【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)

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：

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：

扁鹊图

perfdata2graph.py

#!/usr/bin/python

import sys
import os
import subprocess
import datetime

class Edge:
  def __init__(self):
    self.count = 0
    self.to = None
    self.label = None
    self.penwidth = 1
    self.weight = 1.
    self.color = "#000000"

class Node:
  def __init__(self):
    self.identify = ""
    self.name = ""
    self.count = 0
    self.self_count = 0
    self.id = None
    self.label = None
    self.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 = fmt
    self.all_nodes = {}
    self.samples = 1
    self.s100 = 100.
    self.node_drop_pct = node_drop_pct
    self.edge_drop_pct = edge_drop_pct
    self.next_edge_color = 0
    if edge_drop_pct is None:
      self.edge_drop_pct = node_drop_pct / 5.
    self.node_drop_cnt = 0
    self.edge_drop_cnt = 0
    self.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.samples
    if pct > 10:
      e.penwidth = 3 + min(pct, 100) * 2. / 100
    elif pct > 1:
      e.penwidth = 1 + pct * 2. / 10
    else:
      e.penwidth = 1

  def set_edge_weight(self, e):
    e.weight = e.count * 100. / self.samples
    if e.weight > 100:
      e.weight = 100
    elif e.weight > 10:
      e.weight = 10 + e.weight / 10.

  def set_edge_color(self, e):
    i = self.next_edge_color
    self.next_edge_color += 1
    e.color = self.edge_colors[i % len(self.edge_colors)];

  def set_node_color(self, n):
    v = n.self_count / self.s100
    for 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 = identify
    n.name = name
    self.all_nodes[identify] = n
    return n


  def add_edge(self, f, t):
    if f.edges.has_key(t.identify):
      e = f.edges[t.identify]
      e.count += 1
    else:
      e = Edge()
      e.to = t
      e.count = 1
      f.edges[t.identify] = e

  def 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 = None
    self.samples = 1
    for l in sub.stdout:
      l = l.strip()
      if (not l) and (not prev):
        # avoding continous empty lines
        continue
      tmp = l.split(' ')
      addr = tmp[0]
      name = (" ".join(tmp[1:])).strip()
      if '[unknown]' == name:
        name = addr
      if not l:
        addr = 'fake_addr'
        name = '::ALL::'
      # we use name to identify nodes
      n = self.get_node(name, name)
      if prev == n:
        continue
      n.count += 1
      if prev:
        self.add_edge(n, prev)
      prev = n

      if not l:
        self.samples += 1
        prev = None

  def formalize(self):
    self.s100 = self.samples / 100.
    self.node_drop_cnt = self.samples * self.node_drop_pct / 100
    self.edge_drop_cnt = self.samples * self.edge_drop_pct / 100

    i = 0;
    for n in self.all_nodes.values():
      n.id = "n%s" % (i)
      i+=1
      n.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:
        continue
      out.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:
        continue
      for e in n.edges.values():
        if e.count <= self.edge_drop_cnt or e.to.count <= self.node_drop_cnt:
          continue
        tip = '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:
        pass

if __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 1.0
  ed_pct = len(sys.argv) > 3 and float(sys.argv[3]) or 0.2
  c = PerfToGraph(fmt, nd_pct, ed_pct)
  c.convert()
 
# 生成扁鹊图
cat sample.viz | ./perfdata2graph.py svg sample.svg

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