tidb rule_join_reorder_dp 源码
tidb rule_join_reorder_dp 代码
文件路径：/planner/core/rule_join_reorder_dp.go
// Copyright 2018 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 (
"math/bits"
"github.com/pingcap/tidb/expression"
"github.com/pingcap/tidb/parser/ast"
)
type joinReorderDPSolver struct {
*baseSingleGroupJoinOrderSolver
newJoin func(lChild, rChild LogicalPlan, eqConds []*expression.ScalarFunction, otherConds, leftConds, rightConds []expression.Expression, joinType JoinType) LogicalPlan
}
type joinGroupEqEdge struct {
nodeIDs []int
edge *expression.ScalarFunction
}
type joinGroupNonEqEdge struct {
nodeIDs []int
nodeIDMask uint
expr expression.Expression
}
func (s *joinReorderDPSolver) solve(joinGroup []LogicalPlan, tracer *joinReorderTrace) (LogicalPlan, error) {
eqConds := expression.ScalarFuncs2Exprs(s.eqEdges)
for _, node := range joinGroup {
_, err := node.recursiveDeriveStats(nil)
if err != nil {
return nil, err
}
cost := s.baseNodeCumCost(node)
s.curJoinGroup = append(s.curJoinGroup, &jrNode{
p: node,
cumCost: cost,
})
tracer.appendLogicalJoinCost(node, cost)
}
adjacents := make([][]int, len(s.curJoinGroup))
totalEqEdges := make([]joinGroupEqEdge, 0, len(eqConds))
addEqEdge := func(node1, node2 int, edgeContent *expression.ScalarFunction) {
totalEqEdges = append(totalEqEdges, joinGroupEqEdge{
nodeIDs: []int{node1, node2},
edge: edgeContent,
})
adjacents[node1] = append(adjacents[node1], node2)
adjacents[node2] = append(adjacents[node2], node1)
}
// Build Graph for join group
for _, cond := range eqConds {
sf := cond.(*expression.ScalarFunction)
lCol := sf.GetArgs()[0].(*expression.Column)
rCol := sf.GetArgs()[1].(*expression.Column)
lIdx, err := findNodeIndexInGroup(joinGroup, lCol)
if err != nil {
return nil, err
}
rIdx, err := findNodeIndexInGroup(joinGroup, rCol)
if err != nil {
return nil, err
}
addEqEdge(lIdx, rIdx, sf)
}
totalNonEqEdges := make([]joinGroupNonEqEdge, 0, len(s.otherConds))
for _, cond := range s.otherConds {
cols := expression.ExtractColumns(cond)
mask := uint(0)
ids := make([]int, 0, len(cols))
for _, col := range cols {
idx, err := findNodeIndexInGroup(joinGroup, col)
if err != nil {
return nil, err
}
ids = append(ids, idx)
mask |= 1 << uint(idx)
}
totalNonEqEdges = append(totalNonEqEdges, joinGroupNonEqEdge{
nodeIDs: ids,
nodeIDMask: mask,
expr: cond,
})
}
visited := make([]bool, len(joinGroup))
nodeID2VisitID := make([]int, len(joinGroup))
var joins []LogicalPlan
// BFS the tree.
for i := 0; i < len(joinGroup); i++ {
if visited[i] {
continue
}
visitID2NodeID := s.bfsGraph(i, visited, adjacents, nodeID2VisitID)
nodeIDMask := uint(0)
for _, nodeID := range visitID2NodeID {
nodeIDMask |= 1 << uint(nodeID)
}
var subNonEqEdges []joinGroupNonEqEdge
for i := len(totalNonEqEdges) - 1; i >= 0; i-- {
// If this edge is not the subset of the current sub graph.
if totalNonEqEdges[i].nodeIDMask&nodeIDMask != totalNonEqEdges[i].nodeIDMask {
continue
}
newMask := uint(0)
for _, nodeID := range totalNonEqEdges[i].nodeIDs {
newMask |= 1 << uint(nodeID2VisitID[nodeID])
}
totalNonEqEdges[i].nodeIDMask = newMask
subNonEqEdges = append(subNonEqEdges, totalNonEqEdges[i])
totalNonEqEdges = append(totalNonEqEdges[:i], totalNonEqEdges[i+1:]...)
