pkCol *expression.Column
isUnsigned := false
if ds.TableInfo.PKIsHandle {
if pkColInfo := ds.TableInfo.GetPkColInfo(); pkColInfo != nil {
isUnsigned = mysql.HasUnsignedFlag(pkColInfo.GetFlag())
pkCol = expression.ColInfo2Col(ds.Schema().Columns, pkColInfo)
}
} else {
pkCol = ds.Schema().GetExtraHandleColumn()
}
if pkCol == nil {
path.Ranges = ranger.FullIntRange(isUnsigned)
return nil
}
path.Ranges = ranger.FullIntRange(isUnsigned)
if len(conds) == 0 {
return nil
}
// for cnf condition combination, c=1 and c=2 and (1 member of (a)),
// c=1 and c=2 will derive invalid range represented by an access condition as constant of 0 (false).
// later this constant of 0 will be built as empty range.
path.AccessConds, path.TableFilters = ranger.DetachCondsForColumn(ds.SCtx().GetRangerCtx(), conds, pkCol)
// If there's no access cond, we try to find that whether there's expression containing correlated column that
// can be used to access data.
corColInAccessConds := false
if len(path.AccessConds) == 0 {
for i, filter := range path.TableFilters {
eqFunc, ok := filter.(*expression.ScalarFunction)
if !ok || eqFunc.FuncName.L != ast.EQ {
continue
}
lCol, lOk := eqFunc.GetArgs()[0].(*expression.Column)
if lOk && lCol.Equal(ds.SCtx().GetExprCtx().GetEvalCtx(), pkCol) {
_, rOk := eqFunc.GetArgs()[1].(*expression.CorrelatedColumn)
if rOk {
path.AccessConds = append(path.AccessConds, filter)
path.TableFilters = append(path.TableFilters[:i], path.TableFilters[i+1:]...)
corColInAccessConds = true
break
}
}
rCol, rOk := eqFunc.GetArgs()[1].(*expression.Column)
if rOk && rCol.Equal(ds.SCtx().GetExprCtx().GetEvalCtx(), pkCol) {
_, lOk := eqFunc.GetArgs()[0].(*expression.CorrelatedColumn)
if lOk {
path.AccessConds = append(path.AccessConds, filter)
path.TableFilters = append(path.TableFilters[:i], path.TableFilters[i+1:]...)
corColInAccessConds = true
break
}
}
}
}
if corColInAccessConds {
path.CountAfterAccess = 1
return nil
}
var remainedConds []expression.Expression
path.Ranges, path.AccessConds, remainedConds, err = ranger.BuildTableRange(path.AccessConds, ds.SCtx().GetRangerCtx(), pkCol.RetType, ds.SCtx().GetSessionVars().RangeMaxSize)
path.TableFilters = append(path.TableFilters, remainedConds...)
if err != nil {
return err
}
path.CountAfterAccess, err = cardinality.GetRowCountByIntColumnRanges(ds.SCtx(), &ds.StatisticTable.HistColl, pkCol.ID, path.Ranges)
// If the `CountAfterAccess` is less than `stats.RowCount`, there must be some inconsistent stats info.
// We prefer the `stats.RowCount` because it could use more stats info to calculate the selectivity.
if path.CountAfterAccess < ds.StatsInfo().RowCount && !isIm {
path.CountAfterAccess = math.Min(ds.StatsInfo().RowCount/cost.SelectionFactor, float64(ds.StatisticTable.RealtimeCount))
}
return err
}
func deriveCommonHandleTablePathStats(ds *logicalop.DataSource, path *util.AccessPath, conds []expression.Expression, isIm bool) error {
path.CountAfterAccess = float64(ds.StatisticTable.RealtimeCount)
path.Ranges = ranger.FullNotNullRange()
path.IdxCols, path.IdxColLens = expression.IndexInfo2PrefixCols(ds.Columns, ds.Schema().Columns, path.Index)
path.FullIdxCols, path.FullIdxColLens = expression.IndexInfo2Cols(ds.Columns, ds.Schema().Columns, path.Index)
if len(conds) == 0 {
return nil
}
if err := detachCondAndBuildRangeForPath(ds.SCtx(), path, conds, ds.TableStats.HistColl); err != nil {
return err
}
if path.EqOrInCondCount == len(path.AccessConds) {
accesses, remained := path.SplitCorColAccessCondFromFilters(ds.SCtx(), path.EqOrInCondCount)
path.AccessConds = append(path.AccessConds, accesses...)
