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executor: put SortExec and TopNExec into different files (#48569)
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ref #47733
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@xzhangxian1008
xzhangxian1008 authored Nov 14, 2023
1 parent 032c8e5 commit 361bdab
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Showing 3 changed files with 250 additions and 223 deletions.
5 changes: 4 additions & 1 deletion pkg/executor/sortexec/BUILD.bazel
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Original file line number Diff line number Diff line change
Expand Up @@ -2,7 +2,10 @@ load("@io_bazel_rules_go//go:def.bzl", "go_library", "go_test")

go_library(
name = "sortexec",
srcs = ["sort.go"],
srcs = [
"sort.go",
"topn.go",
],
importpath = "github.com/pingcap/tidb/pkg/executor/sortexec",
visibility = ["//visibility:public"],
deps = [
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222 changes: 0 additions & 222 deletions pkg/executor/sortexec/sort.go
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Original file line number Diff line number Diff line change
Expand Up @@ -18,12 +18,10 @@ import (
"container/heap"
"context"
"errors"
"slices"

"github.com/pingcap/failpoint"
"github.com/pingcap/tidb/pkg/executor/internal/exec"
"github.com/pingcap/tidb/pkg/expression"
plannercore "github.com/pingcap/tidb/pkg/planner/core"
"github.com/pingcap/tidb/pkg/planner/util"
"github.com/pingcap/tidb/pkg/sessionctx/variable"
"github.com/pingcap/tidb/pkg/util/chunk"
Expand Down Expand Up @@ -328,223 +326,3 @@ func (h *multiWayMerge) Pop() interface{} {
func (h *multiWayMerge) Swap(i, j int) {
h.elements[i], h.elements[j] = h.elements[j], h.elements[i]
}

// TopNExec implements a Top-N algorithm and it is built from a SELECT statement with ORDER BY and LIMIT.
// Instead of sorting all the rows fetched from the table, it keeps the Top-N elements only in a heap to reduce memory usage.
type TopNExec struct {
SortExec
Limit *plannercore.PhysicalLimit
totalLimit uint64

// rowChunks is the chunks to store row values.
rowChunks *chunk.List
// rowPointer store the chunk index and row index for each row.
rowPtrs []chunk.RowPtr

chkHeap *topNChunkHeap
}

// topNChunkHeap implements heap.Interface.
type topNChunkHeap struct {
*TopNExec
}

// Less implement heap.Interface, but since we mantains a max heap,
// this function returns true if row i is greater than row j.
func (h *topNChunkHeap) Less(i, j int) bool {
rowI := h.rowChunks.GetRow(h.rowPtrs[i])
rowJ := h.rowChunks.GetRow(h.rowPtrs[j])
return h.greaterRow(rowI, rowJ)
}

func (h *topNChunkHeap) greaterRow(rowI, rowJ chunk.Row) bool {
for i, colIdx := range h.keyColumns {
cmpFunc := h.keyCmpFuncs[i]
cmp := cmpFunc(rowI, colIdx, rowJ, colIdx)
if h.ByItems[i].Desc {
cmp = -cmp
}
if cmp > 0 {
return true
} else if cmp < 0 {
return false
}
}
return false
}

func (h *topNChunkHeap) Len() int {
return len(h.rowPtrs)
}

func (*topNChunkHeap) Push(interface{}) {
// Should never be called.
}

func (h *topNChunkHeap) Pop() interface{} {
h.rowPtrs = h.rowPtrs[:len(h.rowPtrs)-1]
// We don't need the popped value, return nil to avoid memory allocation.
return nil
}

func (h *topNChunkHeap) Swap(i, j int) {
h.rowPtrs[i], h.rowPtrs[j] = h.rowPtrs[j], h.rowPtrs[i]
}

// keyColumnsLess is the less function for key columns.
func (e *TopNExec) keyColumnsLess(i, j chunk.RowPtr) bool {
rowI := e.rowChunks.GetRow(i)
rowJ := e.rowChunks.GetRow(j)
return e.lessRow(rowI, rowJ)
}

func (e *TopNExec) keyColumnsCompare(i, j chunk.RowPtr) int {
rowI := e.rowChunks.GetRow(i)
rowJ := e.rowChunks.GetRow(j)
return e.compressRow(rowI, rowJ)
}

func (e *TopNExec) initPointers() {
e.rowPtrs = make([]chunk.RowPtr, 0, e.rowChunks.Len())
e.memTracker.Consume(int64(8 * e.rowChunks.Len()))
for chkIdx := 0; chkIdx < e.rowChunks.NumChunks(); chkIdx++ {
rowChk := e.rowChunks.GetChunk(chkIdx)
for rowIdx := 0; rowIdx < rowChk.NumRows(); rowIdx++ {
e.rowPtrs = append(e.rowPtrs, chunk.RowPtr{ChkIdx: uint32(chkIdx), RowIdx: uint32(rowIdx)})
}
}
}

