性能监控之Telegraf+InfluxDB+Grafana+P

作者: 沉浮在心 | 来源:发表于2019-10-14 21:32 被阅读0次

前言

监控集成选型的 Telegraf 探针，最近需要实现对 Oracle 数据库的做实时监控，查了下 Telegraf 竟然还不支持 Oracle 监控，WTF？于是自己研究了下，通过 Python + SQL 脚本折中解决了，此文去且当作小结。

实现的效果

预备知识

Oracle动态性能视图

动态性能视图属于数据字典，它们的所有者为SYS，并且多数动态性能视图只能由特权用户和DBA用户查询。当数据库处于不同状态时，可以访问的动态性能视图有所不同。启动例程时，ORACLE会自动建立动态性能视图；停止例程时，ORACLE会自动删除动态性能视图。数据字典信息是从数据文件中获得，而动态性能视图信息是从SGA和控制文件取得。所以，两者所反映的信息还是有很大差异的。数据库管理员利用这些动态性能视图，可以了解数据库运行的一些基本信息，为我们进行数据库维护以及数据库性能优化提供一些数据上的支持。所有动态性能视图都是以V_$开始的，Oracle 为每个动态性能视图提供了相应的同义词（V$开头）

通过查询V$FIXED_TABLE,可以列出所有可用的动态性能视图和动态性能表。

SQL> select * from V$FIXED_TABLE where name like 'V$%';

NAME OBJECT_ID TYPE TABLE_NUM

------------------------------ ---------- ----- ----------

V$WAITSTAT 4294950915 VIEW 65537

V$BH 4294951406 VIEW 65537

V$GC_ELEMENT 4294951794 VIEW 65537

V$CR_BLOCK_SERVER 4294951796 VIEW 65537

V$CURRENT_BLOCK_SERVER 4294952095 VIEW 65537

V$POLICY_HISTORY 4294953128 VIEW 65537

V$ENCRYPTED_TABLESPACES 4294952996 VIEW 65537

V$GC_ELEMENTS_WITH_COLLISIONS 4294951798 VIEW 65537

V$FILE_CACHE_TRANSFER 4294951800 VIEW 65537

V$TEMP_CACHE_TRANSFER 4294951802 VIEW 65537

V$CLASS_CACHE_TRANSFER 4294951804 VIEW 65537

V$INSTANCE_CACHE_TRANSFER 4294952151 VIEW 65537

V$LOCK_ELEMENT 4294951408 VIEW 65537

V$BSP 4294951594 VIEW 65537

V$LOCKS_WITH_COLLISIONS 4294951410 VIEW 65537

V$FILE_PING 4294951412 VIEW 65537

V$TEMP_PING 4294951532 VIEW 65537

V$CLASS_PING 4294951414 VIEW 65537

V$LOCK_ACTIVITY 4294951437 VIEW 65537

V$ROWCACHE 4294950916 VIEW 65537

以下是不同类型的指标视图的快速表格比较：

该表的第一行是经典的等待事件和统计视图。以下几行是度量标准视图。度量标准视图是在Oracle10g中引入的。

度量视图计算增量和速率，这极大地简化了解决简单问题的能力，比如 “现在我的数据库的I/O速率是多少?” 这个问题，在10g之前，处理起来出奇的乏味。要回答这个问题，你必须查询v$sysstat，例如:

Select value from v$sysstat where name='physical reads';

但是仅查询一次v$sysstat不能解决问题，而是“自数据库启动以来已完成了多少I / O？”的问题。要回答原始问题，必须两次查询v$sysstat并接受两个值之间的增量：

在时间A取值

在时间B取值

Delta = (B-A)

and/or get Rate = (B-A)/elapsed time

获得这些差值和速率可能是一项艰巨的工作。然后10gOracle引入了度量标准表，这些度量表可以在一个查询中解决问题。

等待事件视图为（系统级别）

V$SYSTEM_EVENT– 自启动以来累积的等待事件

V$EVENTMETRIC- 等待事件增量持续60秒

DBA_HIST_SYSTEM_EVENT– 自启动以来累计的上周按快照（小时）的等待事件

等待事件汇总到称为等待类的组中。对于等待类，有以下视图：

V$SYSTEM_WAIT_CLASS– 自启动以来累积

V$WAITCLASSMETRIC– 持续60秒增量

V$WAITCLASSMETRIC_HISTORY– 最后一小时的60秒增量

注意：DBA_HIST_WAITCLASSMETRIC_HISTORY用于警报或基准，而不是日常值。

其他的就不一一展开了，具体可以参考下文：

http://datavirtualizer.com/wait-event-and-wait-class-metrics-vs-vsystem_event/

cx_Oracle

cx_Oracle 是一个 Python 扩展模块，可以访问 Oracle 数据库。它符合 Python 数据库API 2.0 规范。

基本要求

要在 Python 和 Oracle 数据库中使用cx_Oracle7，需要满足以下条件：

Python 2.7或 3.5 及更高版本。

Oracle 客户端库。

Oracle 数据库。Oracle的标准客户端 - 服务器版本互操作性允许cx_Oracle连接到较旧和较新的数据库。(推荐)

