人的一生一般会有七次机会。你只需要抓住其中的一两次机会,一下子就能拉开跟同龄人之间的距离,甚至改变人生方向、改变命运。
一、基础
- 适合MongoDB的场景 - 无需要跨文档或跨表的事务及复杂的join查询支持
- 敏捷迭代的业务,需求变动频繁,数据模型无法确定- 如游戏玩家数据
 
- 存储的数据格式灵活,不固定,或属于半结构化数据
- 业务并发访问量大,需数千的QPS
- TB级以上的海量数据存储,且数据量不断增加
- 要求存储的数据持久化、不丢失
- 需要99.999%的数据高可用性
- 需要大量的地理位置查询、文本查询- 游戏、电商、社交、视频直播、物流、监控、日志数据存储,第三方信息抓取、地图、打车、外卖等
 
 
- 安装MongoDB,省略 - 笔者安装目录:/usr/local/mongodb-4.2.5
 
- 笔者安装目录:
- 运行 - cd /usr/local/mongodb-4.2.5 &&./bin/mongod -f 27017.conf- 27017.conf - 1 
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 8- #笔者使用了复制集模式,通过开启27017、27018、27019三个端口实现 
 dbpath = /usr/local/mongodb-4.2.5/data/27017
 logpath = /usr/local/mongodb-4.2.5/logs/27017/mongo.log
 port = 27017
 fork = true
 logappend=true
 replSet = my_replset
 
- 查看运行状态 - ps -ef|grep mongo- 1 - 501 32276 1 0 5:39下午 ?? 0:10.03 ./bin/mongod -f 27017.conf 
- TPCC事务:TPCC是TPC组织联合Oracle、IBM、思科等企业制定的单机事务数据库测试基准。它模拟了一个仓储物流的业务场景,包括新建订单、付款、发货、订单查询、库存查询五个事务操作。执行TPCC测试程序,将会得到被测系统的吞吐量、时延、事务完成数等信息。 
二、使用
- sysbench - 克隆代码: - git clone https://github.com/tmcallaghan/sysbench-mongodb.git mongo-sysbench
- 切换目录: - cd mongo-sysbench
- 安装依赖 - wget https://oss.sonatype.org/content/repositories/releases/org/mongodb/mongo-java-driver/3.9.1/mongo-java-driver-3.9.1.jar
- wget https://oss.sonatype.org/content/repositories/releases/org/mongodb/mongodb-driver-core/3.9.1/mongodb-driver-core-3.9.1.jar
- wget https://oss.sonatype.org/content/repositories/releases/org/mongodb/mongodb-driver-legacy/3.9.1/mongodb-driver-legacy-3.9.1.jar
 
- 修改配置文件 - config.bash,注掉了用户名和密码- 1 
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 8- # database username on DB_NAME 
 #export USERNAME=<replace-with-username>
 # database password to use for USERNAME
 #export PASSWORD=<replace-with-password>
 # name of the server to connect to
 export MONGO_SERVER=127.0.0.1
- 执行测试 - ./run.simple.bash- 1 
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 26- 2021年11月27日 星期六 17时54分18秒 CST | sysbench benchmark duration = 00:00:00:30 
 ************************************************************************
 final interval(s)
 ************************************************************************
 Thread[main,5,main] auto commit = Y
 Thread[main,5,main] run seconds = 600
 Thread[main,5,main] oltp range size = 100
 Thread[main,5,main] oltp point selects = 10
 Thread[main,5,main] oltp simple ranges = 1
 Thread[main,5,main] oltp sum ranges = 1
 Thread[main,5,main] oltp order ranges = 1
 Thread[main,5,main] oltp distinct ranges = 1
 Thread[main,5,main] oltp index updates = 1
 Thread[main,5,main] oltp non index updates = 1
 Thread[main,5,main] oltp inserts = 1
 Thread[main,5,main] write concern = ACKNOWLEDGED
 Thread[main,5,main] maximum tps (global) = 999999
 Thread[main,5,main] maximum tps (per thread) = 31250
 Thread[main,5,main] Server:Port = 127.0.0.1:27017
 Thread[main,5,main] seed = 1638006795
 Thread[main,5,main] userName =
 Thread[main,5,main] read preference = secondaryPreferred
 Thread[main,5,main] use SSL = false
 2021年11月27日 星期六 17时54分18秒 CST | sysbench benchmark duration = 00:00:00:30
- 可通过调整配置文件 - config.bash里的参数多次验证
- 可自定义脚本进行测试 
 
