tidb aggregate 源码
tidb aggregate 代码
文件路径：/executor/aggregate.go
// 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,
// 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 executor
import (
"bytes"
"context"
"fmt"
"sync"
"sync/atomic"
"time"
"github.com/pingcap/errors"
"github.com/pingcap/failpoint"
"github.com/pingcap/tidb/executor/aggfuncs"
"github.com/pingcap/tidb/expression"
"github.com/pingcap/tidb/parser/mysql"
"github.com/pingcap/tidb/parser/terror"
"github.com/pingcap/tidb/sessionctx"
"github.com/pingcap/tidb/sessionctx/stmtctx"
"github.com/pingcap/tidb/sessionctx/variable"
"github.com/pingcap/tidb/types"
"github.com/pingcap/tidb/util/channel"
"github.com/pingcap/tidb/util/chunk"
"github.com/pingcap/tidb/util/codec"
"github.com/pingcap/tidb/util/disk"
"github.com/pingcap/tidb/util/execdetails"
"github.com/pingcap/tidb/util/hack"
"github.com/pingcap/tidb/util/logutil"
"github.com/pingcap/tidb/util/mathutil"
"github.com/pingcap/tidb/util/memory"
"github.com/pingcap/tidb/util/set"
"github.com/twmb/murmur3"
"go.uber.org/zap"
"golang.org/x/exp/slices"
)
type aggPartialResultMapper map[string][]aggfuncs.PartialResult
// baseHashAggWorker stores the common attributes of HashAggFinalWorker and HashAggPartialWorker.
// nolint:structcheck
type baseHashAggWorker struct {
ctx sessionctx.Context
finishCh <-chan struct{}
aggFuncs []aggfuncs.AggFunc
maxChunkSize int
stats *AggWorkerStat
memTracker *memory.Tracker
BInMap int // indicate there are 2^BInMap buckets in Golang Map.
}
func newBaseHashAggWorker(ctx sessionctx.Context, finishCh <-chan struct{}, aggFuncs []aggfuncs.AggFunc,
maxChunkSize int, memTrack *memory.Tracker) baseHashAggWorker {
baseWorker := baseHashAggWorker{
ctx: ctx,
finishCh: finishCh,
aggFuncs: aggFuncs,
maxChunkSize: maxChunkSize,
memTracker: memTrack,
BInMap: 0,
}
return baseWorker
}
// HashAggPartialWorker indicates the partial workers of parallel hash agg execution,
// the number of the worker can be set by `tidb_hashagg_partial_concurrency`.
type HashAggPartialWorker struct {
baseHashAggWorker
inputCh chan *chunk.Chunk
outputChs []chan *HashAggIntermData
globalOutputCh chan *AfFinalResult
giveBackCh chan<- *HashAggInput
partialResultsMap aggPartialResultMapper
groupByItems []expression.Expression
groupKey [][]byte
// chk stores the input data from child,
// and is reused by childExec and partial worker.
chk *chunk.Chunk
}
// HashAggFinalWorker indicates the final workers of parallel hash agg execution,
// the number of the worker can be set by `tidb_hashagg_final_concurrency`.
type HashAggFinalWorker struct {
baseHashAggWorker
rowBuffer []types.Datum
mutableRow chunk.MutRow
partialResultMap aggPartialResultMapper
groupSet set.StringSetWithMemoryUsage
inputCh chan *HashAggIntermData
outputCh chan *AfFinalResult
finalResultHolderCh chan *chunk.Chunk
groupKeys [][]byte
}
// AfFinalResult indicates aggregation functions final result.
type AfFinalResult struct {
chk *chunk.Chunk
err error
giveBackCh chan *chunk.Chunk
}
// HashAggExec deals with all the aggregate functions.
// It is built from the Aggregate Plan. When Next() is called, it reads all the data from Src
// and updates all the items in PartialAggFuncs.
// The parallel execution flow is as the following graph shows:
/*
+-------------+
| Main Thread |
+------+------+
^
|
+
+-+- +-+
| | ...... | | finalOutputCh
+++- +-+
^
|
+---------------+
| |
+--------------+ +--------------+
| final worker | ...... | final worker |
+------------+-+ +-+------------+
^ ^
| |
+-+ +-+ ...... +-+
| | | | | |
... ... ... partialOutputChs
| | | | | |
+++ +++ +++
^ ^ ^
+-+ | | |
| | +--------o----+ |
inputCh +-+ | +-----------------+---+
| | | |
... +---+------------+ +----+-----------+
| | | partial worker | ...... | partial worker |
+++ +--------------+-+ +-+--------------+
| ^ ^
| | |
+----v---------+ +++ +-+ +++
| data fetcher | +------> | | | | ...... | | partialInputChs
+--------------+ +-+ +-+ +-+
*/
type HashAggExec struct {
baseExecutor
sc *stmtctx.StatementContext
PartialAggFuncs []aggfuncs.AggFunc
FinalAggFuncs []aggfuncs.AggFunc
partialResultMap aggPartialResultMapper
bInMap int64 // indicate there are 2^bInMap buckets in partialResultMap
groupSet set.StringSetWithMemoryUsage
groupKeys []string
cursor4GroupKey int
GroupByItems []expression.Expression
groupKeyBuffer [][]byte
finishCh chan struct{}
finalOutputCh chan *AfFinalResult
partialOutputChs []chan *HashAggIntermData
inputCh chan *HashAggInput
partialInputChs []chan *chunk.Chunk
partialWorkers []HashAggPartialWorker
finalWorkers []HashAggFinalWorker
defaultVal *chunk.Chunk
childResult *chunk.Chunk
// isChildReturnEmpty indicates whether the child executor only returns an empty input.
isChildReturnEmpty bool
// After we support parallel execution for aggregation functions with distinct,
// we can remove this attribute.
isUnparallelExec bool
parallelExecInitialized bool
prepared bool
executed bool
memTracker *memory.Tracker // track memory usage.
diskTracker *disk.Tracker
stats *HashAggRuntimeStats
// listInDisk is the chunks to store row values for spilled data.
// The HashAggExec may be set to `spill mode` multiple times, and all spilled data will be appended to ListInDisk.
listInDisk *chunk.ListInDisk
// numOfSpilledChks indicates the number of all the spilled chunks.
numOfSpilledChks int
// offsetOfSpilledChks indicates the offset of the chunk be read from the disk.
// In each round of processing, we need to re-fetch all the chunks spilled in the last one.
offsetOfSpilledChks int
// inSpillMode indicates whether HashAgg is in `spill mode`.
// When HashAgg is in `spill mode`, the size of `partialResultMap` is no longer growing and all the data fetched
// from the child executor is spilled to the disk.
inSpillMode uint32
// tmpChkForSpill is the temp chunk for spilling.
tmpChkForSpill *chunk.Chunk
// spillAction save the Action for spilling.
spillAction *AggSpillDiskAction
// isChildDrained indicates whether the all data from child has been taken out.
isChildDrained bool
}
// HashAggInput indicates the input of hash agg exec.
type HashAggInput struct {
chk *chunk.Chunk
// giveBackCh is bound with specific partial worker,
// it's used to reuse the `chk`,
// and tell the data-fetcher which partial worker it should send data to.
giveBackCh chan<- *chunk.Chunk
}
// HashAggIntermData indicates the intermediate data of aggregation execution.
type HashAggIntermData struct {
groupKeys []string
cursor int
partialResultMap aggPartialResultMapper
}
// getPartialResultBatch fetches a batch of partial results from HashAggIntermData.
func (d *HashAggIntermData) getPartialResultBatch(_ *stmtctx.StatementContext, prs [][]aggfuncs.PartialResult, _ []aggfuncs.AggFunc, maxChunkSize int) (_ [][]aggfuncs.PartialResult, groupKeys []string, reachEnd bool) {
keyStart := d.cursor
for ; d.cursor < len(d.groupKeys) && len(prs) < maxChunkSize; d.cursor++ {
prs = append(prs, d.partialResultMap[d.groupKeys[d.cursor]])
}
if d.cursor == len(d.groupKeys) {
reachEnd = true
}
return prs, d.groupKeys[keyStart:d.cursor], reachEnd
}
// Close implements the Executor Close interface.
func (e *HashAggExec) Close() error {
if e.isUnparallelExec {
var firstErr error
e.childResult = nil
e.groupSet, _ = set.NewStringSetWithMemoryUsage()
e.partialResultMap = nil
if e.memTracker != nil {
e.memTracker.ReplaceBytesUsed(0)
}
if e.listInDisk != nil {
firstErr = e.listInDisk.Close()
}
e.spillAction, e.tmpChkForSpill = nil, nil
if err := e.baseExecutor.Close(); firstErr == nil {
firstErr = err
}
return firstErr
}
if e.parallelExecInitialized {
// `Close` may be called after `Open` without calling `Next` in test.