path.TableFilters = remained
if len(accesses) > 0 && ds.StatisticTable.Pseudo {
path.CountAfterAccess = cardinality.PseudoAvgCountPerValue(ds.StatisticTable)
} else {
selectivity := path.CountAfterAccess / float64(ds.StatisticTable.RealtimeCount)
for i := range accesses {
col := path.IdxCols[path.EqOrInCondCount+i]
ndv := cardinality.EstimateColumnNDV(ds.StatisticTable, col.ID)
ndv *= selectivity
if ndv < 1 {
ndv = 1.0
}
path.CountAfterAccess = path.CountAfterAccess / ndv
}
}
}
// If the `CountAfterAccess` is less than `stats.RowCount`, there must be some inconsistent stats info.
// We prefer the `stats.RowCount` because it could use more stats info to calculate the selectivity.
if path.CountAfterAccess < ds.StatsInfo().RowCount && !isIm {
path.CountAfterAccess = math.Min(ds.StatsInfo().RowCount/cost.SelectionFactor, float64(ds.StatisticTable.RealtimeCount))
}
return nil
}
func detachCondAndBuildRangeForPath(
sctx base.PlanContext,
path *util.AccessPath,
conds []expression.Expression,
histColl *statistics.HistColl,
) error {
if len(path.IdxCols) == 0 {
path.TableFilters = conds
return nil
}
res, err := ranger.DetachCondAndBuildRangeForIndex(sctx.GetRangerCtx(), conds, path.IdxCols, path.IdxColLens, sctx.GetSessionVars().RangeMaxSize)
if err != nil {
return err
}
path.Ranges = res.Ranges
path.AccessConds = res.AccessConds
path.TableFilters = res.RemainedConds
path.EqCondCount = res.EqCondCount
path.EqOrInCondCount = res.EqOrInCount
path.IsDNFCond = res.IsDNFCond
path.MinAccessCondsForDNFCond = res.MinAccessCondsForDNFCond
path.ConstCols = make([]bool, len(path.IdxCols))
if res.ColumnValues != nil {
for i := range path.ConstCols {
path.ConstCols[i] = res.ColumnValues[i] != nil
}
}
path.CountAfterAccess, err = cardinality.GetRowCountByIndexRanges(sctx, histColl, path.Index.ID, path.Ranges)
return err
}
func getMinSelectivityFromPaths(paths []*util.AccessPath, totalRowCount float64) float64 {
minSelectivity := 1.0
if totalRowCount <= 0 {
return minSelectivity
}
for _, path := range paths {
// For table path and index merge path, AccessPath.CountAfterIndex is not set and meaningless,
// but we still consider their AccessPath.CountAfterAccess.
if path.IsTablePath() || path.PartialIndexPaths != nil {
minSelectivity = min(minSelectivity, path.CountAfterAccess/totalRowCount)
continue
}
minSelectivity = min(minSelectivity, path.CountAfterIndex/totalRowCount)
}
return minSelectivity
}
func getGroupNDVs(ds *logicalop.DataSource, colGroups [][]*expression.Column) []property.GroupNDV {
if colGroups == nil {
return nil
}
tbl := ds.TableStats.HistColl
ndvs := make([]property.GroupNDV, 0, len(colGroups))
tbl.ForEachIndexImmutable(func(idxID int64, idx *statistics.Index) bool {
colsLen := len(tbl.Idx2ColUniqueIDs[idxID])
// tbl.Idx2ColUniqueIDs may only contain the prefix of index columns.
// But it may exceeds the total index since the index would contain the handle column if it's not a unique index.
// We append the handle at fillIndexPath.
if colsLen < len(idx.Info.Columns) {
return false
} else if colsLen > len(idx.Info.Columns) {
colsLen--
}
idxCols := make([]int64, colsLen)
copy(idxCols, tbl.Idx2ColUniqueIDs[idxID])
slices.Sort(idxCols)
for _, g := range colGroups {
// We only want those exact matches.
if len(g) != colsLen {
return false
}
match := true
for i, col := range g {
// Both slices are sorted according to UniqueID.
if col.UniqueID != idxCols[i] {
match = false
break
}
}
if match {
ndv := property.GroupNDV{
Cols: idxCols,
NDV: float64(idx.NDV),
}
ndvs = append(ndvs, ndv)
return true
}
}
return false
})
return ndvs
}
// getTblInfoForUsedStatsByPhysicalID get table name, partition name and HintedTable that will be used to record used stats.