- YCSB:cat mongodb-binding/README.md,查看使用方法 - 安装MongoDB并启动服务 
- 安装Java 
- 安装mvn - brew install mvn
 
- 下载源码包,笔者用curl较慢,wget较快 - curl -O --location https://github.com/brianfrankcooper/YCSB/releases/download/0.17.0/ycsb-0.17.0.tar.gz
- wget https://github.com/brianfrankcooper/YCSB/releases/download/0.17.0/ycsb-0.17.0.tar.gz
 
- mkdir mongo-ycsb
- 解压文件 - tar -zxvf ycsb-0.17.0.tar.gz -C mongo-ycsb
- cd mongo-ycsb/ycsb-0.17.0 - ./bin/ycsb load mongodb-async -s -P workloads/workloada > outputLoad.txt - 1 
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 5- Loading workload... 
 Starting test.
 2021-11-28 01:02:51:219 0 sec: 0 operations; est completion in 0 second
 DBWrapper: report latency for each error is false and specific error codes to track for latency are: []
 2021-11-28 01:02:51:356 0 sec: 0 operations; est completion in 106751991167300 days 15 hours [CLEANUP: Count=1, Max=999, Min=999, Avg=999, 90=999, 99=999, 99.9=999, 99.99=999] [INSERT: Count=0, Max=0, Min=9223372036854775807, Avg=NaN, 90=0, 99=0, 99.9=0, 99.99=0] [INSERT-FAILED: Count=1, Max=89535, Min=89472, Avg=89504, 90=89535, 99=89535, 99.9=89535, 99.99=89535]
- ./bin/ycsb run mongodb-async -s -P workloads/workloada > outputRun.txt - 1 
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 5- Loading workload... 
 Starting test.
 2021-11-28 01:01:04:933 0 sec: 0 operations; est completion in 0 second
 DBWrapper: report latency for each error is false and specific error codes to track for latency are: []
 2021-11-28 01:01:05:477 0 sec: 1000 operations; 1838.24 current ops/sec; [READ: Count=496, Max=3859, Min=92, Avg=247.48, 90=335, 99=772, 99.9=3859, 99.99=3859] [CLEANUP: Count=1, Max=1193, Min=1193, Avg=1193, 90=1193, 99=1193, 99.9=1193, 99.99=1193] [UPDATE: Count=504, Max=106751, Min=209, Avg=669.33, 90=611, 99=1188, 99.9=9151, 99.99=106751]
 