if !e.prepared {
close(e.inputCh)
for _, ch := range e.partialOutputChs {
close(ch)
}
for _, ch := range e.partialInputChs {
close(ch)
}
close(e.finalOutputCh)
}
close(e.finishCh)
for _, ch := range e.partialOutputChs {
channel.Clear(ch)
}
for _, ch := range e.partialInputChs {
channel.Clear(ch)
}
channel.Clear(e.finalOutputCh)
e.executed = false
if e.memTracker != nil {
e.memTracker.ReplaceBytesUsed(0)
}
}
return e.baseExecutor.Close()
}
// Open implements the Executor Open interface.
func (e *HashAggExec) Open(ctx context.Context) error {
failpoint.Inject("mockHashAggExecBaseExecutorOpenReturnedError", func(val failpoint.Value) {
if val, _ := val.(bool); val {
failpoint.Return(errors.New("mock HashAggExec.baseExecutor.Open returned error"))
}
})
if err := e.baseExecutor.Open(ctx); err != nil {
return err
}
e.prepared = false
e.memTracker = memory.NewTracker(e.id, -1)
if e.ctx.GetSessionVars().TrackAggregateMemoryUsage {
e.memTracker.AttachTo(e.ctx.GetSessionVars().StmtCtx.MemTracker)
}
if e.isUnparallelExec {
e.initForUnparallelExec()
return nil
}
e.initForParallelExec(e.ctx)
return nil
}
func (e *HashAggExec) initForUnparallelExec() {
var setSize int64
e.groupSet, setSize = set.NewStringSetWithMemoryUsage()
e.partialResultMap = make(aggPartialResultMapper)
e.bInMap = 0
failpoint.Inject("ConsumeRandomPanic", nil)
e.memTracker.Consume(hack.DefBucketMemoryUsageForMapStrToSlice*(1<<e.bInMap) + setSize)
e.groupKeyBuffer = make([][]byte, 0, 8)
e.childResult = newFirstChunk(e.children[0])
e.memTracker.Consume(e.childResult.MemoryUsage())
e.offsetOfSpilledChks, e.numOfSpilledChks = 0, 0
e.executed, e.isChildDrained = false, false
e.listInDisk = chunk.NewListInDisk(retTypes(e.children[0]))
e.tmpChkForSpill = newFirstChunk(e.children[0])
if e.ctx.GetSessionVars().TrackAggregateMemoryUsage && variable.EnableTmpStorageOnOOM.Load() {
e.diskTracker = disk.NewTracker(e.id, -1)
e.diskTracker.AttachTo(e.ctx.GetSessionVars().StmtCtx.DiskTracker)
e.listInDisk.GetDiskTracker().AttachTo(e.diskTracker)
e.ctx.GetSessionVars().StmtCtx.MemTracker.FallbackOldAndSetNewActionForSoftLimit(e.ActionSpill())
}
}
func closeBaseExecutor(b *baseExecutor) {
if r := recover(); r != nil {
// Release the resource, but throw the panic again and let the top level handle it.
terror.Log(b.Close())
logutil.BgLogger().Warn("panic in Open(), close base executor and throw exception again")
panic(r)
}
}
func (e *HashAggExec) initForParallelExec(_ sessionctx.Context) {
sessionVars := e.ctx.GetSessionVars()
finalConcurrency := sessionVars.HashAggFinalConcurrency()
partialConcurrency := sessionVars.HashAggPartialConcurrency()
e.isChildReturnEmpty = true
e.finalOutputCh = make(chan *AfFinalResult, finalConcurrency+partialConcurrency+1)
e.inputCh = make(chan *HashAggInput, partialConcurrency)
e.finishCh = make(chan struct{}, 1)
e.partialInputChs = make([]chan *chunk.Chunk, partialConcurrency)
for i := range e.partialInputChs {
e.partialInputChs[i] = make(chan *chunk.Chunk, 1)
}
e.partialOutputChs = make([]chan *HashAggIntermData, finalConcurrency)
for i := range e.partialOutputChs {
e.partialOutputChs[i] = make(chan *HashAggIntermData, partialConcurrency)
}
e.partialWorkers = make([]HashAggPartialWorker, partialConcurrency)
e.finalWorkers = make([]HashAggFinalWorker, finalConcurrency)
e.initRuntimeStats()
// Init partial workers.
for i := 0; i < partialConcurrency; i++ {
w := HashAggPartialWorker{
baseHashAggWorker: newBaseHashAggWorker(e.ctx, e.finishCh, e.PartialAggFuncs, e.maxChunkSize, e.memTracker),
inputCh: e.partialInputChs[i],
outputChs: e.partialOutputChs,
giveBackCh: e.inputCh,
globalOutputCh: e.finalOutputCh,
partialResultsMap: make(aggPartialResultMapper),
groupByItems: e.GroupByItems,
chk: newFirstChunk(e.children[0]),
groupKey: make([][]byte, 0, 8),
}
// There is a bucket in the empty partialResultsMap.
failpoint.Inject("ConsumeRandomPanic", nil)
e.memTracker.Consume(hack.DefBucketMemoryUsageForMapStrToSlice * (1 << w.BInMap))
if e.stats != nil {
w.stats = &AggWorkerStat{}
e.stats.PartialStats = append(e.stats.PartialStats, w.stats)
}
e.memTracker.Consume(w.chk.MemoryUsage())
e.partialWorkers[i] = w
input := &HashAggInput{
chk: newFirstChunk(e.children[0]),
giveBackCh: w.inputCh,
}
e.memTracker.Consume(input.chk.MemoryUsage())
e.inputCh <- input
}
// Init final workers.
for i := 0; i < finalConcurrency; i++ {
groupSet, setSize := set.NewStringSetWithMemoryUsage()
w := HashAggFinalWorker{
baseHashAggWorker: newBaseHashAggWorker(e.ctx, e.finishCh, e.FinalAggFuncs, e.maxChunkSize, e.memTracker),
partialResultMap: make(aggPartialResultMapper),
groupSet: groupSet,
inputCh: e.partialOutputChs[i],
outputCh: e.finalOutputCh,
finalResultHolderCh: make(chan *chunk.Chunk, 1),
rowBuffer: make([]types.Datum, 0, e.Schema().Len()),
mutableRow: chunk.MutRowFromTypes(retTypes(e)),
groupKeys: make([][]byte, 0, 8),
}
// There is a bucket in the empty partialResultsMap.
e.memTracker.Consume(hack.DefBucketMemoryUsageForMapStrToSlice*(1<<w.BInMap) + setSize)
groupSet.SetTracker(e.memTracker)
if e.stats != nil {
w.stats = &AggWorkerStat{}
e.stats.FinalStats = append(e.stats.FinalStats, w.stats)
}
e.finalWorkers[i] = w
e.finalWorkers[i].finalResultHolderCh <- newFirstChunk(e)
}
e.parallelExecInitialized = true
}
func (w *HashAggPartialWorker) getChildInput() bool {
select {
case <-w.finishCh:
return false
case chk, ok := <-w.inputCh:
if !ok {
return false
}
w.chk.SwapColumns(chk)
w.giveBackCh <- &HashAggInput{
chk: chk,
giveBackCh: w.inputCh,
}
}
return true
}
func recoveryHashAgg(output chan *AfFinalResult, r interface{}) {
err := errors.Errorf("%v", r)
output <- &AfFinalResult{err: errors.Errorf("%v", r)}
logutil.BgLogger().Error("parallel hash aggregation panicked", zap.Error(err), zap.Stack("stack"))
}
func (w *HashAggPartialWorker) run(ctx sessionctx.Context, waitGroup *sync.WaitGroup, finalConcurrency int) {
start := time.Now()
needShuffle, sc := false, ctx.GetSessionVars().StmtCtx
defer func() {
if r := recover(); r != nil {
recoveryHashAgg(w.globalOutputCh, r)
}
if needShuffle {
w.shuffleIntermData(sc, finalConcurrency)
}
w.memTracker.Consume(-w.chk.MemoryUsage())
if w.stats != nil {
w.stats.WorkerTime += int64(time.Since(start))
}
waitGroup.Done()
}()
for {
waitStart := time.Now()
ok := w.getChildInput()
if w.stats != nil {
w.stats.WaitTime += int64(time.Since(waitStart))
}
if !ok {
return
}
execStart := time.Now()
if err := w.updatePartialResult(ctx, sc, w.chk, len(w.partialResultsMap)); err != nil {
w.globalOutputCh <- &AfFinalResult{err: err}
return
}
if w.stats != nil {
w.stats.ExecTime += int64(time.Since(execStart))
w.stats.TaskNum++
}
// The intermData can be promised to be not empty if reaching here,
// so we set needShuffle to be true.