快速安装

在 Linux 上安装 cx_Oracle 的一般方法是使用 Python 的 Pip 包从 PyPI 安装cx_Oracle：

从 PyPI 安装 cx_Oracle：

python -m pip install cx_Oracle --upgrade

将 Oracle 客户端库添加到操作系统库搜索路径，例如 Linux 的 LDLIBRARYPATH

如果你的数据库位于远程计算机上，请下适用于你的操作系统体系结构的免费Oracle Instant Client “Basic” 或 “Basic Light” 包

至于具体的OracleClient安装，可以参考下文：

https://cx-oracle.readthedocs.io/en/latest/user_guide/installation.html#installing-cx-oracle-on-linux

解决方案

Python：收集 Oracle 指标数据

Telegraf：收集 Python 打印的性能指标数据

InfluxDB：存储时间序列 Oracle 性能指标数据

Grafana：可视化 Dashboard

安装

具体的安装可以参考官方文档：

Telegraf：https://docs.influxdata.com/telegraf/v1.12/introduction/installation/

InfluxDB：https://docs.influxdata.com/influxdb/v1.7/introduction/installation/

Grafana：https://grafana.com/docs/installation/rpm/

具体设置

在 InfluxDB 中创建一个 Telegraf 数据库：

[root@zuozewei ~]# influx

Connected to http://localhost:8086 version 1.6.2

InfluxDB shell version: 1.6.2

> create user "telegraf" with password 'telegraf'

> create database telegraf

> show databases

name

----

_internal

telegraf

编写 python+sql 脚本以收集 oracle 指标。脚本的输出内容很重要，必须是 InfluxDB line-protocol。该脚本查询v$ SYSMETRIC和v$eventmetric，获得最后一分钟时，等待类和等待事件指标。

python代码是：

import socket,argparse,subprocess,re,cx_Oracle

fqdn = socket.getfqdn()

class OraStats():

def __init__(self, user, passwd, sid):

self.user = user

self.passwd = passwd

self.sid = sid

self.delengine = "none"

connstr=self.user+'/'+self.passwd+'@'+self.sid

self.connection = cx_Oracle.connect(connstr)

cursor = self.connection.cursor()

cursor.execute("select distinct(SVRNAME) from v$dnfs_servers")

rows = cursor.fetchall()

for i in range(0, cursor.rowcount):

self.dengine_ip = rows[i][0]

proc = subprocess.Popen(["nslookup", self.dengine_ip], stdout=subprocess.PIPE)

lookupresult = proc.communicate()[0].split('\n')

for line in lookupresult:

if 'name=' in re.sub(r'\s', '', line):

self.delengine = re.sub('\..*$', '', re.sub(r'^.*name=', '', re.sub(r'\s', '', re.sub(r'.$', '', line))))

# 等待类别

def waitclassstats(self, user, passwd, sid, format):

cursor = self.connection.cursor()

cursor.execute("""

select n.wait_class, round(m.time_waited/m.INTSIZE_CSEC,3) AAS

from v$waitclassmetric m, v$system_wait_class n

where m.wait_class_id=n.wait_class_id and n.wait_class != 'Idle'

union

select 'CPU', round(value/100,3) AAS

from v$sysmetric where metric_name='CPU Usage Per Sec' and group_id=2

union select 'CPU_OS', round((prcnt.busy*parameter.cpu_count)/100,3) - aas.cpu

from

( select value busy

from v$sysmetric

where metric_name='Host CPU Utilization (%)'

and group_id=2 ) prcnt,

( select value cpu_count from v$parameter where name='cpu_count' ) parameter,

( select 'CPU', round(value/100,3) cpu from v$sysmetric where metric_name='CPU Usage Per Sec' and group_id=2) aas