 
- mongo-perf - git clone https://github.com/mongodb/mongo-perf.git
- cd mongo-perf
- pip install -r requirements.txt
- testcases有各种测试脚本,当然也可以根据需求自定义脚本 - python benchrun.py -f testcases/simple_insert.js -t 1 2 4
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 605- MongoDB shell version v4.0.11 
 connecting to: mongodb://localhost:27017/?gssapiServiceName=mongodb
 Implicit session: session { "id" : UUID("d364c43c-6a62-4576-99c8-ffb57db0e798") }
 MongoDB server version: 4.2.5
 WARNING: shell and server versions do not match
 db version: 4.2.5
 2261279b51ea13df08ae708ff278f0679c59dc32
 load('util/utils.js');
 load('util/docGenerators.js');
 load('testcases/simple_insert.js');
 mongoPerfRunTests([1, 2, 4], 1, 1, 5, 1, "%", [], 0, {"writeCmdMode": "true", "readCmdMode": "false", "writeConcern": {"j": "false"}}, false, false, false, {"traceOnly": false});
 Insert.Empty
 1 7269.969787553751
 2 11636.676242500396
 4 15145.821655075235
 Insert.EmptyCapped
 1 6178.765014942947
 2 9150.603016602348
 4 9791.203774341779
 Insert.EmptyCapped.SeqIntID
 1 5579.4225743621355
 2 8780.241197661215
 4 9466.785694439503
 Insert.JustID
 1 6453.887723781281
 2 12039.786947622359
 4 16016.953457184602
 Insert.IntVector
 1 717.5318343558479
 2 961.691778284588
 4 1115.8261508892645
 Insert.SeqIntID.Indexed
 1 6108.172264291902
 2 9288.215849655635
 4 13964.509173907272
 Insert.IntIDUpsert
 1 5083.715985604563
 2 9069.28052532995
 4 12185.743531658685
 Insert.JustNum
 1 6654.262064448619
 2 11584.422657189818
 4 16059.032638414492
 Insert.JustNumIndexed
 1 6211.335337140367
 2 10886.082883453479
 4 14292.314880578622
 InsertIndexedStringsSimpleCollation
 1 6285.506950441219
 2 9731.579107866964
 4 12697.789255975225
 InsertIndexedStringsNonSimpleCollation
 1 6327.584862114689
 2 9951.564032732394
 4 13156.144294716169
 Insert.UniqueIndex
 1 5571.34526527612
 2 9236.483711087776
 4 12684.164055158411
 Insert.UniqueIndexCompound
 1 5861.723296677158
 2 9692.254573277096
 4 12662.311170272338
 Insert.UniqueIndexCompoundReverse
 1 5804.876936608945
 2 8765.051039724734
 4 13390.150569004967
 Insert.LargeDocVector
 1 425.33101130996556
 2 605.821724914963
 4 709.6603909879481
 Finished Testing.
 {
 "errors": [
 0
 ],
 "end": "2021-11-27T17:28:22.165Z",
 "results": [
 {
 "name": "Insert.Empty",
 "results": {
 "1": {
 "ops_per_sec": 7269.969787553751,
 "ops_per_sec_values": [
 7269.969787553751
 ],
 "error_values": [
 0
 ]
 },
 "start": "2021-11-27T17:23:37.815Z",
 "2": {
 "ops_per_sec": 11636.676242500396,
 "ops_per_sec_values": [
 11636.676242500396
 ],
 "error_values": [
 0
 ]
 },
 "end": "2021-11-27T17:23:55.410Z",
 "4": {
 "ops_per_sec": 15145.821655075235,
 "ops_per_sec_values": [
 15145.821655075235
 ],
 "error_values": [
 0
 ]
 }
 }
 },
 {
 "name": "Insert.EmptyCapped",
 "results": {
 "1": {
 "ops_per_sec": 6178.765014942947,
 "ops_per_sec_values": [
 6178.765014942947
 ],
 "error_values": [
 0
 ]
 },
 "start": "2021-11-27T17:23:55.410Z",
 "2": {
 "ops_per_sec": 9150.603016602348,
 "ops_per_sec_values": [
 9150.603016602348
 ],
 "error_values": [
 0
 ]
 },
 "end": "2021-11-27T17:24:13.360Z",
 "4": {
 "ops_per_sec": 9791.203774341779,
 "ops_per_sec_values": [
 9791.203774341779
 ],
 "error_values": [
 0
 ]
 }
 }
 },
 {
 "name": "Insert.EmptyCapped.SeqIntID",
 "results": {
 "1": {
 "ops_per_sec": 5579.4225743621355,
 "ops_per_sec_values": [
 5579.4225743621355
 ],
 "error_values": [
 0
 ]
 },
 "start": "2021-11-27T17:24:13.360Z",
 "2": {
 "ops_per_sec": 8780.241197661215,
 "ops_per_sec_values": [
 8780.241197661215
 ],
 "error_values": [
 0
 ]
 },
 "end": "2021-11-27T17:24:30.739Z",
 "4": {
 "ops_per_sec": 9466.785694439503,
 "ops_per_sec_values": [
 9466.785694439503
 ],
 "error_values": [
 0
 ]
 }
 }
 },
 {
 "name": "Insert.JustID",
 "results": {
 "1": {
 "ops_per_sec": 6453.887723781281,
 "ops_per_sec_values": [
 6453.887723781281
 ],
 "error_values": [
 0
 ]
 },
 "start": "2021-11-27T17:24:30.739Z",