needShuffle = true
}
}
func getGroupKeyMemUsage(groupKey [][]byte) int64 {
mem := int64(0)
for _, key := range groupKey {
mem += int64(cap(key))
}
mem += aggfuncs.DefSliceSize * int64(cap(groupKey))
return mem
}
func (w *HashAggPartialWorker) updatePartialResult(ctx sessionctx.Context, sc *stmtctx.StatementContext, chk *chunk.Chunk, _ int) (err error) {
memSize := getGroupKeyMemUsage(w.groupKey)
w.groupKey, err = getGroupKey(w.ctx, chk, w.groupKey, w.groupByItems)
failpoint.Inject("ConsumeRandomPanic", nil)
w.memTracker.Consume(getGroupKeyMemUsage(w.groupKey) - memSize)
if err != nil {
return err
}
partialResults := w.getPartialResult(sc, w.groupKey, w.partialResultsMap)
numRows := chk.NumRows()
rows := make([]chunk.Row, 1)
allMemDelta := int64(0)
for i := 0; i < numRows; i++ {
for j, af := range w.aggFuncs {
rows[0] = chk.GetRow(i)
memDelta, err := af.UpdatePartialResult(ctx, rows, partialResults[i][j])
if err != nil {
return err
}
allMemDelta += memDelta
}
}
w.memTracker.Consume(allMemDelta)
return nil
}
// shuffleIntermData shuffles the intermediate data of partial workers to corresponded final workers.
// We only support parallel execution for single-machine, so process of encode and decode can be skipped.
func (w *HashAggPartialWorker) shuffleIntermData(_ *stmtctx.StatementContext, finalConcurrency int) {
groupKeysSlice := make([][]string, finalConcurrency)
for groupKey := range w.partialResultsMap {
finalWorkerIdx := int(murmur3.Sum32([]byte(groupKey))) % finalConcurrency
if groupKeysSlice[finalWorkerIdx] == nil {
groupKeysSlice[finalWorkerIdx] = make([]string, 0, len(w.partialResultsMap)/finalConcurrency)
}
groupKeysSlice[finalWorkerIdx] = append(groupKeysSlice[finalWorkerIdx], groupKey)
}
for i := range groupKeysSlice {
if groupKeysSlice[i] == nil {
continue
}
w.outputChs[i] <- &HashAggIntermData{
groupKeys: groupKeysSlice[i],
partialResultMap: w.partialResultsMap,
}
}
}
// getGroupKey evaluates the group items and args of aggregate functions.
func getGroupKey(ctx sessionctx.Context, input *chunk.Chunk, groupKey [][]byte, groupByItems []expression.Expression) ([][]byte, error) {
numRows := input.NumRows()
avlGroupKeyLen := mathutil.Min(len(groupKey), numRows)
for i := 0; i < avlGroupKeyLen; i++ {
groupKey[i] = groupKey[i][:0]
}
for i := avlGroupKeyLen; i < numRows; i++ {
groupKey = append(groupKey, make([]byte, 0, 10*len(groupByItems)))
}
for _, item := range groupByItems {
tp := item.GetType()
buf, err := expression.GetColumn(tp.EvalType(), numRows)
if err != nil {
return nil, err
}
// In strict sql mode like ‘STRICT_TRANS_TABLES’，can not insert an invalid enum value like 0.
// While in sql mode like '', can insert an invalid enum value like 0,
// then the enum value 0 will have the enum name '', which maybe conflict with user defined enum ''.
// Ref to issue #26885.
// This check is used to handle invalid enum name same with user defined enum name.
// Use enum value as groupKey instead of enum name.
if item.GetType().GetType() == mysql.TypeEnum {
newTp := *tp
newTp.AddFlag(mysql.EnumSetAsIntFlag)
tp = &newTp
}
if err := expression.EvalExpr(ctx, item, tp.EvalType(), input, buf); err != nil {
expression.PutColumn(buf)
return nil, err
}
// This check is used to avoid error during the execution of `EncodeDecimal`.
if item.GetType().GetType() == mysql.TypeNewDecimal {
newTp := *tp
newTp.SetFlen(0)
tp = &newTp
}
groupKey, err = codec.HashGroupKey(ctx.GetSessionVars().StmtCtx, input.NumRows(), buf, groupKey, tp)
if err != nil {
expression.PutColumn(buf)
return nil, err
}
expression.PutColumn(buf)
}
return groupKey, nil
}
func (w *baseHashAggWorker) getPartialResult(_ *stmtctx.StatementContext, groupKey [][]byte, mapper aggPartialResultMapper) [][]aggfuncs.PartialResult {
n := len(groupKey)
partialResults := make([][]aggfuncs.PartialResult, n)
allMemDelta := int64(0)
partialResultSize := w.getPartialResultSliceLenConsiderByteAlign()
for i := 0; i < n; i++ {
var ok bool
if partialResults[i], ok = mapper[string(groupKey[i])]; ok {
continue
}
partialResults[i] = make([]aggfuncs.PartialResult, partialResultSize)
for j, af := range w.aggFuncs {
partialResult, memDelta := af.AllocPartialResult()
partialResults[i][j] = partialResult
allMemDelta += memDelta // the memory usage of PartialResult
}
allMemDelta += int64(partialResultSize * 8)
// Map will expand when count > bucketNum * loadFactor. The memory usage will double.
if len(mapper)+1 > (1<<w.BInMap)*hack.LoadFactorNum/hack.LoadFactorDen {
w.memTracker.Consume(hack.DefBucketMemoryUsageForMapStrToSlice * (1 << w.BInMap))
w.BInMap++
}
mapper[string(groupKey[i])] = partialResults[i]
allMemDelta += int64(len(groupKey[i]))
}
failpoint.Inject("ConsumeRandomPanic", nil)
w.memTracker.Consume(allMemDelta)
return partialResults
}
func (w *baseHashAggWorker) getPartialResultSliceLenConsiderByteAlign() int {
length := len(w.aggFuncs)
if len(w.aggFuncs) == 1 {
return 1
}
return length + length&1
}
func (w *HashAggFinalWorker) getPartialInput() (input *HashAggIntermData, ok bool) {
select {
case <-w.finishCh:
return nil, false
case input, ok = <-w.inputCh:
if !ok {
return nil, false
}
}
return
}
func (w *HashAggFinalWorker) consumeIntermData(sctx sessionctx.Context) (err error) {
var (
input *HashAggIntermData
ok bool
intermDataBuffer [][]aggfuncs.PartialResult
groupKeys []string
sc = sctx.GetSessionVars().StmtCtx
)
for {
waitStart := time.Now()
input, ok = w.getPartialInput()
if w.stats != nil {
w.stats.WaitTime += int64(time.Since(waitStart))
}
if !ok {
return nil
}
execStart := time.Now()
if intermDataBuffer == nil {
intermDataBuffer = make([][]aggfuncs.PartialResult, 0, w.maxChunkSize)
}
// Consume input in batches, size of every batch is less than w.maxChunkSize.