""")

for wait in cursor:

wait_name = wait[0]

wait_value = wait[1]

print ("oracle_wait_class,fqdn={0},delphix={1},db={2},wait_class={3} wait_value={4}".format(fqdn, self.delengine, sid, re.sub(' ', '_', wait_name), wait_value))

# 系统指标

def sysmetrics(self, user, passwd, sid, format):

cursor = self.connection.cursor()

cursor.execute("""

select METRIC_NAME,VALUE,METRIC_UNIT from v$sysmetric where group_id=2

""")

for metric in cursor:

metric_name = metric[0]

metric_value = metric[1]

print ("oracle_sysmetric,fqdn={0},delphix={1},db={2},metric_name={3} metric_value={4}".format(fqdn,self.delengine,sid,re.sub(' ', '_', metric_name),metric_value))

# 在闪回恢复区中有关磁盘配额和当前磁盘使用情况

def fraused(self, user, passwd, sid, format):

cursor = self.connection.cursor()

cursor.execute("""

select round((SPACE_USED-SPACE_RECLAIMABLE)*100/SPACE_LIMIT,1) from V$RECOVERY_FILE_DEST

""")

for frau in cursor:

fra_used = frau[0]

print ("oracle_fra_pctused,fqdn={0},delphix={1},db={2} fra_pctused={3}".format(fqdn,self.delengine,sid,fra_used))

# 磁盘使用状态

def fsused(self):

fss = ['/oracle', '/data']

for fs in fss:

df = subprocess.Popen(["df","-P",fs], stdout=subprocess.PIPE)

output = df.communicate()[0]

total = re.sub('%','',output.split("\n")[1].split()[1])

used = re.sub('%','',output.split("\n")[1].split()[2])

pctused = re.sub('%','',output.split("\n")[1].split()[4])

print("oracle_fs_pctused,fqdn={0},fs_name={1} oraclefs_pctused={2},oraclefs_alloc={3},oraclefs_used={4}".format(fqdn,fs,pctused,total,used))

# 等待状态

def waitstats(self, user, passwd, sid, format):

cursor = self.connection.cursor()

cursor.execute("""

select /*+ ordered use_hash(n) */

n.wait_class wait_class,

n.name wait_name,

m.wait_count cnt,

nvl(round(10*m.time_waited/nullif(m.wait_count,0),3) ,0) avg_ms

from v$eventmetric m,

v$event_name n

where m.event_id=n.event_id

and n.wait_class <> 'Idle' and m.wait_count > 0 order by 1""")

for wait in cursor:

wait_class = wait[0]

wait_name = wait[1]

wait_cnt = wait[2]

wait_avgms = wait[3]

print ("oracle_wait_event,fqdn={0},delphix={1},db={2},wait_class={3},wait_event={4} count={5},latency={6}".format(fqdn, self.delengine,sid,re.sub(' ', '_', wait_class), re.sub(' ','_',wait_name),wait_cnt,wait_avgms))

# 表空间使用状态

def tbsstats(self, user, passwd, sid, format):

cursor = self.connection.cursor()

cursor.execute("""

select /*+ ordered */ tablespace_name,

round(used_space),

round(max_size-used_space) free_space,

round(max_size),

round(used_space*100/max_size,2) percent_used

from (

select m.tablespace_name,

m.used_space*t.block_size/1024/1024 used_space,

(case when t.bigfile='YES' then power(2,32)*t.block_size/1024/1024

else tablespace_size*t.block_size/1024/1024 end) max_size

from dba_tablespace_usage_metrics m, dba_tablespaces t

where m.tablespace_name=t.tablespace_name)

""")

for tbs in cursor:

tbs_name = tbs[0]

used_space_mb = tbs[1]

free_space_mb = tbs[2]

max_size_mb = tbs[3]

percent_used = tbs[4]

print ("oracle_tablespaces,fqdn={0},delphix={1},db={2},tbs_name={3} used_space_mb={4},free_space_mb={5},percent_used={6},max_size_mb={7}".format(fqdn, self.delengine, sid, re.sub(' ', '_', tbs_name), used_space_mb,free_space_mb,percent_used,max_size_mb))

if __name__ == "__main__":

parser = argparse.ArgumentParser()

parser.add_argument('-f', '--format', help="Output format, default influx", choices=['kafka', 'influx'], default='influx')

subparsers = parser.add_subparsers(dest='stat')

parser_all = subparsers.add_parser('ALL', help="Get all database stats")

parser_all.add_argument('-u', '--user', help="Username with sys views grant", required=True)

parser_all.add_argument('-p', '--passwd', required=True)

parser_all.add_argument('-s', '--sid', help="tnsnames SID to connect", required=True)

args = parser.parse_args()

if args.stat == "ALL":

stats = OraStats(args.user, args.passwd, args.sid)

stats.waitclassstats(args.user, args.passwd, args.sid, args.format)

stats.waitstats(args.user, args.passwd, args.sid, args.format)

stats.sysmetrics(args.user, args.passwd, args.sid, args.format)

stats.tbsstats(args.user, args.passwd, args.sid, args.format)

stats.fraused(args.user, args.passwd, args.sid, args.format)

stats.fsused()