 "2": {
 "ops_per_sec": 12039.786947622359,
 "ops_per_sec_values": [
 12039.786947622359
 ],
 "error_values": [
 0
 ]
 },
 "end": "2021-11-27T17:24:48.510Z",
 "4": {
 "ops_per_sec": 16016.953457184602,
 "ops_per_sec_values": [
 16016.953457184602
 ],
 "error_values": [
 0
 ]
 }
 }
 },
 {
 "name": "Insert.IntVector",
 "results": {
 "1": {
 "ops_per_sec": 717.5318343558479,
 "ops_per_sec_values": [
 717.5318343558479
 ],
 "error_values": [
 0
 ]
 },
 "start": "2021-11-27T17:24:48.510Z",
 "2": {
 "ops_per_sec": 961.691778284588,
 "ops_per_sec_values": [
 961.691778284588
 ],
 "error_values": [
 0
 ]
 },
 "end": "2021-11-27T17:25:07.409Z",
 "4": {
 "ops_per_sec": 1115.8261508892645,
 "ops_per_sec_values": [
 1115.8261508892645
 ],
 "error_values": [
 0
 ]
 }
 }
 },
 {
 "name": "Insert.SeqIntID.Indexed",
 "results": {
 "1": {
 "ops_per_sec": 6108.172264291902,
 "ops_per_sec_values": [
 6108.172264291902
 ],
 "error_values": [
 0
 ]
 },
 "start": "2021-11-27T17:25:07.409Z",
 "2": {
 "ops_per_sec": 9288.215849655635,
 "ops_per_sec_values": [
 9288.215849655635
 ],
 "error_values": [
 0
 ]
 },
 "end": "2021-11-27T17:25:28.502Z",
 "4": {
 "ops_per_sec": 13964.509173907272,
 "ops_per_sec_values": [
 13964.509173907272
 ],
 "error_values": [
 0
 ]
 }
 }
 },
 {
 "name": "Insert.IntIDUpsert",
 "results": {
 "1": {
 "ops_per_sec": 5083.715985604563,
 "ops_per_sec_values": [
 5083.715985604563
 ],
 "error_values": [
 0
 ]
 },
 "start": "2021-11-27T17:25:28.503Z",
 "2": {
 "ops_per_sec": 9069.28052532995,
 "ops_per_sec_values": [
 9069.28052532995
 ],
 "error_values": [
 0
 ]
 },
 "end": "2021-11-27T17:25:46.102Z",
 "4": {
 "ops_per_sec": 12185.743531658685,
 "ops_per_sec_values": [
 12185.743531658685
 ],
 "error_values": [
 0
 ]
 }
 }
 },
 {
 "name": "Insert.JustNum",
 "results": {
 "1": {
 "ops_per_sec": 6654.262064448619,
 "ops_per_sec_values": [
 6654.262064448619
 ],
 "error_values": [
 0
 ]
 },
 "start": "2021-11-27T17:25:46.102Z",
 "2": {
 "ops_per_sec": 11584.422657189818,
 "ops_per_sec_values": [
 11584.422657189818
 ],
 "error_values": [
 0
 ]
 },
 "end": "2021-11-27T17:26:03.679Z",
 "4": {
 "ops_per_sec": 16059.032638414492,
 "ops_per_sec_values": [
 16059.032638414492
 ],
 "error_values": [
 0
 ]
 }
 }
 },
 {
 "name": "Insert.JustNumIndexed",
 "results": {
 "1": {
 "ops_per_sec": 6211.335337140367,
 "ops_per_sec_values": [
 6211.335337140367
 ],
 "error_values": [
 0
 ]
 },
 "start": "2021-11-27T17:26:03.679Z",
 "2": {
 "ops_per_sec": 10886.082883453479,
 "ops_per_sec_values": [
 10886.082883453479
 ],
 "error_values": [
 0
 ]
 },
 "end": "2021-11-27T17:26:23.326Z",
 "4": {
 "ops_per_sec": 14292.314880578622,
 "ops_per_sec_values": [
 14292.314880578622
 ],
 "error_values": [
 0
 ]
 }
 }
 },
 {
 "name": "InsertIndexedStringsSimpleCollation",
 "results": {
 "1": {
 "ops_per_sec": 6285.506950441219,
 "ops_per_sec_values": [
 6285.506950441219
 ],
 "error_values": [
 0
 ]
 },
 "start": "2021-11-27T17:26:23.326Z",
 "2": {
 "ops_per_sec": 9731.579107866964,
 "ops_per_sec_values": [
 9731.579107866964
 ],
 "error_values": [
 0
 ]
 },
 "end": "2021-11-27T17:26:42.433Z",
 "4": {
 "ops_per_sec": 12697.789255975225,
 "ops_per_sec_values": [
 12697.789255975225
 ],
 "error_values": [
 0
 ]
 }
 }
 },
 {
 "name": "InsertIndexedStringsNonSimpleCollation",
 "results": {
 "1": {
 "ops_per_sec": 6327.584862114689,
 "ops_per_sec_values": [
 6327.584862114689
 ],
 "error_values": [
 0
 ]
 },
 "start": "2021-11-27T17:26:42.433Z",
 "2": {
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 "storageEngine": "wiredTiger",
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- py-tpcc - git clone https://github.com/apavlo/py-tpcc.git mongo-tpcc 
- cd mongo-tpcc/pytpcc 
- python tpcc.py –print-config mongodb > mongodb.config - 报错ImportError: No module named pymongo
- pip install pymongo- Requirement already satisfied: pymongo in /Library/Frameworks/Python.framework/Versions/3.8/lib/python3.8/site-packages (2.7.2)
 