for reachEnd := false; !reachEnd; {
intermDataBuffer, groupKeys, reachEnd = input.getPartialResultBatch(sc, intermDataBuffer[:0], w.aggFuncs, w.maxChunkSize)
groupKeysLen := len(groupKeys)
memSize := getGroupKeyMemUsage(w.groupKeys)
w.groupKeys = w.groupKeys[:0]
for i := 0; i < groupKeysLen; i++ {
w.groupKeys = append(w.groupKeys, []byte(groupKeys[i]))
}
failpoint.Inject("ConsumeRandomPanic", nil)
w.memTracker.Consume(getGroupKeyMemUsage(w.groupKeys) - memSize)
finalPartialResults := w.getPartialResult(sc, w.groupKeys, w.partialResultMap)
allMemDelta := int64(0)
for i, groupKey := range groupKeys {
if !w.groupSet.Exist(groupKey) {
allMemDelta += w.groupSet.Insert(groupKey)
}
prs := intermDataBuffer[i]
for j, af := range w.aggFuncs {
memDelta, err := af.MergePartialResult(sctx, prs[j], finalPartialResults[i][j])
if err != nil {
return err
}
allMemDelta += memDelta
}
}
w.memTracker.Consume(allMemDelta)
}
if w.stats != nil {
w.stats.ExecTime += int64(time.Since(execStart))
w.stats.TaskNum++
}
}
}
func (w *HashAggFinalWorker) loadFinalResult(sctx sessionctx.Context) {
waitStart := time.Now()
result, finished := w.receiveFinalResultHolder()
if w.stats != nil {
w.stats.WaitTime += int64(time.Since(waitStart))
}
if finished {
return
}
execStart := time.Now()
memSize := getGroupKeyMemUsage(w.groupKeys)
w.groupKeys = w.groupKeys[:0]
for groupKey := range w.groupSet.StringSet {
w.groupKeys = append(w.groupKeys, []byte(groupKey))
}
failpoint.Inject("ConsumeRandomPanic", nil)
w.memTracker.Consume(getGroupKeyMemUsage(w.groupKeys) - memSize)
partialResults := w.getPartialResult(sctx.GetSessionVars().StmtCtx, w.groupKeys, w.partialResultMap)
for i := 0; i < len(w.groupSet.StringSet); i++ {
for j, af := range w.aggFuncs {
if err := af.AppendFinalResult2Chunk(sctx, partialResults[i][j], result); err != nil {
logutil.BgLogger().Error("HashAggFinalWorker failed to append final result to Chunk", zap.Error(err))
}
}
if len(w.aggFuncs) == 0 {
result.SetNumVirtualRows(result.NumRows() + 1)
}
if result.IsFull() {
w.outputCh <- &AfFinalResult{chk: result, giveBackCh: w.finalResultHolderCh}
result, finished = w.receiveFinalResultHolder()
if finished {
return
}
}
}
w.outputCh <- &AfFinalResult{chk: result, giveBackCh: w.finalResultHolderCh}
if w.stats != nil {
w.stats.ExecTime += int64(time.Since(execStart))
}
}
func (w *HashAggFinalWorker) receiveFinalResultHolder() (*chunk.Chunk, bool) {
select {
case <-w.finishCh:
return nil, true
case result, ok := <-w.finalResultHolderCh:
return result, !ok
}
}
func (w *HashAggFinalWorker) run(ctx sessionctx.Context, waitGroup *sync.WaitGroup) {
start := time.Now()
defer func() {
if r := recover(); r != nil {
recoveryHashAgg(w.outputCh, r)
}
if w.stats != nil {
w.stats.WorkerTime += int64(time.Since(start))
}
waitGroup.Done()
}()
if err := w.consumeIntermData(ctx); err != nil {
w.outputCh <- &AfFinalResult{err: err}
}
w.loadFinalResult(ctx)
}
// Next implements the Executor Next interface.
func (e *HashAggExec) Next(ctx context.Context, req *chunk.Chunk) error {
req.Reset()
if e.isUnparallelExec {
return e.unparallelExec(ctx, req)
}
return e.parallelExec(ctx, req)
}
func (e *HashAggExec) fetchChildData(ctx context.Context, waitGroup *sync.WaitGroup) {
var (
input *HashAggInput
chk *chunk.Chunk
ok bool
err error
)
defer func() {
if r := recover(); r != nil {
recoveryHashAgg(e.finalOutputCh, r)
}
for i := range e.partialInputChs {
close(e.partialInputChs[i])
}
waitGroup.Done()
}()
for {
select {
case <-e.finishCh:
return
case input, ok = <-e.inputCh:
if !ok {
return
}
chk = input.chk
}
mSize := chk.MemoryUsage()
err = Next(ctx, e.children[0], chk)
if err != nil {
e.finalOutputCh <- &AfFinalResult{err: err}
e.memTracker.Consume(-mSize)
return
}
if chk.NumRows() == 0 {
e.memTracker.Consume(-mSize)
return
}
failpoint.Inject("ConsumeRandomPanic", nil)
e.memTracker.Consume(chk.MemoryUsage() - mSize)
input.giveBackCh <- chk
}
}
func (e *HashAggExec) waitPartialWorkerAndCloseOutputChs(waitGroup *sync.WaitGroup) {
waitGroup.Wait()
close(e.inputCh)
for input := range e.inputCh {
e.memTracker.Consume(-input.chk.MemoryUsage())
}
for _, ch := range e.partialOutputChs {
close(ch)
}
}
func (e *HashAggExec) waitAllWorkersAndCloseFinalOutputCh(waitGroups ...*sync.WaitGroup) {
for _, waitGroup := range waitGroups {
waitGroup.Wait()
}
close(e.finalOutputCh)
}
func (e *HashAggExec) prepare4ParallelExec(ctx context.Context) {
fetchChildWorkerWaitGroup := &sync.WaitGroup{}
fetchChildWorkerWaitGroup.Add(1)
go e.fetchChildData(ctx, fetchChildWorkerWaitGroup)
// We get the pointers here instead of when we are all finished and adding the time because:
// (1) If there is Apply in the plan tree, executors may be reused (Open()ed and Close()ed multiple times)
// (2) we don't wait all goroutines of HashAgg to exit in HashAgg.Close()
// So we can't write something like:
// atomic.AddInt64(&e.stats.PartialWallTime, int64(time.Since(partialStart)))
// Because the next execution of HashAgg may have started when this goroutine haven't exited and then there will be data race.
var partialWallTimePtr, finalWallTimePtr *int64
if e.stats != nil {
partialWallTimePtr = &e.stats.PartialWallTime
finalWallTimePtr = &e.stats.FinalWallTime
}
partialWorkerWaitGroup := &sync.WaitGroup{}
partialWorkerWaitGroup.Add(len(e.partialWorkers))
partialStart := time.Now()
for i := range e.partialWorkers {
go e.partialWorkers[i].run(e.ctx, partialWorkerWaitGroup, len(e.finalWorkers))
}
go func() {
e.waitPartialWorkerAndCloseOutputChs(partialWorkerWaitGroup)
if partialWallTimePtr != nil {
atomic.AddInt64(partialWallTimePtr, int64(time.Since(partialStart)))
}
}()
finalWorkerWaitGroup := &sync.WaitGroup{}
finalWorkerWaitGroup.Add(len(e.finalWorkers))
finalStart := time.Now()
for i := range e.finalWorkers {
go e.finalWorkers[i].run(e.ctx, finalWorkerWaitGroup)
}
go func() {
finalWorkerWaitGroup.Wait()
if finalWallTimePtr != nil {
atomic.AddInt64(finalWallTimePtr, int64(time.Since(finalStart)))
}
}()
// All workers may send error message to e.finalOutputCh when they panic.
// And e.finalOutputCh should be closed after all goroutines gone.
go e.waitAllWorkersAndCloseFinalOutputCh(fetchChildWorkerWaitGroup, partialWorkerWaitGroup, finalWorkerWaitGroup)
}
// HashAggExec employs one input reader, M partial workers and N final workers to execute parallelly.
// The parallel execution flow is:
// 1. input reader reads data from child executor and send them to partial workers.
// 2. partial worker receives the input data, updates the partial results, and shuffle the partial results to the final workers.
// 3. final worker receives partial results from all the partial workers, evaluates the final results and sends the final results to the main thread.
func (e *HashAggExec) parallelExec(ctx context.Context, chk *chunk.Chunk) error {
if !e.prepared {
e.prepare4ParallelExec(ctx)
e.prepared = true
}
failpoint.Inject("parallelHashAggError", func(val failpoint.Value) {
if val, _ := val.(bool); val {
failpoint.Return(errors.New("HashAggExec.parallelExec error"))
}
})
if e.executed {
return nil
}
for {
result, ok := <-e.finalOutputCh
if !ok {
e.executed = true
if e.isChildReturnEmpty && e.defaultVal != nil {
chk.Append(e.defaultVal, 0, 1)
}
return nil
}
if result.err != nil {
return result.err
}
chk.SwapColumns(result.chk)
result.chk.Reset()
result.giveBackCh <- result.chk
if chk.NumRows() > 0 {
e.isChildReturnEmpty = false
return nil
}
}
}
// unparallelExec executes hash aggregation algorithm in single thread.
func (e *HashAggExec) unparallelExec(ctx context.Context, chk *chunk.Chunk) error {
chk.Reset()
for {
if e.prepared {
// Since we return e.maxChunkSize rows every time, so we should not traverse
// `groupSet` because of its randomness.
for ; e.cursor4GroupKey < len(e.groupKeys); e.cursor4GroupKey++ {
partialResults := e.getPartialResults(e.groupKeys[e.cursor4GroupKey])
if len(e.PartialAggFuncs) == 0 {
chk.SetNumVirtualRows(chk.NumRows() + 1)
}
for i, af := range e.PartialAggFuncs {
if err := af.AppendFinalResult2Chunk(e.ctx, partialResults[i], chk); err != nil {
return err
}
}
if chk.IsFull() {
e.cursor4GroupKey++
return nil
}
}
e.resetSpillMode()
}
if e.executed {
return nil
}
if err := e.execute(ctx); err != nil {
return err
}
if (len(e.groupSet.StringSet) == 0) && len(e.GroupByItems) == 0 {
// If no groupby and no data, we should add an empty group.
