网络延迟对事务的影响

1.背景概述

最近在做数据同步测试,需要通过DTS将kafka中的数据同步到数据库中,4G的数据量同步到数据库用了大约4个多小时,这看起来并不合理;此时查看数据库所在主机的CPU,IO的使用率都不高,没有瓶颈;最后通过排查发现由于kafka,DTS,数据库不再同一个机房,网络延迟较大,导致同步速率缓慢;

将kafka,DTS,数据库部署到同一个机房后,同步速度明显提升,只需要15分钟就能同步完。

2.问题复现

本次测试通过sysbench在不同网络延迟的情况下,进行数据写入及性能压测,对比网络延迟对数据库事务的影响。

2.1 查看当前网络延迟

$ ping 192.168.137.162
PING 192.168.137.162 (192.168.137.162) 56(84) bytes of data.
64 bytes from 192.168.137.162: icmp_seq=1 ttl=64 time=0.299 ms
64 bytes from 192.168.137.162: icmp_seq=2 ttl=64 time=0.180 ms
64 bytes from 192.168.137.162: icmp_seq=3 ttl=64 time=0.297 ms
64 bytes from 192.168.137.162: icmp_seq=4 ttl=64 time=0.329 ms
64 bytes from 192.168.137.162: icmp_seq=5 ttl=64 time=0.263 ms
64 bytes from 192.168.137.162: icmp_seq=6 ttl=64 time=0.367 ms
64 bytes from 192.168.137.162: icmp_seq=7 ttl=64 time=0.237 ms
64 bytes from 192.168.137.162: icmp_seq=8 ttl=64 time=0.160 ms
64 bytes from 192.168.137.162: icmp_seq=9 ttl=64 time=0.180 ms
64 bytes from 192.168.137.162: icmp_seq=10 ttl=64 time=0.257 ms

当前2台主机在同一个机房,网络延迟大约在 0.3ms 左右

2.2 (正常延迟)通过sysbench写入数据

2.2.1 创建一张表写入500W条数据

$ time sysbench lua/oltp_read_write.lua --mysql-db=sysbench --mysql-host=192.168.137.162 --mysql-port=3307 --mysql-user=root --mysql-password=greatdb --tables=1 --table_size=5000000 --report-interval=2 --threads=10 --time=600 --mysql-ignore-errors=all prepare
sysbench 1.1.0-df89d34 (using bundled LuaJIT 2.1.0-beta3)
Initializing worker threads...
Creating table 'sbtest1'...
Inserting 5000000 records into 'sbtest1'
Creating a secondary index on 'sbtest1'...
 
real1m56.459s
user0m7.187s
sys0m0.400s

写入 500w 数据量耗时 1m56s

2.2.2 sysbench 压测3分钟

SQL statistics:
 queries performed:
​ read: 1711374
​ write: 488964
​ other: 244482
​ total: 2444820
 transactions: 122241 (407.37 per sec.)
 queries: 2444820 (8147.45 per sec.)
 ignored errors: 0 (0.00 per sec.)
 reconnects: 0 (0.00 per sec.)
Throughput:
 events/s (eps): 407.3725
 time elapsed: 300.0718s
 total number of events: 122241
Latency (ms):
​ min: 10.68
​ avg: 122.72
​ max: 1267.88
​ 95th percentile: 502.20
​ sum: 15000894.94
Threads fairness:
 events (avg/stddev): 2444.8200/14.99
 execution time (avg/stddev): 300.0179/0.02

可以看到 TPS:407.37 QPS:8147.45

2.3通过tc命令模拟网络延迟

tc命令是Linux系统中的一个网络管理工具,用于配置和管理网络流量控制。它可以用来限制网络带宽、延迟、丢包等,以及实现QoS(Quality of Service)等功能。

