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rule_aggregation_push_down.go
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rule_aggregation_push_down.go
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// Copyright 2016 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 plan
import (
"fmt"
"github.com/pingcap/tidb/ast"
"github.com/pingcap/tidb/expression"
"github.com/pingcap/tidb/expression/aggregation"
"github.com/pingcap/tidb/model"
"github.com/pingcap/tidb/mysql"
"github.com/pingcap/tidb/sessionctx"
"github.com/pingcap/tidb/types"
)
type aggregationOptimizer struct {
}
// isDecomposable checks if an aggregate function is decomposable. An aggregation function $F$ is decomposable
// if there exist aggregation functions F_1 and F_2 such that F(S_1 union all S_2) = F_2(F_1(S_1),F_1(S_2)),
// where S_1 and S_2 are two sets of values. We call S_1 and S_2 partial groups.
// It's easy to see that max, min, first row is decomposable, no matter whether it's distinct, but sum(distinct) and
// count(distinct) is not.
// Currently we don't support avg and concat.
func (a *aggregationOptimizer) isDecomposable(fun *aggregation.AggFuncDesc) bool {
switch fun.Name {
case ast.AggFuncAvg, ast.AggFuncGroupConcat:
// TODO: Support avg push down.
return false
case ast.AggFuncMax, ast.AggFuncMin, ast.AggFuncFirstRow:
return true
case ast.AggFuncSum, ast.AggFuncCount:
return !fun.HasDistinct
default:
return false
}
}
// getAggFuncChildIdx gets which children it belongs to, 0 stands for left, 1 stands for right, -1 stands for both.
func (a *aggregationOptimizer) getAggFuncChildIdx(aggFunc *aggregation.AggFuncDesc, schema *expression.Schema) int {
fromLeft, fromRight := false, false
var cols []*expression.Column
cols = expression.ExtractColumnsFromExpressions(cols, aggFunc.Args, nil)
for _, col := range cols {
if schema.Contains(col) {
fromLeft = true
} else {
fromRight = true
}
}
if fromLeft && fromRight {
return -1
} else if fromLeft {
return 0
}
return 1
}
// collectAggFuncs collects all aggregate functions and splits them into two parts: "leftAggFuncs" and "rightAggFuncs" whose
// arguments are all from left child or right child separately. If some aggregate functions have the arguments that have
// columns both from left and right children, the whole aggregation is forbidden to push down.
func (a *aggregationOptimizer) collectAggFuncs(agg *LogicalAggregation, join *LogicalJoin) (valid bool, leftAggFuncs, rightAggFuncs []*aggregation.AggFuncDesc) {
valid = true
leftChild := join.children[0]
for _, aggFunc := range agg.AggFuncs {
if !a.isDecomposable(aggFunc) {
return false, nil, nil
}
index := a.getAggFuncChildIdx(aggFunc, leftChild.Schema())
switch index {
case 0:
leftAggFuncs = append(leftAggFuncs, aggFunc)
case 1:
rightAggFuncs = append(rightAggFuncs, aggFunc)
default:
return false, nil, nil
}
}
return
}
// collectGbyCols collects all columns from gby-items and join-conditions and splits them into two parts: "leftGbyCols" and
// "rightGbyCols". e.g. For query "SELECT SUM(B.id) FROM A, B WHERE A.c1 = B.c1 AND A.c2 != B.c2 GROUP BY B.c3" , the optimized
// query should be "SELECT SUM(B.agg) FROM A, (SELECT SUM(id) as agg, c1, c2, c3 FROM B GROUP BY id, c1, c2, c3) as B
// WHERE A.c1 = B.c1 AND A.c2 != B.c2 GROUP BY B.c3". As you see, all the columns appearing in join-conditions should be
// treated as group by columns in join subquery.
func (a *aggregationOptimizer) collectGbyCols(agg *LogicalAggregation, join *LogicalJoin) (leftGbyCols, rightGbyCols []*expression.Column) {
leftChild := join.children[0]
ctx := agg.ctx
for _, gbyExpr := range agg.GroupByItems {
cols := expression.ExtractColumns(gbyExpr)
for _, col := range cols {
if leftChild.Schema().Contains(col) {
leftGbyCols = append(leftGbyCols, col)
} else {
rightGbyCols = append(rightGbyCols, col)
}
}
}
// extract equal conditions
for _, eqFunc := range join.EqualConditions {
leftGbyCols = a.addGbyCol(ctx, leftGbyCols, eqFunc.GetArgs()[0].(*expression.Column))
rightGbyCols = a.addGbyCol(ctx, rightGbyCols, eqFunc.GetArgs()[1].(*expression.Column))
}
for _, leftCond := range join.LeftConditions {
cols := expression.ExtractColumns(leftCond)
leftGbyCols = a.addGbyCol(ctx, leftGbyCols, cols...)