// For example:
// "select count(c) from t;" should return one row [0]
// "select count(c) from t group by c1;" should return empty result set.
e.memTracker.Consume(e.groupSet.Insert(""))
e.groupKeys = append(e.groupKeys, "")
}
e.prepared = true
}
}
func (e *HashAggExec) resetSpillMode() {
e.cursor4GroupKey, e.groupKeys = 0, e.groupKeys[:0]
var setSize int64
e.groupSet, setSize = set.NewStringSetWithMemoryUsage()
e.partialResultMap = make(aggPartialResultMapper)
e.bInMap = 0
e.prepared = false
e.executed = e.numOfSpilledChks == e.listInDisk.NumChunks() // No data is spilling again, all data have been processed.
e.numOfSpilledChks = e.listInDisk.NumChunks()
e.memTracker.ReplaceBytesUsed(setSize)
atomic.StoreUint32(&e.inSpillMode, 0)
}
// execute fetches Chunks from src and update each aggregate function for each row in Chunk.
func (e *HashAggExec) execute(ctx context.Context) (err error) {
defer func() {
if e.tmpChkForSpill.NumRows() > 0 && err == nil {
err = e.listInDisk.Add(e.tmpChkForSpill)
e.tmpChkForSpill.Reset()
}
}()
for {
mSize := e.childResult.MemoryUsage()
if err := e.getNextChunk(ctx); err != nil {
return err
}
failpoint.Inject("ConsumeRandomPanic", nil)
e.memTracker.Consume(e.childResult.MemoryUsage() - mSize)
if err != nil {
return err
}
failpoint.Inject("unparallelHashAggError", func(val failpoint.Value) {
if val, _ := val.(bool); val {
failpoint.Return(errors.New("HashAggExec.unparallelExec error"))
}
})
// no more data.
if e.childResult.NumRows() == 0 {
return nil
}
e.groupKeyBuffer, err = getGroupKey(e.ctx, e.childResult, e.groupKeyBuffer, e.GroupByItems)
if err != nil {
return err
}
allMemDelta := int64(0)
sel := make([]int, 0, e.childResult.NumRows())
var tmpBuf [1]chunk.Row
for j := 0; j < e.childResult.NumRows(); j++ {
groupKey := string(e.groupKeyBuffer[j]) // do memory copy here, because e.groupKeyBuffer may be reused.
if !e.groupSet.Exist(groupKey) {
if atomic.LoadUint32(&e.inSpillMode) == 1 && e.groupSet.Count() > 0 {
sel = append(sel, j)
continue
}
allMemDelta += e.groupSet.Insert(groupKey)
e.groupKeys = append(e.groupKeys, groupKey)
}
partialResults := e.getPartialResults(groupKey)
for i, af := range e.PartialAggFuncs {
tmpBuf[0] = e.childResult.GetRow(j)
memDelta, err := af.UpdatePartialResult(e.ctx, tmpBuf[:], partialResults[i])
if err != nil {
return err
}
allMemDelta += memDelta
}
}
// spill unprocessed data when exceeded.
if len(sel) > 0 {
e.childResult.SetSel(sel)
err = e.spillUnprocessedData(len(sel) == cap(sel))
if err != nil {
return err
}
}
failpoint.Inject("ConsumeRandomPanic", nil)
e.memTracker.Consume(allMemDelta)
}
}
func (e *HashAggExec) spillUnprocessedData(isFullChk bool) (err error) {
if isFullChk {
return e.listInDisk.Add(e.childResult)
}
for i := 0; i < e.childResult.NumRows(); i++ {
e.tmpChkForSpill.AppendRow(e.childResult.GetRow(i))
if e.tmpChkForSpill.IsFull() {
err = e.listInDisk.Add(e.tmpChkForSpill)
if err != nil {
return err
}
e.tmpChkForSpill.Reset()
}
}
return nil
}
func (e *HashAggExec) getNextChunk(ctx context.Context) (err error) {
e.childResult.Reset()
if !e.isChildDrained {
if err := Next(ctx, e.children[0], e.childResult); err != nil {
return err
}
if e.childResult.NumRows() == 0 {
e.isChildDrained = true
} else {
return nil
}
}
if e.offsetOfSpilledChks < e.numOfSpilledChks {
e.childResult, err = e.listInDisk.GetChunk(e.offsetOfSpilledChks)
if err != nil {
return err
}
e.offsetOfSpilledChks++
}
return nil
}
func (e *HashAggExec) getPartialResults(groupKey string) []aggfuncs.PartialResult {
partialResults, ok := e.partialResultMap[groupKey]
allMemDelta := int64(0)
if !ok {
partialResults = make([]aggfuncs.PartialResult, 0, len(e.PartialAggFuncs))
for _, af := range e.PartialAggFuncs {
partialResult, memDelta := af.AllocPartialResult()
partialResults = append(partialResults, partialResult)
allMemDelta += memDelta
}
// Map will expand when count > bucketNum * loadFactor. The memory usage will doubled.
if len(e.partialResultMap)+1 > (1<<e.bInMap)*hack.LoadFactorNum/hack.LoadFactorDen {
e.memTracker.Consume(hack.DefBucketMemoryUsageForMapStrToSlice * (1 << e.bInMap))
e.bInMap++
}
e.partialResultMap[groupKey] = partialResults
allMemDelta += int64(len(groupKey))
}
failpoint.Inject("ConsumeRandomPanic", nil)
e.memTracker.Consume(allMemDelta)
return partialResults
}
func (e *HashAggExec) initRuntimeStats() {
if e.runtimeStats != nil {
stats := &HashAggRuntimeStats{
PartialConcurrency: e.ctx.GetSessionVars().HashAggPartialConcurrency(),
FinalConcurrency: e.ctx.GetSessionVars().HashAggFinalConcurrency(),
}
stats.PartialStats = make([]*AggWorkerStat, 0, stats.PartialConcurrency)
stats.FinalStats = make([]*AggWorkerStat, 0, stats.FinalConcurrency)
e.stats = stats
e.ctx.GetSessionVars().StmtCtx.RuntimeStatsColl.RegisterStats(e.id, e.stats)
}
}
// HashAggRuntimeStats record the HashAggExec runtime stat
type HashAggRuntimeStats struct {
PartialConcurrency int
PartialWallTime int64
FinalConcurrency int
FinalWallTime int64
PartialStats []*AggWorkerStat
FinalStats []*AggWorkerStat
}
// AggWorkerInfo contains the agg worker information.
type AggWorkerInfo struct {
Concurrency int
WallTime int64
}
// AggWorkerStat record the AggWorker runtime stat
type AggWorkerStat struct {
TaskNum int64
WaitTime int64
ExecTime int64
WorkerTime int64
}
// Clone implements the RuntimeStats interface.
func (w *AggWorkerStat) Clone() *AggWorkerStat {
return &AggWorkerStat{
TaskNum: w.TaskNum,
WaitTime: w.WaitTime,
ExecTime: w.ExecTime,
WorkerTime: w.WorkerTime,
}
}
func (*HashAggRuntimeStats) workerString(buf *bytes.Buffer, prefix string, concurrency int, wallTime int64, workerStats []*AggWorkerStat) {
var totalTime, totalWait, totalExec, totalTaskNum int64
for _, w := range workerStats {
totalTime += w.WorkerTime
totalWait += w.WaitTime
totalExec += w.ExecTime
totalTaskNum += w.TaskNum
}
buf.WriteString(prefix)
buf.WriteString(fmt.Sprintf("_worker:{wall_time:%s, concurrency:%d, task_num:%d, tot_wait:%s, tot_exec:%s, tot_time:%s",
time.Duration(wallTime), concurrency, totalTaskNum, time.Duration(totalWait), time.Duration(totalExec), time.Duration(totalTime)))
n := len(workerStats)
if n > 0 {
slices.SortFunc(workerStats, func(i, j *AggWorkerStat) bool { return i.WorkerTime < j.WorkerTime })
buf.WriteString(fmt.Sprintf(", max:%v, p95:%v",
time.Duration(workerStats[n-1].WorkerTime), time.Duration(workerStats[n*19/20].WorkerTime)))
}
buf.WriteString("}")
}
// String implements the RuntimeStats interface.
