【OceanBase DBA早下班系列】—— 性能问题如何 “拍CT“ (一键获取火焰图和扁鹊图)

2024-06-14 01:28

本文主要是介绍【OceanBase DBA早下班系列】—— 性能问题如何 “拍CT“ (一键获取火焰图和扁鹊图),希望对大家解决编程问题提供一定的参考价值,需要的开发者们随着小编来一起学习吧!

1. 前言

最近接连遇到几个客户的环境在排查集群性能问题,总结了一下,直接教大家如何去获取火焰图、扁鹊图(调用关系图),直击要害,就像是内脏的疾病去医院看病,上来先照一个CT,通过分析CT,大概的毛病也就定位的七七八八了。

2. 火焰图/扁鹊图一键收集

2.1. 步骤一:安装部署obdiag

参考文档: OceanBase分布式数据库-海量数据 笔笔算数

安装obdiag并配置被诊断集群信息(~/.obdiag/config.yml),说明:obdiag 是一款25MB大小的针对OceanBase的黑屏命令行的诊断小工具,功能强大,部署简单。

sudo yum install -y yum-utils
sudo yum-config-manager --add-repo https://mirrors.aliyun.com/oceanbase/OceanBase.repo
sudo yum install -y oceanbase-diagnostic-tool
source /usr/local/oceanbase-diagnostic-tool/init.sh# 配置被诊断集群信息
obdiag config -hxx.xx.xx.xx -uroot@sys -Pxxxx -p*****

2.2. 步骤二:一键收集火焰图/扁鹊图

obdiag gather perf

收集过程如图:

1718261610

解压之后的结果

$tree
.
├── flame.data # 火焰图的数据,后面会用到
├── flame.viz
├── sample.data
├── sample.viz # 扁鹊图的数据,后面会用到
└── top.txt

2.3. 步骤三:将火焰图/扁鹊图数据可视化

git clone https://github.com/brendangregg/FlameGraph.git# 将上面采集到的flame.viz数据经过两次处理,就可以火焰图
./FlameGraph/stackcollapse-perf.pl flame.viz | ./FlameGraph/flamegraph.pl - > perf.svg

火焰图:

1718268132

扁鹊图

perfdata2graph.py

#!/usr/bin/pythonimport sys
import os
import subprocess
import datetimeclass Edge:def __init__(self):self.count = 0self.to = Noneself.label = Noneself.penwidth = 1self.weight = 1.self.color = "#000000"class Node:def __init__(self):self.identify = ""self.name = ""self.count = 0self.self_count = 0self.id = Noneself.label = Noneself.color = "#F8F8F8"self.edges = {}def __str__(self):return "id: %s, name: %s, count %s, edges %s" % (self.id, self.name, self.count, len(self.edges))class PerfToGraph:def __init__(self, fmt = "svg", node_drop_pct = 1., edge_drop_pct = None):self.fmt = fmtself.all_nodes = {}self.samples = 1self.s100 = 100.self.node_drop_pct = node_drop_pctself.edge_drop_pct = edge_drop_pctself.next_edge_color = 0if edge_drop_pct is None:self.edge_drop_pct = node_drop_pct / 5.self.node_drop_cnt = 0self.edge_drop_cnt = 0self.colors = [(0.02, "#FAFAF0"),(0.2, "#FAFAD2"),(1.0, "#F9EBB6"),(2.0, "#F9DB9B"),(3.0, "#F8CC7F"),(5.0, "#F7BC63"),(7.0, "#FF8B01"),(9.0, "#FA6F01"),(12.0, "#F55301"),(15.0, "#F03801"),(19.0, "#EB1C01"),(23.0, "#E60001")]self.edge_colors = ["#FF8B01","#EB1C01","#DC92EF","#9653B8","#66B031","#D9CA0C","#BDBDBD","#696969","#113866","#5CBFAC","#1120A8","#960144","#EA52B2"]def convert(self):self.read_stdin()self.formalize()self.output()def set_pen_width(self, e):pct = e.count * 100. / self.samplesif pct > 10:e.penwidth = 3 + min(pct, 100) * 2. / 100elif pct > 1:e.penwidth = 1 + pct * 2. / 10else:e.penwidth = 1def set_edge_weight(self, e):e.weight = e.count * 100. / self.samplesif e.weight > 100:e.weight = 100elif e.weight > 10:e.weight = 10 + e.weight / 10.def set_edge_color(self, e):i = self.next_edge_colorself.next_edge_color += 1e.color = self.edge_colors[i % len(self.edge_colors)];def set_node_color(self, n):v = n.self_count / self.s100for p in self.colors:if v >= p[0]:n.color = p[1]def get_node(self, identify, name):if self.all_nodes.has_key(identify):return self.all_nodes[identify]n = Node()n.identify = identifyn.name = nameself.all_nodes[identify] = nreturn ndef add_edge(self, f, t):if f.edges.has_key(t.identify):e = f.edges[t.identify]e.count += 1else:e = Edge()e.to = te.count = 1f.edges[t.identify] = edef read_stdin(self):# $ escape not needed?cmd = "sed -e 's/<.*>//g' -e 's/ (.*$//' -e 's/+0x.*//g' -e '/^[^\t]/d' -e 's/^\s*//'"sub = subprocess.Popen(cmd, stdout=subprocess.PIPE, shell = True)prev = Noneself.samples = 1for l in sub.stdout:l = l.strip()if (not l) and (not prev):# avoding continous empty linescontinuetmp = l.split(' ')addr = tmp[0]name = (" ".join(tmp[1:])).strip()if '[unknown]' == name:name = addrif not l:addr = 'fake_addr'name = '::ALL::'# we use name to identify nodesn = self.get_node(name, name)if prev == n:continuen.count += 1if prev:self.add_edge(n, prev)prev = nif not l:self.samples += 1prev = Nonedef formalize(self):self.s100 = self.samples / 100.self.node_drop_cnt = self.samples * self.node_drop_pct / 100self.edge_drop_cnt = self.samples * self.edge_drop_pct / 100i = 0;for n in self.all_nodes.values():n.id = "n%s" % (i)i+=1n.self_count = n.count - sum([x.count for x in n.edges.values()])n.label = "%s\\nTotal: %.2f%% | Call: %.2f%%\\nSelf: %.2f%%(%s)" % (n.name.replace("::", "\\n"), n.count/self.s100, (n.count - n.self_count)/self.s100, n.self_count/self.s100, n.self_count)self.set_node_color(n)for e in n.edges.values():e.label = "%.2f%%" % (e.count/self.s100)self.set_pen_width(e)self.set_edge_weight(e)self.set_edge_color(e)def to_dot(self):out = []out.append("""digraph call_graph_for_perf_data {style = "perf.css";node [shape = box, style=filled ];""")out.append('note [ label = "%s\\nTotal samples: %d\\nDrop nodes with <= %.2f%%(%d)\\nDrop edges with <= %.2f%%(%d)", fillcolor="#00AFFF" ];' % (datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S'), self.samples, self.node_drop_pct, int(self.node_drop_cnt), self.edge_drop_pct, int(self.edge_drop_cnt)))for n in self.all_nodes.values():if n.count <= self.node_drop_cnt:continueout.append('%s [ label = "%s", tooltip = "%s", fillcolor="%s"];' % (n.id, n.label, n.name, n.color))for n in self.all_nodes.values():if n.count <= self.node_drop_cnt:continuefor e in n.edges.values():if e.count <= self.edge_drop_cnt or e.to.count <= self.node_drop_cnt:continuetip = 'edgetooltip = "%s ==> %s", labeltooltip = "%s ==> %s"' % (n.name, e.to.name, n.name, e.to.name)out.append('%s -> %s [ penwidth = %.2f, weight = %f, color = "%s", label = "%s", fontcolor = "%s", %s ];' % (n.id, e.to.id, e.penwidth, e.weight, e.color, e.label, e.color, tip))out.append("}")return "\n".join(out)def output(self):if "dot" == self.fmt:print self.to_dot()elif "svg" == self.fmt:cmd = "dot -T svg"sub = subprocess.Popen(cmd, stdin=subprocess.PIPE, shell = True)dot = self.to_dot()sub.communicate(input = dot)elif "top" == self.fmt:try:for n in sorted(self.all_nodes.values(), key = lambda n : n.self_count, reverse = True):print "%s %.2f%%" % (n.name, n.self_count/self.s100)except:passif __name__ == "__main__":support_fmt = { "svg" : None, "dot" : None, "top" : None }if len(sys.argv) < 2 or (not support_fmt.has_key(sys.argv[1])):print "%s dot/svg/top [node_drop_perent] [edge_drop_percent]" % (sys.argv[0])sys.exit(1)fmt = sys.argv[1]nd_pct = len(sys.argv) > 2 and float(sys.argv[2]) or 1.0ed_pct = len(sys.argv) > 3 and float(sys.argv[3]) or 0.2c = PerfToGraph(fmt, nd_pct, ed_pct)c.convert()

# 生成扁鹊图
cat sample.viz | ./perfdata2graph.py svg sample.svg

1718268035

3. obdiag 一键收集火焰图和扁鹊图原理

其实obdiag收集信息是依赖于远端ob节点上的perf工具,所以务必要在ob节点上安装perf工具。相当于obdiag帮你去各个节点上执行了如下命令:

# 注意:-p 后面是进程ID,改成你要 perf 的进程## 生成调用图(扁鹊图)
sudo perf record -e cycles -c 100000000 -p 87741 -g -- sleep 20
sudo perf script -F ip,sym -f > sample.viz## 生成火焰图
sudo perf record -F 99 -p 87741 -g -- sleep 20
sudo perf script > flame.viz

感兴趣的可以通过obdiag gather perf -v 查看详细的obdiag 日志,通过日志你就能大概知道obdiag的执行过程了。

4. 附录

  • obdiag 下载地址: OceanBase分布式数据库-海量数据 笔笔算数
  • obdiag 官方文档: OceanBase分布式数据库-海量数据 笔笔算数
  • obdiag github地址:  GitHub - oceanbase/obdiag: obdiag (OceanBase Diagnostic Tool) is designed to help OceanBase users quickly gather necessary information and analyze the root cause of the problem.
  • obdiag SIG 营地: 诊断工具 · OceanBase 技术交流

这篇关于【OceanBase DBA早下班系列】—— 性能问题如何 “拍CT“ (一键获取火焰图和扁鹊图)的文章就介绍到这儿,希望我们推荐的文章对编程师们有所帮助!



http://www.chinasem.cn/article/1058985

相关文章

Springboot3统一返回类设计全过程(从问题到实现)

《Springboot3统一返回类设计全过程(从问题到实现)》文章介绍了如何在SpringBoot3中设计一个统一返回类,以实现前后端接口返回格式的一致性,该类包含状态码、描述信息、业务数据和时间戳,... 目录Spring Boot 3 统一返回类设计:从问题到实现一、核心需求:统一返回类要解决什么问题?

springboot的controller中如何获取applicatim.yml的配置值

《springboot的controller中如何获取applicatim.yml的配置值》本文介绍了在SpringBoot的Controller中获取application.yml配置值的四种方式,... 目录1. 使用@Value注解(最常用)application.yml 配置Controller 中

maven异常Invalid bound statement(not found)的问题解决

《maven异常Invalidboundstatement(notfound)的问题解决》本文详细介绍了Maven项目中常见的Invalidboundstatement异常及其解决方案,文中通过... 目录Maven异常:Invalid bound statement (not found) 详解问题描述可

C++,C#,Rust,Go,Java,Python,JavaScript的性能对比全面讲解

《C++,C#,Rust,Go,Java,Python,JavaScript的性能对比全面讲解》:本文主要介绍C++,C#,Rust,Go,Java,Python,JavaScript性能对比全面... 目录编程语言性能对比、核心优势与最佳使用场景性能对比表格C++C#RustGoJavapythonjav

idea粘贴空格时显示NBSP的问题及解决方案

《idea粘贴空格时显示NBSP的问题及解决方案》在IDEA中粘贴代码时出现大量空格占位符NBSP,可以通过取消勾选AdvancedSettings中的相应选项来解决... 目录1、背景介绍2、解决办法3、处理完成总结1、背景介绍python在idehttp://www.chinasem.cna粘贴代码,出

SpringBoot整合Kafka启动失败的常见错误问题总结(推荐)

《SpringBoot整合Kafka启动失败的常见错误问题总结(推荐)》本文总结了SpringBoot项目整合Kafka启动失败的常见错误,包括Kafka服务器连接问题、序列化配置错误、依赖配置问题、... 目录一、Kafka服务器连接问题1. Kafka服务器无法连接2. 开发环境与生产环境网络不通二、序

SpringSecurity中的跨域问题处理方案

《SpringSecurity中的跨域问题处理方案》本文介绍了跨域资源共享(CORS)技术在JavaEE开发中的应用,详细讲解了CORS的工作原理,包括简单请求和非简单请求的处理方式,本文结合实例代码... 目录1.什么是CORS2.简单请求3.非简单请求4.Spring跨域解决方案4.1.@CrossOr

nacos服务无法注册到nacos服务中心问题及解决

《nacos服务无法注册到nacos服务中心问题及解决》本文详细描述了在Linux服务器上使用Tomcat启动Java程序时,服务无法注册到Nacos的排查过程,通过一系列排查步骤,发现问题出在Tom... 目录简介依赖异常情况排查断点调试原因解决NacosRegisterOnWar结果总结简介1、程序在

CPython与PyPy解释器架构的性能测试结果对比

《CPython与PyPy解释器架构的性能测试结果对比》Python解释器的选择对应用程序性能有着决定性影响,CPython以其稳定性和丰富的生态系统著称;而PyPy作为基于JIT(即时编译)技术的替... 目录引言python解释器架构概述CPython架构解析PyPy架构解析架构对比可视化性能基准测试测

解决java.util.RandomAccessSubList cannot be cast to java.util.ArrayList错误的问题

《解决java.util.RandomAccessSubListcannotbecasttojava.util.ArrayList错误的问题》当你尝试将RandomAccessSubList... 目录Java.util.RandomAccessSubList cannot be cast to java.