}
for _, rightCond := range join.RightConditions {
cols := expression.ExtractColumns(rightCond)
rightGbyCols = a.addGbyCol(ctx, rightGbyCols, cols...)
}
for _, otherCond := range join.OtherConditions {
cols := expression.ExtractColumns(otherCond)
for _, col := range cols {
if leftChild.Schema().Contains(col) {
leftGbyCols = a.addGbyCol(ctx, leftGbyCols, col)
} else {
rightGbyCols = a.addGbyCol(ctx, rightGbyCols, col)
}
}
}
return
}
func (a *aggregationOptimizer) splitAggFuncsAndGbyCols(agg *LogicalAggregation, join *LogicalJoin) (valid bool,
leftAggFuncs, rightAggFuncs []*aggregation.AggFuncDesc,
leftGbyCols, rightGbyCols []*expression.Column) {
valid, leftAggFuncs, rightAggFuncs = a.collectAggFuncs(agg, join)
if !valid {
return
}
leftGbyCols, rightGbyCols = a.collectGbyCols(agg, join)
return
}
// addGbyCol adds a column to gbyCols. If a group by column has existed, it will not be added repeatedly.
func (a *aggregationOptimizer) addGbyCol(ctx sessionctx.Context, gbyCols []*expression.Column, cols ...*expression.Column) []*expression.Column {
for _, c := range cols {
duplicate := false
for _, gbyCol := range gbyCols {
if c.Equal(ctx, gbyCol) {
duplicate = true
break
}
}
if !duplicate {
gbyCols = append(gbyCols, c)
}
}
return gbyCols
}
// checkValidJoin checks if this join should be pushed across.
func (a *aggregationOptimizer) checkValidJoin(join *LogicalJoin) bool {
return join.JoinType == InnerJoin || join.JoinType == LeftOuterJoin || join.JoinType == RightOuterJoin
}
// decompose splits an aggregate function to two parts: a final mode function and a partial mode function. Currently
// there are no differences between partial mode and complete mode, so we can confuse them.
func (a *aggregationOptimizer) decompose(ctx sessionctx.Context, aggFunc *aggregation.AggFuncDesc, schema *expression.Schema) ([]*aggregation.AggFuncDesc, *expression.Schema) {
// Result is a slice because avg should be decomposed to sum and count. Currently we don't process this case.
result := []*aggregation.AggFuncDesc{aggFunc.Clone()}
for _, aggFunc := range result {
schema.Append(&expression.Column{
ColName: model.NewCIStr(fmt.Sprintf("join_agg_%d", schema.Len())), // useless but for debug
UniqueID: ctx.GetSessionVars().AllocPlanColumnID(),
RetType: aggFunc.RetTp,
})
}
aggFunc.Args = expression.Column2Exprs(schema.Columns[schema.Len()-len(result):])
aggFunc.Mode = aggregation.FinalMode
return result, schema
}
// tryToPushDownAgg tries to push down an aggregate function into a join path. If all aggFuncs are first row, we won't
// process it temporarily. If not, We will add additional group by columns and first row functions. We make a new aggregation operator.
// If the pushed aggregation is grouped by unique key, it's no need to push it down.
func (a *aggregationOptimizer) tryToPushDownAgg(aggFuncs []*aggregation.AggFuncDesc, gbyCols []*expression.Column, join *LogicalJoin, childIdx int) LogicalPlan {
child := join.children[childIdx]
if aggregation.IsAllFirstRow(aggFuncs) {
return child
}
// If the join is multiway-join, we forbid pushing down.
if _, ok := join.children[childIdx].(*LogicalJoin); ok {
return child
}
tmpSchema := expression.NewSchema(gbyCols...)
for _, key := range child.Schema().Keys {
if tmpSchema.ColumnsIndices(key) != nil {
return child
}
}
agg := a.makeNewAgg(join.ctx, aggFuncs, gbyCols)
agg.SetChildren(child)
// If agg has no group-by item, it will return a default value, which may cause some bugs.
