forked from huichen/wukong
-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathbenchmark.go
207 lines (187 loc) · 5.48 KB
/
benchmark.go
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
// 悟空性能测试
package main
import (
"bufio"
"flag"
"github.com/huichen/wukong/engine"
"github.com/huichen/wukong/types"
"log"
"os"
"runtime"
"runtime/pprof"
"strings"
"time"
)
const (
numRepeatQuery = 1000
)
var (
weibo_data = flag.String(
"weibo_data",
"../testdata/weibo_data.txt",
"微博数据")
queries = flag.String(
"queries",
"女人母亲,你好中国,网络草根,热门微博,红十字会,"+
"鳄鱼表演,星座歧视,chinajoy,高帅富,假期计划",
"待搜索的关键词")
dictionaries = flag.String(
"dictionaries",
"../data/dictionary.txt",
"分词字典文件")
stop_token_file = flag.String(
"stop_token_file",
"../data/stop_tokens.txt",
"停用词文件")
cpuprofile = flag.String("cpuprofile", "", "处理器profile文件")
memprofile = flag.String("memprofile", "", "内存profile文件")
num_repeat_text = flag.Int("num_repeat_text", 10, "文本重复加入多少次")
index_type = flag.Int("index_type", types.DocIdsIndex, "索引类型")
use_persistent = flag.Bool("use_persistent", false, "是否使用持久存储")
persistent_storage_folder = flag.String("persistent_storage_folder", "benchmark.persistent", "持久存储数据库保存的目录")
persistent_storage_shards = flag.Int("persistent_storage_shards", 0, "持久数据库存储裂分数目")
searcher = engine.Engine{}
options = types.RankOptions{
OutputOffset: 0,
MaxOutputs: 100,
}
searchQueries = []string{}
NumShards = 2
numQueryThreads = runtime.NumCPU() / NumShards
)
func main() {
// 解析命令行参数
flag.Parse()
searchQueries = strings.Split(*queries, ",")
log.Printf("待搜索的关键词为\"%s\"", searchQueries)
// 初始化
tBeginInit := time.Now()
searcher.Init(types.EngineInitOptions{
SegmenterDictionaries: *dictionaries,
StopTokenFile: *stop_token_file,
IndexerInitOptions: &types.IndexerInitOptions{
IndexType: *index_type,
},
NumShards: NumShards,
DefaultRankOptions: &options,
UsePersistentStorage: *use_persistent,
PersistentStorageFolder: *persistent_storage_folder,
PersistentStorageShards: *persistent_storage_shards,
})
tEndInit := time.Now()
defer searcher.Close()
// 打开将要搜索的文件
file, err := os.Open(*weibo_data)
if err != nil {
log.Fatal(err)
}
defer file.Close()
// 逐行读入
log.Printf("读入文本 %s", *weibo_data)
scanner := bufio.NewScanner(file)
lines := []string{}
size := 0
for scanner.Scan() {
var text string
data := strings.Split(scanner.Text(), "||||")
if len(data) != 10 {
continue
}
text = data[9]
if text != "" {
size += len(text) * (*num_repeat_text)
lines = append(lines, text)
}
}
log.Print("文件行数", len(lines))
// 记录时间
t0 := time.Now()
// 打开处理器profile文件
if *cpuprofile != "" {
f, err := os.Create(*cpuprofile)
if err != nil {
log.Fatal(err)
}
pprof.StartCPUProfile(f)
defer pprof.StopCPUProfile()
}
// 建索引
log.Print("建索引 ... ")
docId := uint64(1)
for i := 0; i < *num_repeat_text; i++ {
for _, line := range lines {
searcher.IndexDocument(docId, types.DocumentIndexData{
Content: line})
docId++
if docId-docId/1000000*1000000 == 0 {
log.Printf("已索引%d百万文档", docId/1000000)
runtime.GC()
}
}
}
searcher.FlushIndex()
log.Print("加入的索引总数", searcher.NumTokenIndexAdded())
// 记录时间
t1 := time.Now()
log.Printf("建立索引花费时间 %v", t1.Sub(t0))
log.Printf("建立索引速度每秒添加 %f 百万个索引",
float64(searcher.NumTokenIndexAdded())/t1.Sub(t0).Seconds()/(1000000))
// 写入内存profile文件
if *memprofile != "" {
f, err := os.Create(*memprofile)
if err != nil {
log.Fatal(err)
}
pprof.WriteHeapProfile(f)
defer f.Close()
}
// 记录时间
t2 := time.Now()
done := make(chan bool)
for iThread := 0; iThread < numQueryThreads; iThread++ {
go search(done)
}
for iThread := 0; iThread < numQueryThreads; iThread++ {
<-done
}
// 记录时间并计算分词速度
t3 := time.Now()
log.Printf("搜索平均响应时间 %v 毫秒",
t3.Sub(t2).Seconds()*1000/float64(numRepeatQuery*len(searchQueries)))
log.Printf("搜索吞吐量每秒 %v 次查询",
float64(numRepeatQuery*numQueryThreads*len(searchQueries))/
t3.Sub(t2).Seconds())
if *use_persistent {
searcher.Close()
t4 := time.Now()
searcher1 := engine.Engine{}
searcher1.Init(types.EngineInitOptions{
SegmenterDictionaries: *dictionaries,
StopTokenFile: *stop_token_file,
IndexerInitOptions: &types.IndexerInitOptions{
IndexType: *index_type,
},
NumShards: NumShards,
DefaultRankOptions: &options,
UsePersistentStorage: *use_persistent,
PersistentStorageFolder: *persistent_storage_folder,
PersistentStorageShards: *persistent_storage_shards,
})
defer searcher1.Close()
t5 := time.Now()
t := t5.Sub(t4).Seconds() - tEndInit.Sub(tBeginInit).Seconds()
log.Print("从持久存储加入的索引总数", searcher1.NumTokenIndexAdded())
log.Printf("从持久存储建立索引花费时间 %v 秒", t)
log.Printf("从持久存储建立索引速度每秒添加 %f 百万个索引",
float64(searcher1.NumTokenIndexAdded())/t/(1000000))
}
//os.RemoveAll(*persistent_storage_folder)
}
func search(ch chan bool) {
for i := 0; i < numRepeatQuery; i++ {
for _, query := range searchQueries {
searcher.Search(types.SearchRequest{Text: query})
}
}
ch <- true
}