func getTblInfoForUsedStatsByPhysicalID(sctx base.PlanContext, id int64) (fullName string, tblInfo *model.TableInfo) {
fullName = "tableID " + strconv.FormatInt(id, 10)
is := domain.GetDomain(sctx).InfoSchema()
var tbl table.Table
var partDef *model.PartitionDefinition
tbl, partDef = infoschema.FindTableByTblOrPartID(is, id)
if tbl == nil || tbl.Meta() == nil {
return
}
tblInfo = tbl.Meta()
fullName = tblInfo.Name.O
if partDef != nil {
fullName += " " + partDef.Name.O
} else if pi := tblInfo.GetPartitionInfo(); pi != nil && len(pi.Definitions) > 0 {
fullName += " global"
}
return
}
func initStats(ds *logicalop.DataSource, colGroups [][]*expression.Column) {
if ds.TableStats != nil {
// Reload GroupNDVs since colGroups may have changed.
ds.TableStats.GroupNDVs = getGroupNDVs(ds, colGroups)
return
}
if ds.StatisticTable == nil {
ds.StatisticTable = getStatsTable(ds.SCtx(), ds.TableInfo, ds.PhysicalTableID)
}
tableStats := &property.StatsInfo{
RowCount: float64(ds.StatisticTable.RealtimeCount),
ColNDVs: make(map[int64]float64, ds.Schema().Len()),
HistColl: ds.StatisticTable.GenerateHistCollFromColumnInfo(ds.TableInfo, ds.TblCols),
StatsVersion: ds.StatisticTable.Version,
}
if ds.StatisticTable.Pseudo {
tableStats.StatsVersion = statistics.PseudoVersion
}
statsRecord := ds.SCtx().GetSessionVars().StmtCtx.GetUsedStatsInfo(true)
name, tblInfo := getTblInfoForUsedStatsByPhysicalID(ds.SCtx(), ds.PhysicalTableID)
statsRecord.RecordUsedInfo(ds.PhysicalTableID, &stmtctx.UsedStatsInfoForTable{
Name: name,
TblInfo: tblInfo,
Version: tableStats.StatsVersion,
RealtimeCount: tableStats.HistColl.RealtimeCount,
ModifyCount: tableStats.HistColl.ModifyCount,
ColAndIdxStatus: ds.StatisticTable.ColAndIdxExistenceMap,
})
for _, col := range ds.Schema().Columns {
tableStats.ColNDVs[col.UniqueID] = cardinality.EstimateColumnNDV(ds.StatisticTable, col.ID)
}
ds.TableStats = tableStats
ds.TableStats.GroupNDVs = getGroupNDVs(ds, colGroups)
ds.TblColHists = ds.StatisticTable.ID2UniqueID(ds.TblCols)
for _, col := range ds.TableInfo.Columns {
if col.State != model.StatePublic {
continue
}
// If we enable lite stats init or we just found out the meta info of the column is missed, we need to register columns for async load.
_, isLoadNeeded, _ := ds.StatisticTable.ColumnIsLoadNeeded(col.ID, false)
if isLoadNeeded {
asyncload.AsyncLoadHistogramNeededItems.Insert(model.TableItemID{
TableID: ds.TableInfo.ID,
ID: col.ID,
IsIndex: false,
IsSyncLoadFailed: ds.SCtx().GetSessionVars().StmtCtx.StatsLoad.Timeout > 0,
}, false)
}
}
}
func deriveStatsByFilter(ds *logicalop.DataSource, conds expression.CNFExprs, filledPaths []*util.AccessPath) *property.StatsInfo {
if ds.SCtx().GetSessionVars().StmtCtx.EnableOptimizerDebugTrace {
debugtrace.EnterContextCommon(ds.SCtx())
defer debugtrace.LeaveContextCommon(ds.SCtx())
}
selectivity, _, err := cardinality.Selectivity(ds.SCtx(), ds.TableStats.HistColl, conds, filledPaths)
if err != nil {
logutil.BgLogger().Debug("something wrong happened, use the default selectivity", zap.Error(err))
selectivity = cost.SelectionFactor
}
// TODO: remove NewHistCollBySelectivity later on.