// So here we add a group-by item forcely.
if len(agg.GroupByItems) == 0 {
agg.GroupByItems = []expression.Expression{&expression.Constant{
Value: types.NewDatum(0),
RetType: types.NewFieldType(mysql.TypeLong)}}
}
if (childIdx == 0 && join.JoinType == RightOuterJoin) || (childIdx == 1 && join.JoinType == LeftOuterJoin) {
var existsDefaultValues bool
join.DefaultValues, existsDefaultValues = a.getDefaultValues(agg)
if !existsDefaultValues {
return child
}
}
return agg
}
func (a *aggregationOptimizer) getDefaultValues(agg *LogicalAggregation) ([]types.Datum, bool) {
defaultValues := make([]types.Datum, 0, agg.Schema().Len())
for _, aggFunc := range agg.AggFuncs {
value, existsDefaultValue := aggFunc.EvalNullValueInOuterJoin(agg.ctx, agg.children[0].Schema())
if !existsDefaultValue {
return nil, false
}
defaultValues = append(defaultValues, value)
}
return defaultValues, true
}
func (a *aggregationOptimizer) checkAnyCountAndSum(aggFuncs []*aggregation.AggFuncDesc) bool {
for _, fun := range aggFuncs {
if fun.Name == ast.AggFuncSum || fun.Name == ast.AggFuncCount {
return true
}
}
return false
}
func (a *aggregationOptimizer) makeNewAgg(ctx sessionctx.Context, aggFuncs []*aggregation.AggFuncDesc, gbyCols []*expression.Column) *LogicalAggregation {
agg := LogicalAggregation{
GroupByItems: expression.Column2Exprs(gbyCols),
groupByCols: gbyCols,
}.init(ctx)
aggLen := len(aggFuncs) + len(gbyCols)
newAggFuncDescs := make([]*aggregation.AggFuncDesc, 0, aggLen)
schema := expression.NewSchema(make([]*expression.Column, 0, aggLen)...)
for _, aggFunc := range aggFuncs {
var newFuncs []*aggregation.AggFuncDesc
newFuncs, schema = a.decompose(ctx, aggFunc, schema)
newAggFuncDescs = append(newAggFuncDescs, newFuncs...)
}
for _, gbyCol := range gbyCols {
firstRow := aggregation.NewAggFuncDesc(agg.ctx, ast.AggFuncFirstRow, []expression.Expression{gbyCol}, false)
newCol, _ := gbyCol.Clone().(*expression.Column)
newCol.RetType = firstRow.RetTp
newAggFuncDescs = append(newAggFuncDescs, firstRow)
schema.Append(newCol)
}
agg.AggFuncs = newAggFuncDescs
agg.SetSchema(schema)
// TODO: Add a Projection if any argument of aggregate funcs or group by items are scalar functions.
// agg.buildProjectionIfNecessary()
return agg
}
// pushAggCrossUnion will try to push the agg down to the union. If the new aggregation's group-by columns doesn't contain unique key.
// We will return the new aggregation. Otherwise we will transform the aggregation to projection.
func (a *aggregationOptimizer) pushAggCrossUnion(agg *LogicalAggregation, unionSchema *expression.Schema, unionChild LogicalPlan) LogicalPlan {
ctx := agg.ctx
newAgg := LogicalAggregation{
AggFuncs: make([]*aggregation.AggFuncDesc, 0, len(agg.AggFuncs)),
GroupByItems: make([]expression.Expression, 0, len(agg.GroupByItems)),
}.init(ctx)
newAgg.SetSchema(agg.schema.Clone())
for _, aggFunc := range agg.AggFuncs {
newAggFunc := aggFunc.Clone()
newArgs := make([]expression.Expression, 0, len(newAggFunc.Args))
for _, arg := range newAggFunc.Args {
newArgs = append(newArgs, expression.ColumnSubstitute(arg, unionSchema, expression.Column2Exprs(unionChild.Schema().Columns)))
}
newAggFunc.Args = newArgs
newAgg.AggFuncs = append(newAgg.AggFuncs, newAggFunc)
}
for _, gbyExpr := range agg.GroupByItems {
newExpr := expression.ColumnSubstitute(gbyExpr, unionSchema, expression.Column2Exprs(unionChild.Schema().Columns))
newAgg.GroupByItems = append(newAgg.GroupByItems, newExpr)
}
newAgg.collectGroupByColumns()
tmpSchema := expression.NewSchema(newAgg.groupByCols...)