- 多Python版本导致的
- 查看自默认安装路径python -m site- /Users/xxxx/Library/Python/2.7/lib/python/site-packages
 
- 重新安装并指定位置pip install pymongo --target=/Users/xxxx/Library/Python/2.7/lib/python/site-packages/
- 重新运行python tpcc.py --print-config mongodb > mongodb.config
 
- 报错
- python tpcc.py --config=mongodb.config mongodb- 1 
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 17- 11-28-2021 02:05:22 [<module>:234] INFO : Initializing TPC-C benchmark using MongodbDriver 
 11-28-2021 02:05:22 [<module>:244] INFO : Loading TPC-C benchmark data using MongodbDriver
 11-28-2021 02:12:01 [loadFinish:354] INFO : Finished loading tables
 11-28-2021 02:12:01 [execute:056] INFO : Executing benchmark for 60 seconds
 ==================================================================
 Data Loading Time: 398 seconds
 Execution Results after 60 seconds
 ------------------------------------------------------------------
 Executed Time (µs) Rate
 DELIVERY 63 10632275.8198 5.93 txn/s
 NEW_ORDER 745 23894075.6321 31.18 txn/s
 ORDER_STATUS 79 1405402.66037 56.21 txn/s
 PAYMENT 788 21150436.6398 37.26 txn/s
 STOCK_LEVEL 70 2821108.1028 24.81 txn/s
 ------------------------------------------------------------------
 TOTAL 1745 59903298.8548 29.13 txn/s