// if ds.SCtx().GetSessionVars().OptimizerSelectivityLevel >= 1 {
// Only '0' is suggested, see https://docs.pingcap.com/zh/tidb/stable/system-variables#tidb_optimizer_selectivity_level.
// stats.HistColl = stats.HistColl.NewHistCollBySelectivity(ds.SCtx(), nodes)
// }
return ds.TableStats.Scale(selectivity)
}
// We bind logic of derivePathStats and tryHeuristics together. When some path matches the heuristic rule, we don't need
// to derive stats of subsequent paths. In this way we can save unnecessary computation of derivePathStats.
func derivePathStatsAndTryHeuristics(ds *logicalop.DataSource) error {
if ds.SCtx().GetSessionVars().StmtCtx.EnableOptimizerDebugTrace {
debugtrace.EnterContextCommon(ds.SCtx())
defer debugtrace.LeaveContextCommon(ds.SCtx())
}
uniqueIdxsWithDoubleScan := make([]*util.AccessPath, 0, len(ds.PossibleAccessPaths))
singleScanIdxs := make([]*util.AccessPath, 0, len(ds.PossibleAccessPaths))
var (
selected, uniqueBest, refinedBest *util.AccessPath
isRefinedPath bool
)
// step1: if user prefer tiFlash store type, tiFlash path should always be built anyway ahead.
var tiflashPath *util.AccessPath
if ds.PreferStoreType&h.PreferTiFlash != 0 {
for _, path := range ds.PossibleAccessPaths {
if path.StoreType == kv.TiFlash {
err := deriveTablePathStats(ds, path, ds.PushedDownConds, false)
if err != nil {
return err
}
path.IsSingleScan = true
tiflashPath = path
break
}
}
}
// step2: kv path should follow the heuristic rules.
for _, path := range ds.PossibleAccessPaths {
if path.IsTablePath() {
err := deriveTablePathStats(ds, path, ds.PushedDownConds, false)
if err != nil {
return err
}
path.IsSingleScan = true
} else {
deriveIndexPathStats(ds, path, ds.PushedDownConds, false)
path.IsSingleScan = isSingleScan(ds, path.FullIdxCols, path.FullIdxColLens)
}
// step: 3
// Try some heuristic rules to select access path.
// tiFlash path also have table-range-scan (range point like here) to be heuristic treated.
if len(path.Ranges) == 0 {
selected = path
break
}
if path.OnlyPointRange(ds.SCtx().GetSessionVars().StmtCtx.TypeCtx()) {
if path.IsTablePath() || path.Index.Unique {
if path.IsSingleScan {
selected = path
break
}
uniqueIdxsWithDoubleScan = append(uniqueIdxsWithDoubleScan, path)
}
} else if path.IsSingleScan {
singleScanIdxs = append(singleScanIdxs, path)
}
}
if selected == nil && len(uniqueIdxsWithDoubleScan) > 0 {
uniqueIdxAccessCols := make([]util.Col2Len, 0, len(uniqueIdxsWithDoubleScan))
for _, uniqueIdx := range uniqueIdxsWithDoubleScan {
uniqueIdxAccessCols = append(uniqueIdxAccessCols, uniqueIdx.GetCol2LenFromAccessConds(ds.SCtx()))
// Find the unique index with the minimal number of ranges as `uniqueBest`.
/*
If the number of scan ranges are equal, choose the one with the least table predicates - meaning the unique index with the most index predicates.
Because the most index predicates means that it is more likely to fetch 0 index rows.
Example in the test "TestPointgetIndexChoosen".
*/
if uniqueBest == nil || len(uniqueIdx.Ranges) < len(uniqueBest.Ranges) ||
(len(uniqueIdx.Ranges) == len(uniqueBest.Ranges) && len(uniqueIdx.TableFilters) < len(uniqueBest.TableFilters)) {
uniqueBest = uniqueIdx
}
}
// `uniqueBest` may not always be the best.
// ```
// create table t(a int, b int, c int, unique index idx_b(b), index idx_b_c(b, c));
// select b, c from t where b = 5 and c > 10;
// ```
// In the case, `uniqueBest` is `idx_b`. However, `idx_b_c` is better than `idx_b`.
// Hence, for each index in `singleScanIdxs`, we check whether it is better than some index in `uniqueIdxsWithDoubleScan`.