// e.g. Union distinct will add a aggregation like `select join_agg_0, join_agg_1, join_agg_2 from t group by a, b, c` above UnionAll.
// And the pushed agg will be something like `select a, b, c, a, b, c from t group by a, b, c`. So if we just return child as join does,
// this will cause error during executor phase.
for _, key := range unionChild.Schema().Keys {
if tmpSchema.ColumnsIndices(key) != nil {
proj := a.convertAggToProj(newAgg)
proj.SetChildren(unionChild)
return proj
}
}
newAgg.SetChildren(unionChild)
return newAgg
}
func (a *aggregationOptimizer) optimize(p LogicalPlan) (LogicalPlan, error) {
if !p.context().GetSessionVars().AllowAggPushDown {
return p, nil
}
a.aggPushDown(p)
return p, nil
}
// aggPushDown tries to push down aggregate functions to join paths.
func (a *aggregationOptimizer) aggPushDown(p LogicalPlan) LogicalPlan {
if agg, ok := p.(*LogicalAggregation); ok {
proj := a.tryToEliminateAggregation(agg)
if proj != nil {
p = proj
} else {
child := agg.children[0]
if join, ok1 := child.(*LogicalJoin); ok1 && a.checkValidJoin(join) {
if valid, leftAggFuncs, rightAggFuncs, leftGbyCols, rightGbyCols := a.splitAggFuncsAndGbyCols(agg, join); valid {
var lChild, rChild LogicalPlan
// If there exist count or sum functions in left join path, we can't push any
// aggregate function into right join path.
rightInvalid := a.checkAnyCountAndSum(leftAggFuncs)
leftInvalid := a.checkAnyCountAndSum(rightAggFuncs)
if rightInvalid {
rChild = join.children[1]
} else {
rChild = a.tryToPushDownAgg(rightAggFuncs, rightGbyCols, join, 1)
}
if leftInvalid {
lChild = join.children[0]
} else {
lChild = a.tryToPushDownAgg(leftAggFuncs, leftGbyCols, join, 0)
}
join.SetChildren(lChild, rChild)
join.SetSchema(expression.MergeSchema(lChild.Schema(), rChild.Schema()))
join.buildKeyInfo()
proj := a.tryToEliminateAggregation(agg)
if proj != nil {
p = proj
}
}
} else if proj, ok1 := child.(*LogicalProjection); ok1 {
// TODO: This optimization is not always reasonable. We have not supported pushing projection to kv layer yet,
// so we must do this optimization.
for i, gbyItem := range agg.GroupByItems {
agg.GroupByItems[i] = expression.ColumnSubstitute(gbyItem, proj.schema, proj.Exprs)
}
agg.collectGroupByColumns()
for _, aggFunc := range agg.AggFuncs {
newArgs := make([]expression.Expression, 0, len(aggFunc.Args))
for _, arg := range aggFunc.Args {
newArgs = append(newArgs, expression.ColumnSubstitute(arg, proj.schema, proj.Exprs))
}
aggFunc.Args = newArgs
}
projChild := proj.children[0]
agg.SetChildren(projChild)
} else if union, ok1 := child.(*LogicalUnionAll); ok1 {
var gbyCols []*expression.Column
gbyCols = expression.ExtractColumnsFromExpressions(gbyCols, agg.GroupByItems, nil)
pushedAgg := a.makeNewAgg(agg.ctx, agg.AggFuncs, gbyCols)
newChildren := make([]LogicalPlan, 0, len(union.children))
for _, child := range union.children {
newChild := a.pushAggCrossUnion(pushedAgg, union.Schema(), child)
newChildren = append(newChildren, newChild)
}
union.SetChildren(newChildren...)
}
}
}
newChildren := make([]LogicalPlan, 0, len(p.Children()))
for _, child := range p.Children() {
newChild := a.aggPushDown(child)
newChildren = append(newChildren, newChild)
}
p.SetChildren(newChildren...)
return p
}
// tryToEliminateAggregation will eliminate aggregation grouped by unique key.