输出格式化为 InfluxDB line-protocol

[root@localhost tools]# ./oracle.sh

oracle_wait_class,fqdn=localhost.localdomain,delphix=none,db=172.16.106.251:1521/orcl,wait_class=Application wait_value=0

oracle_wait_class,fqdn=localhost.localdomain,delphix=none,db=172.16.106.251:1521/orcl,wait_class=CPU wait_value=0.003

oracle_wait_class,fqdn=localhost.localdomain,delphix=none,db=172.16.106.251:1521/orcl,wait_class=CPU_OS wait_value=0.778

oracle_wait_class,fqdn=localhost.localdomain,delphix=none,db=172.16.106.251:1521/orcl,wait_class=Commit wait_value=0

oracle_wait_class,fqdn=localhost.localdomain,delphix=none,db=172.16.106.251:1521/orcl,wait_class=Concurrency wait_value=0.001

oracle_wait_class,fqdn=localhost.localdomain,delphix=none,db=172.16.106.251:1521/orcl,wait_class=Configuration wait_value=0

oracle_wait_class,fqdn=localhost.localdomain,delphix=none,db=172.16.106.251:1521/orcl,wait_class=Network wait_value=0

oracle_wait_class,fqdn=localhost.localdomain,delphix=none,db=172.16.106.251:1521/orcl,wait_class=Other wait_value=0

oracle_wait_class,fqdn=localhost.localdomain,delphix=none,db=172.16.106.251:1521/orcl,wait_class=System_I/O wait_value=0.001

oracle_wait_class,fqdn=localhost.localdomain,delphix=none,db=172.16.106.251:1521/orcl,wait_class=User_I/O wait_value=0

oracle_wait_event,fqdn=localhost.localdomain,delphix=none,db=172.16.106.251:1521/orcl,wait_class=Commit,wait_event=log_file_sync count=2,latency=0.122

oracle_wait_event,fqdn=localhost.localdomain,delphix=none,db=172.16.106.251:1521/orcl,wait_class=Concurrency,wait_event=os_thread_startup count=2,latency=21.595

oracle_wait_event,fqdn=localhost.localdomain,delphix=none,db=172.16.106.251:1521/orcl,wait_class=Network,wait_event=SQL*Net_message_to_client count=17,latency=0.001

oracle_wait_event,fqdn=localhost.localdomain,delphix=none,db=172.16.106.251:1521/orcl,wait_class=Other,wait_event=asynch_descriptor_resize count=4,latency=0.001

oracle_wait_event,fqdn=localhost.localdomain,delphix=none,db=172.16.106.251:1521/orcl,wait_class=System_I/O,wait_event=db_file_parallel_write count=2,latency=0.081

oracle_wait_event,fqdn=localhost.localdomain,delphix=none,db=172.16.106.251:1521/orcl,wait_class=System_I/O,wait_event=control_file_parallel_write count=24,latency=0.268

oracle_wait_event,fqdn=localhost.localdomain,delphix=none,db=172.16.106.251:1521/orcl,wait_class=System_I/O,wait_event=control_file_sequential_read count=71,latency=0.716

oracle_wait_event,fqdn=localhost.localdomain,delphix=none,db=172.16.106.251:1521/orcl,wait_class=System_I/O,wait_event=log_file_parallel_write count=7,latency=0.076

oracle_wait_event,fqdn=localhost.localdomain,delphix=none,db=172.16.106.251:1521/orcl,wait_class=User_I/O,wait_event=Disk_file_operations_I/O count=16,laten

定义一个 shell 脚本执行 Python 脚本

#!/usr/bin/env bash

python /home/oracle/scripts/oracle_metrics.sh -f "influx" "ALL" "-u" "system" "-p" "xxxx" "-s" "172.16.106.251:1521/orcl"

在 oracle主机上，配置 telegraf 以60秒的间隔执行 python sh，然后将输出发送到 InfluxDB。编辑/etc/telegraf/telegraf.conf配置文件：