}
// Do DP on each sub graph.
join, err := s.dpGraph(visitID2NodeID, nodeID2VisitID, joinGroup, totalEqEdges, subNonEqEdges, tracer)
if err != nil {
return nil, err
}
joins = append(joins, join)
}
remainedOtherConds := make([]expression.Expression, 0, len(totalNonEqEdges))
for _, edge := range totalNonEqEdges {
remainedOtherConds = append(remainedOtherConds, edge.expr)
}
// Build bushy tree for cartesian joins.
return s.makeBushyJoin(joins, remainedOtherConds), nil
}
// bfsGraph bfs a sub graph starting at startPos. And relabel its label for future use.
func (s *joinReorderDPSolver) bfsGraph(startNode int, visited []bool, adjacents [][]int, nodeID2VisitID []int) []int {
queue := []int{startNode}
visited[startNode] = true
var visitID2NodeID []int
for len(queue) > 0 {
curNodeID := queue[0]
queue = queue[1:]
nodeID2VisitID[curNodeID] = len(visitID2NodeID)
visitID2NodeID = append(visitID2NodeID, curNodeID)
for _, adjNodeID := range adjacents[curNodeID] {
if visited[adjNodeID] {
continue
}
queue = append(queue, adjNodeID)
visited[adjNodeID] = true
}
}
return visitID2NodeID
}
// dpGraph is the core part of this algorithm.
// It implements the traditional join reorder algorithm: DP by subset using the following formula:
//
// bestPlan[S:set of node] = the best one among Join(bestPlan[S1:subset of S], bestPlan[S2: S/S1])
func (s *joinReorderDPSolver) dpGraph(visitID2NodeID, nodeID2VisitID []int, _ []LogicalPlan,
totalEqEdges []joinGroupEqEdge, totalNonEqEdges []joinGroupNonEqEdge, tracer *joinReorderTrace) (LogicalPlan, error) {
nodeCnt := uint(len(visitID2NodeID))
bestPlan := make([]*jrNode, 1<<nodeCnt)
// bestPlan[s] is nil can be treated as bestCost[s] = +inf.
for i := uint(0); i < nodeCnt; i++ {
bestPlan[1<<i] = s.curJoinGroup[visitID2NodeID[i]]
}
// Enumerate the nodeBitmap from small to big, make sure that S1 must be enumerated before S2 if S1 belongs to S2.
for nodeBitmap := uint(1); nodeBitmap < (1 << nodeCnt); nodeBitmap++ {
if bits.OnesCount(nodeBitmap) == 1 {
continue
}
// This loop can iterate all its subset.
for sub := (nodeBitmap - 1) & nodeBitmap; sub > 0; sub = (sub - 1) & nodeBitmap {
remain := nodeBitmap ^ sub
if sub > remain {
continue
}
// If this subset is not connected skip it.
if bestPlan[sub] == nil || bestPlan[remain] == nil {
continue
}
// Get the edge connecting the two parts.
usedEdges, otherConds := s.nodesAreConnected(sub, remain, nodeID2VisitID, totalEqEdges, totalNonEqEdges)
// Here we only check equal condition currently.