func (e *HashAggRuntimeStats) String() string {
buf := bytes.NewBuffer(make([]byte, 0, 64))
e.workerString(buf, "partial", e.PartialConcurrency, atomic.LoadInt64(&e.PartialWallTime), e.PartialStats)
buf.WriteString(", ")
e.workerString(buf, "final", e.FinalConcurrency, atomic.LoadInt64(&e.FinalWallTime), e.FinalStats)
return buf.String()
}
// Clone implements the RuntimeStats interface.
func (e *HashAggRuntimeStats) Clone() execdetails.RuntimeStats {
newRs := &HashAggRuntimeStats{
PartialConcurrency: e.PartialConcurrency,
PartialWallTime: atomic.LoadInt64(&e.PartialWallTime),
FinalConcurrency: e.FinalConcurrency,
FinalWallTime: atomic.LoadInt64(&e.FinalWallTime),
PartialStats: make([]*AggWorkerStat, 0, e.PartialConcurrency),
FinalStats: make([]*AggWorkerStat, 0, e.FinalConcurrency),
}
for _, s := range e.PartialStats {
newRs.PartialStats = append(newRs.PartialStats, s.Clone())
}
for _, s := range e.FinalStats {
newRs.FinalStats = append(newRs.FinalStats, s.Clone())
}
return newRs
}
// Merge implements the RuntimeStats interface.
func (e *HashAggRuntimeStats) Merge(other execdetails.RuntimeStats) {
tmp, ok := other.(*HashAggRuntimeStats)
if !ok {
return
}
atomic.AddInt64(&e.PartialWallTime, atomic.LoadInt64(&tmp.PartialWallTime))
atomic.AddInt64(&e.FinalWallTime, atomic.LoadInt64(&tmp.FinalWallTime))
e.PartialStats = append(e.PartialStats, tmp.PartialStats...)
e.FinalStats = append(e.FinalStats, tmp.FinalStats...)
}
// Tp implements the RuntimeStats interface.
func (*HashAggRuntimeStats) Tp() int {
return execdetails.TpHashAggRuntimeStat
}
// StreamAggExec deals with all the aggregate functions.
// It assumes all the input data is sorted by group by key.
// When Next() is called, it will return a result for the same group.
type StreamAggExec struct {
baseExecutor
executed bool
// isChildReturnEmpty indicates whether the child executor only returns an empty input.
isChildReturnEmpty bool
defaultVal *chunk.Chunk
groupChecker *vecGroupChecker
inputIter *chunk.Iterator4Chunk
inputRow chunk.Row
aggFuncs []aggfuncs.AggFunc
partialResults []aggfuncs.PartialResult
groupRows []chunk.Row
childResult *chunk.Chunk
memTracker *memory.Tracker // track memory usage.
// memUsageOfInitialPartialResult indicates the memory usage of all partial results after initialization.
// All partial results will be reset after processing one group data, and the memory usage should also be reset.
// We can't get memory delta from ResetPartialResult, so record the memory usage here.
memUsageOfInitialPartialResult int64
}
// Open implements the Executor Open interface.
func (e *StreamAggExec) Open(ctx context.Context) error {
failpoint.Inject("mockStreamAggExecBaseExecutorOpenReturnedError", func(val failpoint.Value) {
if val, _ := val.(bool); val {
failpoint.Return(errors.New("mock StreamAggExec.baseExecutor.Open returned error"))
}
})
if err := e.baseExecutor.Open(ctx); err != nil {
return err
}
// If panic in Open, the children executor should be closed because they are open.
defer closeBaseExecutor(&e.baseExecutor)
e.childResult = newFirstChunk(e.children[0])
e.executed = false
e.isChildReturnEmpty = true
e.inputIter = chunk.NewIterator4Chunk(e.childResult)
e.inputRow = e.inputIter.End()
e.partialResults = make([]aggfuncs.PartialResult, 0, len(e.aggFuncs))
for _, aggFunc := range e.aggFuncs {
partialResult, memDelta := aggFunc.AllocPartialResult()
e.partialResults = append(e.partialResults, partialResult)
e.memUsageOfInitialPartialResult += memDelta
}
// bytesLimit <= 0 means no limit, for now we just track the memory footprint
e.memTracker = memory.NewTracker(e.id, -1)
if e.ctx.GetSessionVars().TrackAggregateMemoryUsage {
e.memTracker.AttachTo(e.ctx.GetSessionVars().StmtCtx.MemTracker)
}
failpoint.Inject("ConsumeRandomPanic", nil)
e.memTracker.Consume(e.childResult.MemoryUsage() + e.memUsageOfInitialPartialResult)
return nil
}
// Close implements the Executor Close interface.
func (e *StreamAggExec) Close() error {
if e.childResult != nil {
e.memTracker.Consume(-e.childResult.MemoryUsage() - e.memUsageOfInitialPartialResult)
e.childResult = nil
}
e.groupChecker.reset()
return e.baseExecutor.Close()
}
// Next implements the Executor Next interface.
func (e *StreamAggExec) Next(ctx context.Context, req *chunk.Chunk) (err error) {
req.Reset()
for !e.executed && !req.IsFull() {
err = e.consumeOneGroup(ctx, req)
if err != nil {
e.executed = true
return err
}
}
return nil
}
func (e *StreamAggExec) consumeOneGroup(ctx context.Context, chk *chunk.Chunk) (err error) {
if e.groupChecker.isExhausted() {
if err = e.consumeCurGroupRowsAndFetchChild(ctx, chk); err != nil {
return err
}
if !e.executed {
_, err := e.groupChecker.splitIntoGroups(e.childResult)
if err != nil {
return err
}
} else {
return nil
}
}
begin, end := e.groupChecker.getNextGroup()
for i := begin; i < end; i++ {
e.groupRows = append(e.groupRows, e.childResult.GetRow(i))
}
for meetLastGroup := end == e.childResult.NumRows(); meetLastGroup; {
meetLastGroup = false
if err = e.consumeCurGroupRowsAndFetchChild(ctx, chk); err != nil || e.executed {
return err
}
isFirstGroupSameAsPrev, err := e.groupChecker.splitIntoGroups(e.childResult)
if err != nil {
return err
}
if isFirstGroupSameAsPrev {
begin, end = e.groupChecker.getNextGroup()
for i := begin; i < end; i++ {
e.groupRows = append(e.groupRows, e.childResult.GetRow(i))
}
meetLastGroup = end == e.childResult.NumRows()
}
}
err = e.consumeGroupRows()
if err != nil {
return err
}
return e.appendResult2Chunk(chk)
}
func (e *StreamAggExec) consumeGroupRows() error {
if len(e.groupRows) == 0 {
return nil
}
allMemDelta := int64(0)
for i, aggFunc := range e.aggFuncs {
memDelta, err := aggFunc.UpdatePartialResult(e.ctx, e.groupRows, e.partialResults[i])
if err != nil {
return err
}
allMemDelta += memDelta
}
failpoint.Inject("ConsumeRandomPanic", nil)
e.memTracker.Consume(allMemDelta)
e.groupRows = e.groupRows[:0]
return nil
}
func (e *StreamAggExec) consumeCurGroupRowsAndFetchChild(ctx context.Context, chk *chunk.Chunk) (err error) {
// Before fetching a new batch of input, we should consume the last group.
err = e.consumeGroupRows()
if err != nil {
return err
}
mSize := e.childResult.MemoryUsage()
err = Next(ctx, e.children[0], e.childResult)
failpoint.Inject("ConsumeRandomPanic", nil)
e.memTracker.Consume(e.childResult.MemoryUsage() - mSize)
if err != nil {
return err
}
// No more data.
if e.childResult.NumRows() == 0 {
if !e.isChildReturnEmpty {
err = e.appendResult2Chunk(chk)
} else if e.defaultVal != nil {
chk.Append(e.defaultVal, 0, 1)
}
e.executed = true
return err
}
// Reach here, "e.childrenResults[0].NumRows() > 0" is guaranteed.
e.isChildReturnEmpty = false
e.inputRow = e.inputIter.Begin()
return nil
}
// appendResult2Chunk appends result of all the aggregation functions to the
// result chunk, and reset the evaluation context for each aggregation.
