tidb estimate 源码
tidb estimate 代码
文件路径：/statistics/estimate.go
// Copyright 2019 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 statistics
import (
"math"
"github.com/pingcap/tidb/util/mathutil"
)
// calculateEstimateNDV calculates the estimate ndv of a sampled data from a multisize with size total.
func calculateEstimateNDV(h *topNHelper, rowCount uint64) (ndv uint64, scaleRatio uint64) {
sampleSize, sampleNDV, onlyOnceItems := h.sampleSize, uint64(len(h.sorted)), h.onlyOnceItems
scaleRatio = rowCount / sampleSize
if onlyOnceItems == sampleSize {
// Assume this is a unique column, so do not scale up the count of elements
return rowCount, 1
} else if onlyOnceItems == 0 {
// Assume data only consists of sampled data
// Nothing to do, no change with scale ratio
return sampleNDV, scaleRatio
}
// Charikar, Moses, et al. "Towards estimation error guarantees for distinct values."
// Proceedings of the nineteenth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems. ACM, 2000.
// This is GEE in that paper.
// estimateNDV = sqrt(N/n) f_1 + sum_2..inf f_i
// f_i = number of elements occurred i times in sample
f1 := float64(onlyOnceItems)
n := float64(sampleSize)
N := float64(rowCount)
d := float64(sampleNDV)
ndv = uint64(math.Sqrt(N/n)*f1 + d - f1 + 0.5)
ndv = mathutil.Max(ndv, sampleNDV)
ndv = mathutil.Min(ndv, rowCount)
return ndv, scaleRatio
}
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