# Telegraf configuration

# Telegraf is entirely plugin driven. All metrics are gathered from the

# declared inputs, and sent to the declared outputs.

# Plugins must be declared in here to be active.

# To deactivate a plugin, comment out the name and any variables.

# Use 'telegraf -config telegraf.conf -test' to see what metrics a config

# file would generate.

# Global tags can be specified here in key="value" format.

[global_tags]

# dc = "us-east-1" # will tag all metrics with dc=us-east-1

# rack = "1a"

host="Dprima"

collector="telegraf"

# Configuration for telegraf agent

[agent]

## Default data collection interval for all inputs

interval = "10s"

## Rounds collection interval to 'interval'

## ie, if interval="10s" then always collect on :00, :10, :20, etc.

round_interval = true

## Telegraf will cache metric_buffer_limit metrics for each output, and will

## flush this buffer on a successful write.

metric_buffer_limit = 10000

## Flush the buffer whenever full, regardless of flush_interval.

flush_buffer_when_full = true

## Collection jitter is used to jitter the collection by a random amount.

## Each plugin will sleep for a random time within jitter before collecting.

## This can be used to avoid many plugins querying things like sysfs at the

## same time, which can have a measurable effect on the system.

collection_jitter = "0s"

## Default flushing interval for all outputs. You shouldn't set this below

## interval. Maximum flush_interval will be flush_interval + flush_jitter

flush_interval = "60s"

## Jitter the flush interval by a random amount. This is primarily to avoid

## large write spikes for users running a large number of telegraf instances.

## ie, a jitter of 5s and interval 10s means flushes will happen every 10-15s

flush_jitter = "0s"

## Run telegraf in debug mode

debug = false

## Run telegraf in quiet mode

quiet = false

## Override default hostname, if empty use os.Hostname()

hostname = "Dprima"

###############################################################################

# OUTPUTS #

###############################################################################

# Configuration for influxdb server to send metrics to

[[outputs.influxdb]]

urls = ["http://influxgraf:8086"] # required

database = "telegraf" # required

precision = "s"

timeout = "5s"

[[outputs.influxdb]]

urls = ["http://localhost:9092"] # required

database = "kapacitor" # required

precision = "s"

retention_policy = "default"

timeout = "5s"

#[[outputs.file]]

# files=["/home/oracle/scripts/telegraf_debug.txt"]

###############################################################################

# INPUTS #

###############################################################################

# Oracle metrics

[[inputs.exec]]

# Shell/commands array

commands = ["/home/oracle/scripts/oracle_metrics.sh"]

# Data format to consume. This can be "json", "influx" or "graphite" (line-protocol)

# NOTE json only reads numerical measurements, strings and booleans are ignored.

data_format = "influx"

interval = "60s"

###############################################################################

# SERVICE INPUTS #

###############################################################################

启动 telegraf：

telegraf -config /etc/telegraf/telegraf.conf

数据可视化

查询 InfluxDB 数据库

[root@localhost log]# influx

Connected to http://localhost:8086 version 1.7.4

InfluxDB shell version: 1.7.4

Enter an InfluxQL query

> show databases

name

----

_internal

telegraf

> use telegraf

Using database telegraf

> show measurements

name

----

oracle_fra_pctused

oracle_sysmetric

oracle_tablespaces

oracle_wait_class

oracle_wait_event

> select * from oracle_sysmetric limit 5

time db delphix fqdn host metric_name metric_value

---- -- ------- ---- ---- ----------- ------------

1554277680000000000 172.16.14.251:1521/orcl none localhost.localdomain localhost.localdomain Active_Parallel_Sessions 0

1554277680000000000 172.16.14.251:1521/orcl none localhost.localdomain localhost.localdomain Active_Serial_Sessions 1

1554277680000000000 172.16.14.251:1521/orcl none localhost.localdomain localhost.localdomain Average_Active_Sessions 0.0138029495084

1554277680000000000 172.16.14.251:1521/orcl none localhost.localdomain localhost.localdomain Average_Synchronous_Single-Block_Read_Latency 0.5875

1554277680000000000 172.16.14.251:1521/orcl none localhost.localdomain localhost.localdomain Background_CPU_Usage_Per_Sec 0.104149308449

>

Grafana 效果图如下：

小结

通过结合 Python 脚本开发的方式，我们可以扩展部分 Telegraf 不支持的监控项，本文简单提供了一种思路。

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本文标题：性能监控之Telegraf+InfluxDB+Grafana+P

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