func (e *StreamAggExec) appendResult2Chunk(chk *chunk.Chunk) error {
for i, aggFunc := range e.aggFuncs {
err := aggFunc.AppendFinalResult2Chunk(e.ctx, e.partialResults[i], chk)
if err != nil {
return err
}
aggFunc.ResetPartialResult(e.partialResults[i])
}
failpoint.Inject("ConsumeRandomPanic", nil)
// All partial results have been reset, so reset the memory usage.
e.memTracker.ReplaceBytesUsed(e.childResult.MemoryUsage() + e.memUsageOfInitialPartialResult)
if len(e.aggFuncs) == 0 {
chk.SetNumVirtualRows(chk.NumRows() + 1)
}
return nil
}
// vecGroupChecker is used to split a given chunk according to the `group by` expression in a vectorized manner
// It is usually used for streamAgg
type vecGroupChecker struct {
ctx sessionctx.Context
GroupByItems []expression.Expression
// groupOffset holds the offset of the last row in each group of the current chunk
groupOffset []int
// groupCount is the count of groups in the current chunk
groupCount int
// nextGroupID records the group id of the next group to be consumed
nextGroupID int
// lastGroupKeyOfPrevChk is the groupKey of the last group of the previous chunk
lastGroupKeyOfPrevChk []byte
// firstGroupKey and lastGroupKey are used to store the groupKey of the first and last group of the current chunk
firstGroupKey []byte
lastGroupKey []byte
// firstRowDatums and lastRowDatums store the results of the expression evaluation for the first and last rows of the current chunk in datum
// They are used to encode to get firstGroupKey and lastGroupKey
firstRowDatums []types.Datum
lastRowDatums []types.Datum
// sameGroup is used to check whether the current row belongs to the same group as the previous row
sameGroup []bool
// set these functions for testing
allocateBuffer func(evalType types.EvalType, capacity int) (*chunk.Column, error)
releaseBuffer func(buf *chunk.Column)
}
func newVecGroupChecker(ctx sessionctx.Context, items []expression.Expression) *vecGroupChecker {
return &vecGroupChecker{
ctx: ctx,
GroupByItems: items,
groupCount: 0,
nextGroupID: 0,
sameGroup: make([]bool, 1024),
}
}
// splitIntoGroups splits a chunk into multiple groups which the row in the same group have the same groupKey
// `isFirstGroupSameAsPrev` indicates whether the groupKey of the first group of the newly passed chunk is equal to the groupKey of the last group left before
// TODO: Since all the group by items are only a column reference, guaranteed by building projection below aggregation, we can directly compare data in a chunk.
func (e *vecGroupChecker) splitIntoGroups(chk *chunk.Chunk) (isFirstGroupSameAsPrev bool, err error) {
// The numRows can not be zero. `fetchChild` is called before `splitIntoGroups` is called.
// if numRows == 0, it will be returned in `fetchChild`. See `fetchChild` for more details.
numRows := chk.NumRows()
e.reset()
e.nextGroupID = 0
if len(e.GroupByItems) == 0 {
e.groupOffset = append(e.groupOffset, numRows)
e.groupCount = 1
return true, nil
}
for _, item := range e.GroupByItems {
err = e.getFirstAndLastRowDatum(item, chk, numRows)
if err != nil {
return false, err
}
}
e.firstGroupKey, err = codec.EncodeValue(e.ctx.GetSessionVars().StmtCtx, e.firstGroupKey, e.firstRowDatums...)
if err != nil {
return false, err
}
e.lastGroupKey, err = codec.EncodeValue(e.ctx.GetSessionVars().StmtCtx, e.lastGroupKey, e.lastRowDatums...)
if err != nil {
return false, err
}
if len(e.lastGroupKeyOfPrevChk) == 0 {
isFirstGroupSameAsPrev = false
} else {
if bytes.Equal(e.lastGroupKeyOfPrevChk, e.firstGroupKey) {
isFirstGroupSameAsPrev = true
} else {
isFirstGroupSameAsPrev = false
}
}
if length := len(e.lastGroupKey); len(e.lastGroupKeyOfPrevChk) >= length {
e.lastGroupKeyOfPrevChk = e.lastGroupKeyOfPrevChk[:length]
} else {
e.lastGroupKeyOfPrevChk = make([]byte, length)
}
copy(e.lastGroupKeyOfPrevChk, e.lastGroupKey)
if bytes.Equal(e.firstGroupKey, e.lastGroupKey) {
e.groupOffset = append(e.groupOffset, numRows)
e.groupCount = 1
return isFirstGroupSameAsPrev, nil
}
if cap(e.sameGroup) < numRows {
e.sameGroup = make([]bool, 0, numRows)
}
e.sameGroup = append(e.sameGroup, false)
for i := 1; i < numRows; i++ {
e.sameGroup = append(e.sameGroup, true)
}
for _, item := range e.GroupByItems {
err = e.evalGroupItemsAndResolveGroups(item, chk, numRows)
if err != nil {
return false, err
}
}
for i := 1; i < numRows; i++ {
if !e.sameGroup[i] {
e.groupOffset = append(e.groupOffset, i)
}
}
e.groupOffset = append(e.groupOffset, numRows)
e.groupCount = len(e.groupOffset)
return isFirstGroupSameAsPrev, nil
}
func (e *vecGroupChecker) getFirstAndLastRowDatum(item expression.Expression, chk *chunk.Chunk, numRows int) (err error) {
var firstRowDatum, lastRowDatum types.Datum
tp := item.GetType()
eType := tp.EvalType()
switch eType {
case types.ETInt:
firstRowVal, firstRowIsNull, err := item.EvalInt(e.ctx, chk.GetRow(0))
if err != nil {
return err
}
lastRowVal, lastRowIsNull, err := item.EvalInt(e.ctx, chk.GetRow(numRows-1))
if err != nil {
return err
}
if !firstRowIsNull {
firstRowDatum.SetInt64(firstRowVal)
} else {
firstRowDatum.SetNull()
}
if !lastRowIsNull {
lastRowDatum.SetInt64(lastRowVal)
} else {
lastRowDatum.SetNull()
}
case types.ETReal:
firstRowVal, firstRowIsNull, err := item.EvalReal(e.ctx, chk.GetRow(0))
if err != nil {
return err
}
lastRowVal, lastRowIsNull, err := item.EvalReal(e.ctx, chk.GetRow(numRows-1))
if err != nil {
return err
}
if !firstRowIsNull {
firstRowDatum.SetFloat64(firstRowVal)
} else {
firstRowDatum.SetNull()
}
if !lastRowIsNull {
lastRowDatum.SetFloat64(lastRowVal)
} else {
lastRowDatum.SetNull()
}
case types.ETDecimal:
firstRowVal, firstRowIsNull, err := item.EvalDecimal(e.ctx, chk.GetRow(0))
if err != nil {
return err
}
lastRowVal, lastRowIsNull, err := item.EvalDecimal(e.ctx, chk.GetRow(numRows-1))
if err != nil {
return err
}
if !firstRowIsNull {
// make a copy to avoid DATA RACE
firstDatum := types.MyDecimal{}
err := firstDatum.FromString(firstRowVal.ToString())
if err != nil {
return err
}
firstRowDatum.SetMysqlDecimal(&firstDatum)
} else {
firstRowDatum.SetNull()
}
if !lastRowIsNull {
// make a copy to avoid DATA RACE
lastDatum := types.MyDecimal{}
err := lastDatum.FromString(lastRowVal.ToString())
if err != nil {
return err
}
lastRowDatum.SetMysqlDecimal(&lastDatum)
} else {
lastRowDatum.SetNull()
}
case types.ETDatetime, types.ETTimestamp:
firstRowVal, firstRowIsNull, err := item.EvalTime(e.ctx, chk.GetRow(0))
if err != nil {
return err
}
lastRowVal, lastRowIsNull, err := item.EvalTime(e.ctx, chk.GetRow(numRows-1))
if err != nil {
return err
}
if !firstRowIsNull {
firstRowDatum.SetMysqlTime(firstRowVal)
} else {
firstRowDatum.SetNull()
}
if !lastRowIsNull {
lastRowDatum.SetMysqlTime(lastRowVal)
} else {
lastRowDatum.SetNull()
}
case types.ETDuration:
firstRowVal, firstRowIsNull, err := item.EvalDuration(e.ctx, chk.GetRow(0))
if err != nil {
return err
}
lastRowVal, lastRowIsNull, err := item.EvalDuration(e.ctx, chk.GetRow(numRows-1))
if err != nil {
return err
}
if !firstRowIsNull {
firstRowDatum.SetMysqlDuration(firstRowVal)
} else {
firstRowDatum.SetNull()
}
if !lastRowIsNull {
lastRowDatum.SetMysqlDuration(lastRowVal)
} else {
lastRowDatum.SetNull()
}
case types.ETJson:
firstRowVal, firstRowIsNull, err := item.EvalJSON(e.ctx, chk.GetRow(0))
if err != nil {
return err
}
lastRowVal, lastRowIsNull, err := item.EvalJSON(e.ctx, chk.GetRow(numRows-1))
if err != nil {
return err
}
if !firstRowIsNull {
// make a copy to avoid DATA RACE
firstRowDatum.SetMysqlJSON(firstRowVal.Copy())
} else {
firstRowDatum.SetNull()
}
if !lastRowIsNull {
// make a copy to avoid DATA RACE
lastRowDatum.SetMysqlJSON(lastRowVal.Copy())
} else {
lastRowDatum.SetNull()
}
case types.ETString:
firstRowVal, firstRowIsNull, err := item.EvalString(e.ctx, chk.GetRow(0))
if err != nil {
return err
}
lastRowVal, lastRowIsNull, err := item.EvalString(e.ctx, chk.GetRow(numRows-1))
if err != nil {
return err
}
if !firstRowIsNull {
// make a copy to avoid DATA RACE
firstDatum := string([]byte(firstRowVal))
firstRowDatum.SetString(firstDatum, tp.GetCollate())
} else {
firstRowDatum.SetNull()
}
if !lastRowIsNull {
// make a copy to avoid DATA RACE
lastDatum := string([]byte(lastRowVal))
lastRowDatum.SetString(lastDatum, tp.GetCollate())
} else {
lastRowDatum.SetNull()
}
default:
err = fmt.Errorf("invalid eval type %v", eType)
return err
}
e.firstRowDatums = append(e.firstRowDatums, firstRowDatum)
e.lastRowDatums = append(e.lastRowDatums, lastRowDatum)
return err
}
// evalGroupItemsAndResolveGroups evaluates the chunk according to the expression item.