if len(usedEdges) == 0 {
continue
}
join, err := s.newJoinWithEdge(bestPlan[sub].p, bestPlan[remain].p, usedEdges, otherConds)
if err != nil {
return nil, err
}
curCost := s.calcJoinCumCost(join, bestPlan[sub], bestPlan[remain])
tracer.appendLogicalJoinCost(join, curCost)
if bestPlan[nodeBitmap] == nil {
bestPlan[nodeBitmap] = &jrNode{
p: join,
cumCost: curCost,
}
} else if bestPlan[nodeBitmap].cumCost > curCost {
bestPlan[nodeBitmap].p = join
bestPlan[nodeBitmap].cumCost = curCost
}
}
}
return bestPlan[(1<<nodeCnt)-1].p, nil
}
func (s *joinReorderDPSolver) nodesAreConnected(leftMask, rightMask uint, oldPos2NewPos []int,
totalEqEdges []joinGroupEqEdge, totalNonEqEdges []joinGroupNonEqEdge) ([]joinGroupEqEdge, []expression.Expression) {
//nolint: prealloc
var usedEqEdges []joinGroupEqEdge
//nolint: prealloc
var otherConds []expression.Expression
for _, edge := range totalEqEdges {
lIdx := uint(oldPos2NewPos[edge.nodeIDs[0]])
rIdx := uint(oldPos2NewPos[edge.nodeIDs[1]])
if ((leftMask&(1<<lIdx)) > 0 && (rightMask&(1<<rIdx)) > 0) || ((leftMask&(1<<rIdx)) > 0 && (rightMask&(1<<lIdx)) > 0) {
usedEqEdges = append(usedEqEdges, edge)
}
}
for _, edge := range totalNonEqEdges {
// If the result is false, means that the current group hasn't covered the columns involved in the expression.
if edge.nodeIDMask&(leftMask|rightMask) != edge.nodeIDMask {
continue
}
// Check whether this expression is only built from one side of the join.
if edge.nodeIDMask&leftMask == 0 || edge.nodeIDMask&rightMask == 0 {
continue
}
otherConds = append(otherConds, edge.expr)
}
return usedEqEdges, otherConds
}
func (s *joinReorderDPSolver) newJoinWithEdge(leftPlan, rightPlan LogicalPlan, edges []joinGroupEqEdge, otherConds []expression.Expression) (LogicalPlan, error) {
var eqConds []*expression.ScalarFunction
for _, edge := range edges {
lCol := edge.edge.GetArgs()[0].(*expression.Column)
rCol := edge.edge.GetArgs()[1].(*expression.Column)
if leftPlan.Schema().Contains(lCol) {
eqConds = append(eqConds, edge.edge)
} else {
newSf := expression.NewFunctionInternal(s.ctx, ast.EQ, edge.edge.GetType(), rCol, lCol).(*expression.ScalarFunction)
eqConds = append(eqConds, newSf)
}
}
join := s.newJoin(leftPlan, rightPlan, eqConds, otherConds, nil, nil, InnerJoin)
_, err := join.recursiveDeriveStats(nil)
return join, err
}
// Make cartesian join as bushy tree.
func (s *joinReorderDPSolver) makeBushyJoin(cartesianJoinGroup []LogicalPlan, otherConds []expression.Expression) LogicalPlan {
for len(cartesianJoinGroup) > 1 {
resultJoinGroup := make([]LogicalPlan, 0, len(cartesianJoinGroup))
for i := 0; i < len(cartesianJoinGroup); i += 2 {
if i+1 == len(cartesianJoinGroup) {
resultJoinGroup = append(resultJoinGroup, cartesianJoinGroup[i])
break
}
// TODO:Since the other condition may involve more than two tables, e.g. t1.a = t2.b+t3.c.
// So We'll need a extra stage to deal with it.
// Currently, we just add it when building cartesianJoinGroup.
mergedSchema := expression.MergeSchema(cartesianJoinGroup[i].Schema(), cartesianJoinGroup[i+1].Schema())
var usedOtherConds []expression.Expression
otherConds, usedOtherConds = expression.FilterOutInPlace(otherConds, func(expr expression.Expression) bool {
return expression.ExprFromSchema(expr, mergedSchema)
})
resultJoinGroup = append(resultJoinGroup, s.newJoin(cartesianJoinGroup[i], cartesianJoinGroup[i+1], nil, usedOtherConds, nil, nil, InnerJoin))
}
cartesianJoinGroup = resultJoinGroup
}
return cartesianJoinGroup[0]
}
func findNodeIndexInGroup(group []LogicalPlan, col *expression.Column) (int, error) {
for i, plan := range group {
if plan.Schema().Contains(col) {
return i, nil
}
}
return -1, ErrUnknownColumn.GenWithStackByArgs(col, "JOIN REORDER RULE")
}
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