# 对ens3网卡进行延迟设置,设置延迟为10ms
tc qdisc add dev ens3 root netem delay 10ms

如果在使用tc命令时报错如下错误,可以升级一下内核模块

# 报错
tc qdisc add dev ens3 root netem delay 10ms
Error: Specified qdisc not found.
# 升级
$ yum install kernel-modules-extra*
# 重启主机
$ reboot

2.4查看当前网络延迟

$ ping 192.168.137.162
PING 192.168.137.162 (192.168.137.162) 56(84) bytes of data.
64 bytes from 192.168.137.162: icmp_seq=1 ttl=64 time=10.5 ms
64 bytes from 192.168.137.162: icmp_seq=2 ttl=64 time=10.4 ms
64 bytes from 192.168.137.162: icmp_seq=3 ttl=64 time=10.5 ms
64 bytes from 192.168.137.162: icmp_seq=4 ttl=64 time=10.4 ms
64 bytes from 192.168.137.162: icmp_seq=5 ttl=64 time=10.4 ms
64 bytes from 192.168.137.162: icmp_seq=6 ttl=64 time=10.4 ms
64 bytes from 192.168.137.162: icmp_seq=7 ttl=64 time=10.4 ms
64 bytes from 192.168.137.162: icmp_seq=8 ttl=64 time=10.5 ms
64 bytes from 192.168.137.162: icmp_seq=9 ttl=64 time=10.5 ms
64 bytes from 192.168.137.162: icmp_seq=10 ttl=64 time=10.2 ms

网络延迟大约为 10ms

2.3 (延迟10ms)通过sysbench写入数据

2.3.1 创建一张表写入500W条数据

$ time sysbench lua/oltp_read_write.lua --mysql-db=sysbench --mysql-host=192.168.137.162 --mysql-port=3307 --mysql-user=root --mysql-password=greatdb --tables=1 --table_size=5000000 --report-interval=2 --threads=10 --time=600 --mysql-ignore-errors=all prepare
sysbench 1.1.0-df89d34 (using bundled LuaJIT 2.1.0-beta3)
Initializing worker threads...
Creating table 'sbtest1'...
Inserting 5000000 records into 'sbtest1'
Creating a secondary index on 'sbtest1'...
real2m11.656s
user0m7.314s
sys0m0.470s

写入 500w 数据量耗时 2m11s

2.3.2 sysbench 压测3分钟

SQL statistics:
 queries performed:
 read: 788214
 write: 225204
 other: 112602
 total: 1126020
 transactions: 56301 (187.41 per sec.)
 queries: 1126020 (3748.16 per sec.)
 ignored errors: 0 (0.00 per sec.)
 reconnects: 0 (0.00 per sec.)
Throughput:
 events/s (eps): 187.4079
 time elapsed: 300.4196s
 total number of events: 56301
Latency (ms):
 min: 210.14
 avg: 266.68
 max: 493.91
 95th percentile: 419.45
 sum: 15014235.80
Threads fairness:
 events (avg/stddev): 1126.0200/1.16
 execution time (avg/stddev): 300.2847/0.16

可以看到 TPS:187.41 QPS:3748.16

3.总结

通过上面的测试可以看出网络延迟较大时,对数据的写入及每秒执行的事务数都有较大影响;如果需要做性能测试及数据同步,尽量将压测工具或同步工具部署在同一个机房,避免网络延迟较大,对测试结果有影响。


Enjoy GreatSQL 😃

关于 GreatSQL

GreatSQL是适用于金融级应用的国内自主开源数据库,具备高性能、高可靠、高易用性、高安全等多个核心特性,可以作为MySQL或Percona Server的可选替换,用于线上生产环境,且完全免费并兼容MySQL或Percona Server。

相关链接: GreatSQL社区GiteeGitHubBilibili

GreatSQL社区:

社区博客有奖征稿详情:https://greatsql.cn/thread-100-1-1.html

技术交流群:

微信:扫码添加GreatSQL社区助手微信好友,发送验证信息加群

作者:GreatSQL原文地址:https://www.cnblogs.com/greatsql/p/18098189

%s 个评论

要回复文章请先登录注册