// And resolve the rows into groups according to the evaluation results
func (e *vecGroupChecker) evalGroupItemsAndResolveGroups(item expression.Expression, chk *chunk.Chunk, numRows int) (err error) {
tp := item.GetType()
eType := tp.EvalType()
if e.allocateBuffer == nil {
e.allocateBuffer = expression.GetColumn
}
if e.releaseBuffer == nil {
e.releaseBuffer = expression.PutColumn
}
col, err := e.allocateBuffer(eType, numRows)
if err != nil {
return err
}
defer e.releaseBuffer(col)
err = expression.EvalExpr(e.ctx, item, eType, chk, col)
if err != nil {
return err
}
previousIsNull := col.IsNull(0)
switch eType {
case types.ETInt:
vals := col.Int64s()
for i := 1; i < numRows; i++ {
isNull := col.IsNull(i)
if e.sameGroup[i] {
switch {
case !previousIsNull && !isNull:
if vals[i] != vals[i-1] {
e.sameGroup[i] = false
}
case isNull != previousIsNull:
e.sameGroup[i] = false
}
}
previousIsNull = isNull
}
case types.ETReal:
vals := col.Float64s()
for i := 1; i < numRows; i++ {
isNull := col.IsNull(i)
if e.sameGroup[i] {
switch {
case !previousIsNull && !isNull:
if vals[i] != vals[i-1] {
e.sameGroup[i] = false
}
case isNull != previousIsNull:
e.sameGroup[i] = false
}
}
previousIsNull = isNull
}
case types.ETDecimal:
vals := col.Decimals()
for i := 1; i < numRows; i++ {
isNull := col.IsNull(i)
if e.sameGroup[i] {
switch {
case !previousIsNull && !isNull:
if vals[i].Compare(&vals[i-1]) != 0 {
e.sameGroup[i] = false
}
case isNull != previousIsNull:
e.sameGroup[i] = false
}
}
previousIsNull = isNull
}
case types.ETDatetime, types.ETTimestamp:
vals := col.Times()
for i := 1; i < numRows; i++ {
isNull := col.IsNull(i)
if e.sameGroup[i] {
switch {
case !previousIsNull && !isNull:
if vals[i].Compare(vals[i-1]) != 0 {
e.sameGroup[i] = false
}
case isNull != previousIsNull:
e.sameGroup[i] = false
}
}
previousIsNull = isNull
}
case types.ETDuration:
vals := col.GoDurations()
for i := 1; i < numRows; i++ {
isNull := col.IsNull(i)
if e.sameGroup[i] {
switch {
case !previousIsNull && !isNull:
if vals[i] != vals[i-1] {
e.sameGroup[i] = false
}
case isNull != previousIsNull:
e.sameGroup[i] = false
}
}
previousIsNull = isNull
}
case types.ETJson:
var previousKey, key types.BinaryJSON
if !previousIsNull {
previousKey = col.GetJSON(0)
}
for i := 1; i < numRows; i++ {
isNull := col.IsNull(i)
if !isNull {
key = col.GetJSON(i)
}
if e.sameGroup[i] {
if isNull == previousIsNull {
if !isNull && types.CompareBinaryJSON(previousKey, key) != 0 {
e.sameGroup[i] = false
}
} else {
e.sameGroup[i] = false
}
}
if !isNull {
previousKey = key
}
previousIsNull = isNull
}
case types.ETString:
previousKey := codec.ConvertByCollationStr(col.GetString(0), tp)
for i := 1; i < numRows; i++ {
key := codec.ConvertByCollationStr(col.GetString(i), tp)
isNull := col.IsNull(i)
if e.sameGroup[i] {
if isNull != previousIsNull || previousKey != key {
e.sameGroup[i] = false
}
}
previousKey = key
previousIsNull = isNull
}
default:
err = fmt.Errorf("invalid eval type %v", eType)
}
if err != nil {
return err
}
return err
}
func (e *vecGroupChecker) getNextGroup() (begin, end int) {
if e.nextGroupID == 0 {
begin = 0
} else {
begin = e.groupOffset[e.nextGroupID-1]
}
end = e.groupOffset[e.nextGroupID]
e.nextGroupID++
return begin, end
}
func (e *vecGroupChecker) isExhausted() bool {
return e.nextGroupID >= e.groupCount
}
func (e *vecGroupChecker) reset() {
if e.groupOffset != nil {
e.groupOffset = e.groupOffset[:0]
}
if e.sameGroup != nil {
e.sameGroup = e.sameGroup[:0]
}
if e.firstGroupKey != nil {
e.firstGroupKey = e.firstGroupKey[:0]
}
if e.lastGroupKey != nil {
e.lastGroupKey = e.lastGroupKey[:0]
}
if e.firstRowDatums != nil {
e.firstRowDatums = e.firstRowDatums[:0]
}
if e.lastRowDatums != nil {
e.lastRowDatums = e.lastRowDatums[:0]
}
}
// ActionSpill returns a AggSpillDiskAction for spilling intermediate data for hashAgg.
func (e *HashAggExec) ActionSpill() *AggSpillDiskAction {
if e.spillAction == nil {
e.spillAction = &AggSpillDiskAction{
e: e,
}
}
return e.spillAction
}
// maxSpillTimes indicates how many times the data can spill at most.
const maxSpillTimes = 10
// AggSpillDiskAction implements memory.ActionOnExceed for unparalleled HashAgg.
// If the memory quota of a query is exceeded, AggSpillDiskAction.Action is
// triggered.
type AggSpillDiskAction struct {
memory.BaseOOMAction
e *HashAggExec
spillTimes uint32
}
// Action set HashAggExec spill mode.
func (a *AggSpillDiskAction) Action(t *memory.Tracker) {
// Guarantee that processed data is at least 20% of the threshold, to avoid spilling too frequently.
if atomic.LoadUint32(&a.e.inSpillMode) == 0 && a.spillTimes < maxSpillTimes && a.e.memTracker.BytesConsumed() >= t.GetBytesLimit()/5 {
a.spillTimes++
logutil.BgLogger().Info("memory exceeds quota, set aggregate mode to spill-mode",
zap.Uint32("spillTimes", a.spillTimes),
zap.Int64("consumed", t.BytesConsumed()),
zap.Int64("quota", t.GetBytesLimit()))
atomic.StoreUint32(&a.e.inSpillMode, 1)
return
}
if fallback := a.GetFallback(); fallback != nil {
fallback.Action(t)
}
}
// GetPriority get the priority of the Action
func (*AggSpillDiskAction) GetPriority() int64 {
return memory.DefSpillPriority
}
// SetLogHook sets the hook, it does nothing just to form the memory.ActionOnExceed interface.
func (*AggSpillDiskAction) SetLogHook(_ func(uint64)) {}
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