// If yes, the index is a refined one. We find the refined index with the minimal number of ranges as `refineBest`.
for _, singleScanIdx := range singleScanIdxs {
col2Len := singleScanIdx.GetCol2LenFromAccessConds(ds.SCtx())
for _, uniqueIdxCol2Len := range uniqueIdxAccessCols {
accessResult, comparable1 := util.CompareCol2Len(col2Len, uniqueIdxCol2Len)
if comparable1 && accessResult == 1 {
if refinedBest == nil || len(singleScanIdx.Ranges) < len(refinedBest.Ranges) {
refinedBest = singleScanIdx
}
}
}
}
// `refineBest` may not always be better than `uniqueBest`.
// ```
// create table t(a int, b int, c int, d int, unique index idx_a(a), unique index idx_b_c(b, c), unique index idx_b_c_a_d(b, c, a, d));
// select a, b, c from t where a = 1 and b = 2 and c in (1, 2, 3, 4, 5);
// ```
// In the case, `refinedBest` is `idx_b_c_a_d` and `uniqueBest` is `a`. `idx_b_c_a_d` needs to access five points while `idx_a`
// only needs one point access and one table access.
// Hence we should compare `len(refinedBest.Ranges)` and `2*len(uniqueBest.Ranges)` to select the better one.
if refinedBest != nil && (uniqueBest == nil || len(refinedBest.Ranges) < 2*len(uniqueBest.Ranges)) {
selected = refinedBest
isRefinedPath = true
} else {
selected = uniqueBest
}
}
// heuristic rule pruning other path should consider hint prefer.
// If no hints and some path matches a heuristic rule, just remove other possible paths.
if selected != nil {
ds.PossibleAccessPaths[0] = selected
ds.PossibleAccessPaths = ds.PossibleAccessPaths[:1]
// if user wanna tiFlash read, while current heuristic choose a TiKV path. so we shouldn't prune tiFlash path.
keep := ds.PreferStoreType&h.PreferTiFlash != 0 && selected.StoreType != kv.TiFlash
if keep {
// also keep tiflash path as well.
ds.PossibleAccessPaths = append(ds.PossibleAccessPaths, tiflashPath)
return nil
}
var tableName string
if ds.TableAsName.O == "" {
tableName = ds.TableInfo.Name.O
} else {
tableName = ds.TableAsName.O
}
var sb strings.Builder
if selected.IsTablePath() {
// TODO: primary key / handle / real name?
fmt.Fprintf(&sb, "handle of %s is selected since the path only has point ranges", tableName)
} else {
if selected.Index.Unique {
sb.WriteString("unique ")
}
sb.WriteString(fmt.Sprintf("index %s of %s is selected since the path", selected.Index.Name.O, tableName))
if isRefinedPath {
sb.WriteString(" only fetches limited number of rows")
} else {
sb.WriteString(" only has point ranges")
}
if selected.IsSingleScan {
sb.WriteString(" with single scan")
} else {
sb.WriteString(" with double scan")
}
}
if ds.SCtx().GetSessionVars().StmtCtx.InVerboseExplain {
ds.SCtx().GetSessionVars().StmtCtx.AppendNote(errors.NewNoStackError(sb.String()))
} else {
ds.SCtx().GetSessionVars().StmtCtx.AppendExtraNote(errors.NewNoStackError(sb.String()))
}
}
return nil
}
// loadTableStats loads the stats of the table and store it in the statement `UsedStatsInfo` if it didn't exist
func loadTableStats(ctx sessionctx.Context, tblInfo *model.TableInfo, pid int64) {
statsRecord := ctx.GetSessionVars().StmtCtx.GetUsedStatsInfo(true)
if statsRecord.GetUsedInfo(pid) != nil {
return
}
pctx := ctx.GetPlanCtx()
tableStats := getStatsTable(pctx, tblInfo, pid)
name := tblInfo.Name.O
partInfo := tblInfo.GetPartitionInfo()
if partInfo != nil {
for _, p := range partInfo.Definitions {
if p.ID == pid {
name += " " + p.Name.O
}
}
}
usedStats := &stmtctx.UsedStatsInfoForTable{
Name: name,
TblInfo: tblInfo,
RealtimeCount: tableStats.HistColl.RealtimeCount,
ModifyCount: tableStats.HistColl.ModifyCount,
Version: tableStats.Version,
}
if tableStats.Pseudo {
usedStats.Version = statistics.PseudoVersion
}
statsRecord.RecordUsedInfo(pid, usedStats)
}