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// Copyright 2017 PingCAP, Inc.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// See the License for the specific language governing permissions and
// limitations under the License.
package statistics
import (
"github.com/pingcap/tidb/sessionctx"
"github.com/pingcap/tidb/sessionctx/stmtctx"
"github.com/pingcap/tidb/types"
"github.com/pkg/errors"
)
// SortedBuilder is used to build histograms for PK and index.
type SortedBuilder struct {
sc *stmtctx.StatementContext
numBuckets int64
valuesPerBucket int64
lastNumber int64
bucketIdx int64
Count int64
hist *Histogram
}
// NewSortedBuilder creates a new SortedBuilder.
func NewSortedBuilder(sc *stmtctx.StatementContext, numBuckets, id int64, tp *types.FieldType) *SortedBuilder {
return &SortedBuilder{
sc: sc,
numBuckets: numBuckets,
valuesPerBucket: 1,
hist: NewHistogram(id, 0, 0, 0, tp, int(numBuckets), 0),
}
}
// Hist returns the histogram built by SortedBuilder.
func (b *SortedBuilder) Hist() *Histogram {
return b.hist
}
// Iterate updates the histogram incrementally.
func (b *SortedBuilder) Iterate(data types.Datum) error {
b.Count++
if b.Count == 1 {
b.hist.AppendBucket(&data, &data, 1, 1)
b.hist.NDV = 1
return nil
}
cmp, err := b.hist.GetUpper(int(b.bucketIdx)).CompareDatum(b.sc, &data)
if err != nil {
return errors.Trace(err)
}
if cmp == 0 {
// The new item has the same value as current bucket value, to ensure that
// a same value only stored in a single bucket, we do not increase bucketIdx even if it exceeds
// valuesPerBucket.
b.hist.Buckets[b.bucketIdx].Count++
b.hist.Buckets[b.bucketIdx].Repeat++
} else if b.hist.Buckets[b.bucketIdx].Count+1-b.lastNumber <= b.valuesPerBucket {
// The bucket still have room to store a new item, update the bucket.
b.hist.updateLastBucket(&data, b.hist.Buckets[b.bucketIdx].Count+1, 1)
b.hist.NDV++
} else {
// All buckets are full, we should merge buckets.
if b.bucketIdx+1 == b.numBuckets {
b.hist.mergeBuckets(int(b.bucketIdx))
b.valuesPerBucket *= 2
b.bucketIdx = b.bucketIdx / 2
if b.bucketIdx == 0 {
b.lastNumber = 0
} else {
b.lastNumber = b.hist.Buckets[b.bucketIdx-1].Count
}
}
// We may merge buckets, so we should check it again.
if b.hist.Buckets[b.bucketIdx].Count+1-b.lastNumber <= b.valuesPerBucket {
b.hist.updateLastBucket(&data, b.hist.Buckets[b.bucketIdx].Count+1, 1)
} else {
b.lastNumber = b.hist.Buckets[b.bucketIdx].Count
b.bucketIdx++
b.hist.AppendBucket(&data, &data, b.lastNumber+1, 1)
}
b.hist.NDV++
}
return nil
}
// BuildColumn builds histogram from samples for column.
func BuildColumn(ctx sessionctx.Context, numBuckets, id int64, collector *SampleCollector, tp *types.FieldType) (*Histogram, error) {
count := collector.Count
if count == 0 {
return &Histogram{ID: id, NullCount: collector.NullCount}, nil
}
sc := ctx.GetSessionVars().StmtCtx
samples := collector.Samples
err := types.SortDatums(sc, samples)
if err != nil {
return nil, errors.Trace(err)
}
ndv := collector.FMSketch.NDV()
if ndv > count {
ndv = count
}
hg := NewHistogram(id, ndv, collector.NullCount, 0, tp, int(numBuckets), collector.TotalSize)
sampleNum := int64(len(samples))
// As we use samples to build the histogram, the bucket number and repeat should multiply a factor.
sampleFactor := float64(count) / float64(len(samples))
// Since bucket count is increased by sampleFactor, so the actual max values per bucket is
// floor(valuesPerBucket/sampleFactor)*sampleFactor, which may less than valuesPerBucket,
// thus we need to add a sampleFactor to avoid building too many buckets.
valuesPerBucket := float64(count)/float64(numBuckets) + sampleFactor
ndvFactor := float64(count) / float64(hg.NDV)
if ndvFactor > sampleFactor {
ndvFactor = sampleFactor
}
bucketIdx := 0
var lastCount int64
hg.AppendBucket(&samples[0], &samples[0], int64(sampleFactor), int64(ndvFactor))
for i := int64(1); i < sampleNum; i++ {
cmp, err := hg.GetUpper(bucketIdx).CompareDatum(sc, &samples[i])
if err != nil {
return nil, errors.Trace(err)
}
totalCount := float64(i+1) * sampleFactor
if cmp == 0 {
// The new item has the same value as current bucket value, to ensure that
// a same value only stored in a single bucket, we do not increase bucketIdx even if it exceeds
// valuesPerBucket.
hg.Buckets[bucketIdx].Count = int64(totalCount)
if float64(hg.Buckets[bucketIdx].Repeat) == ndvFactor {
hg.Buckets[bucketIdx].Repeat = int64(2 * sampleFactor)
} else {
hg.Buckets[bucketIdx].Repeat += int64(sampleFactor)
}
} else if totalCount-float64(lastCount) <= valuesPerBucket {
// The bucket still have room to store a new item, update the bucket.
hg.updateLastBucket(&samples[i], int64(totalCount), int64(ndvFactor))
} else {
lastCount = hg.Buckets[bucketIdx].Count
// The bucket is full, store the item in the next bucket.
bucketIdx++
hg.AppendBucket(&samples[i], &samples[i], int64(totalCount), int64(ndvFactor))
}
}
return hg, nil
}
// AnalyzeResult is used to represent analyze result.
type AnalyzeResult struct {
// PhysicalTableID is the id of a partition or a table.
PhysicalTableID int64
Hist []*Histogram
Cms []*CMSketch
Count int64
IsIndex int
Err error
}
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