// e.g. select min(b) from t group by a. If a is a unique key, then this sql is equal to `select b from t group by a`.
// For count(expr), sum(expr), avg(expr), count(distinct expr, [expr...]) we may need to rewrite the expr. Details are shown below.
// If we can eliminate agg successful, we return a projection. Else we return a nil pointer.
func (a *aggregationOptimizer) tryToEliminateAggregation(agg *LogicalAggregation) *LogicalProjection {
schemaByGroupby := expression.NewSchema(agg.groupByCols...)
coveredByUniqueKey := false
for _, key := range agg.children[0].Schema().Keys {
if schemaByGroupby.ColumnsIndices(key) != nil {
coveredByUniqueKey = true
break
}
}
if coveredByUniqueKey {
// GroupByCols has unique key, so this aggregation can be removed.
proj := a.convertAggToProj(agg)
proj.SetChildren(agg.children[0])
return proj
}
return nil
}
func (a *aggregationOptimizer) convertAggToProj(agg *LogicalAggregation) *LogicalProjection {
proj := LogicalProjection{
Exprs: make([]expression.Expression, 0, len(agg.AggFuncs)),
}.init(agg.ctx)
for _, fun := range agg.AggFuncs {
expr := a.rewriteExpr(agg.ctx, fun)
proj.Exprs = append(proj.Exprs, expr)
}
proj.SetSchema(agg.schema.Clone())
return proj
}
func (a *aggregationOptimizer) rewriteCount(ctx sessionctx.Context, exprs []expression.Expression) expression.Expression {
// If is count(expr), we will change it to if(isnull(expr), 0, 1).
// If is count(distinct x, y, z) we will change it to if(isnull(x) or isnull(y) or isnull(z), 0, 1).
isNullExprs := make([]expression.Expression, 0, len(exprs))
for _, expr := range exprs {
isNullExpr := expression.NewFunctionInternal(ctx, ast.IsNull, types.NewFieldType(mysql.TypeTiny), expr)
isNullExprs = append(isNullExprs, isNullExpr)
}
innerExpr := expression.ComposeDNFCondition(ctx, isNullExprs...)
newExpr := expression.NewFunctionInternal(ctx, ast.If, types.NewFieldType(mysql.TypeLonglong), innerExpr, expression.Zero, expression.One)
return newExpr
}
// See https://dev.mysql.com/doc/refman/5.7/en/group-by-functions.html
// The SUM() and AVG() functions return a DECIMAL value for exact-value arguments (integer or DECIMAL),
// and a DOUBLE value for approximate-value arguments (FLOAT or DOUBLE).
func (a *aggregationOptimizer) rewriteSumOrAvg(ctx sessionctx.Context, exprs []expression.Expression) expression.Expression {
// FIXME: Consider the case that avg is final mode.
expr := exprs[0]
switch expr.GetType().Tp {
// Integer type should be cast to decimal.
case mysql.TypeTiny, mysql.TypeShort, mysql.TypeInt24, mysql.TypeLong, mysql.TypeLonglong:
return expression.BuildCastFunction(ctx, expr, types.NewFieldType(mysql.TypeNewDecimal))
// Double and Decimal doesn't need to be cast.
case mysql.TypeDouble, mysql.TypeNewDecimal:
return expr
// Float should be cast to double. And other non-numeric type should be cast to double too.
default:
return expression.BuildCastFunction(ctx, expr, types.NewFieldType(mysql.TypeDouble))
}
}
// rewriteExpr will rewrite the aggregate function to expression doesn't contain aggregate function.
func (a *aggregationOptimizer) rewriteExpr(ctx sessionctx.Context, aggFunc *aggregation.AggFuncDesc) expression.Expression {
switch aggFunc.Name {
case ast.AggFuncCount:
if aggFunc.Mode == aggregation.FinalMode {
return a.rewriteSumOrAvg(ctx, aggFunc.Args)
}
return a.rewriteCount(ctx, aggFunc.Args)
case ast.AggFuncSum, ast.AggFuncAvg:
return a.rewriteSumOrAvg(ctx, aggFunc.Args)
default:
// Default we do nothing about expr.
return aggFunc.Args[0]
}
}