// Open implements the Executor Open interface.
func (e *TopNExec) Open(ctx context.Context) error {
e.memTracker = memory.NewTracker(e.ID(), -1)
e.memTracker.AttachTo(e.Ctx().GetSessionVars().StmtCtx.MemTracker)

e.fetched = false
e.Idx = 0

return exec.Open(ctx, e.Children(0))
}

// Next implements the Executor Next interface.
func (e *TopNExec) Next(ctx context.Context, req *chunk.Chunk) error {
req.Reset()
if !e.fetched {
e.totalLimit = e.Limit.Offset + e.Limit.Count
e.Idx = int(e.Limit.Offset)
err := e.loadChunksUntilTotalLimit(ctx)
if err != nil {
return err
}
err = e.executeTopN(ctx)
if err != nil {
return err
}
e.fetched = true
}
if e.Idx >= len(e.rowPtrs) {
return nil
}
if !req.IsFull() {
numToAppend := min(len(e.rowPtrs)-e.Idx, req.RequiredRows()-req.NumRows())
rows := make([]chunk.Row, numToAppend)
for index := 0; index < numToAppend; index++ {
rows[index] = e.rowChunks.GetRow(e.rowPtrs[e.Idx])
e.Idx++
}
req.AppendRows(rows)
}
return nil
}

func (e *TopNExec) loadChunksUntilTotalLimit(ctx context.Context) error {
e.chkHeap = &topNChunkHeap{e}
e.rowChunks = chunk.NewList(exec.RetTypes(e), e.InitCap(), e.MaxChunkSize())
e.rowChunks.GetMemTracker().AttachTo(e.memTracker)
e.rowChunks.GetMemTracker().SetLabel(memory.LabelForRowChunks)
for uint64(e.rowChunks.Len()) < e.totalLimit {
srcChk := exec.TryNewCacheChunk(e.Children(0))
// adjust required rows by total limit
srcChk.SetRequiredRows(int(e.totalLimit-uint64(e.rowChunks.Len())), e.MaxChunkSize())
err := exec.Next(ctx, e.Children(0), srcChk)
if err != nil {
return err
}
if srcChk.NumRows() == 0 {
break
}
e.rowChunks.Add(srcChk)
}
e.initPointers()
e.initCompareFuncs()
e.buildKeyColumns()
return nil
}

const topNCompactionFactor = 4

func (e *TopNExec) executeTopN(ctx context.Context) error {
heap.Init(e.chkHeap)
for uint64(len(e.rowPtrs)) > e.totalLimit {
// The number of rows we loaded may exceeds total limit, remove greatest rows by Pop.
heap.Pop(e.chkHeap)
}
childRowChk := exec.TryNewCacheChunk(e.Children(0))
for {
err := exec.Next(ctx, e.Children(0), childRowChk)
if err != nil {
return err
}
if childRowChk.NumRows() == 0 {
break
}
err = e.processChildChk(childRowChk)
if err != nil {
return err
}
if e.rowChunks.Len() > len(e.rowPtrs)*topNCompactionFactor {
err = e.doCompaction()
if err != nil {
return err
}
}
}
slices.SortFunc(e.rowPtrs, e.keyColumnsCompare)
return nil
}

func (e *TopNExec) processChildChk(childRowChk *chunk.Chunk) error {
for i := 0; i < childRowChk.NumRows(); i++ {
heapMaxPtr := e.rowPtrs[0]
var heapMax, next chunk.Row
heapMax = e.rowChunks.GetRow(heapMaxPtr)
next = childRowChk.GetRow(i)
if e.chkHeap.greaterRow(heapMax, next) {
// Evict heap max, keep the next row.
e.rowPtrs[0] = e.rowChunks.AppendRow(childRowChk.GetRow(i))
heap.Fix(e.chkHeap, 0)
}
}
return nil
}

// doCompaction rebuild the chunks and row pointers to release memory.
// If we don't do compaction, in a extreme case like the child data is already ascending sorted
// but we want descending top N, then we will keep all data in memory.
// But if data is distributed randomly, this function will be called log(n) times.
func (e *TopNExec) doCompaction() error {
newRowChunks := chunk.NewList(exec.RetTypes(e), e.InitCap(), e.MaxChunkSize())
newRowPtrs := make([]chunk.RowPtr, 0, e.rowChunks.Len())
for _, rowPtr := range e.rowPtrs {
newRowPtr := newRowChunks.AppendRow(e.rowChunks.GetRow(rowPtr))
newRowPtrs = append(newRowPtrs, newRowPtr)
}
newRowChunks.GetMemTracker().SetLabel(memory.LabelForRowChunks)
e.memTracker.ReplaceChild(e.rowChunks.GetMemTracker(), newRowChunks.GetMemTracker())
e.rowChunks = newRowChunks

e.memTracker.Consume(int64(-8 * len(e.rowPtrs)))
e.memTracker.Consume(int64(8 * len(newRowPtrs)))
e.rowPtrs = newRowPtrs
return nil
}
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