性能监控之 Telegraf+InfluxDB+Grafana+Python 实现 Oracle 实时监控

2021 年 12 月 10 日
本文字数：10365 字
阅读完需：约 34 分钟

一、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。

二、实现的效果

三、预备知识

1、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$WAITSTAT                     4294950915 VIEW       65537V$BH                           4294951406 VIEW       65537V$GC_ELEMENT                   4294951794 VIEW       65537V$CR_BLOCK_SERVER              4294951796 VIEW       65537V$CURRENT_BLOCK_SERVER         4294952095 VIEW       65537V$POLICY_HISTORY               4294953128 VIEW       65537V$ENCRYPTED_TABLESPACES        4294952996 VIEW       65537V$GC_ELEMENTS_WITH_COLLISIONS  4294951798 VIEW       65537V$FILE_CACHE_TRANSFER          4294951800 VIEW       65537V$TEMP_CACHE_TRANSFER          4294951802 VIEW       65537V$CLASS_CACHE_TRANSFER         4294951804 VIEW       65537V$INSTANCE_CACHE_TRANSFER      4294952151 VIEW       65537V$LOCK_ELEMENT                 4294951408 VIEW       65537V$BSP                          4294951594 VIEW       65537V$LOCKS_WITH_COLLISIONS        4294951410 VIEW       65537V$FILE_PING                    4294951412 VIEW       65537V$TEMP_PING                    4294951532 VIEW       65537V$CLASS_PING                   4294951414 VIEW       65537V$LOCK_ACTIVITY                4294951437 VIEW       65537V$ROWCACHE                     4294950916 VIEW       65537

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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 Oracle 10g 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';

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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 10g Oracle 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/

2、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。

2.1、基本要求

要在 Python 和 Oracle 数据库中使用 cx_Oracle 7，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)

2.2、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

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

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 Oracle Client 安装，可以参考下文：https://cx-oracle.readthedocs.io/en/latest/user_guide/installation.html#installing-cx-oracle-on-linux

四、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

1、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/
Grafanak：https://grafana.com/docs/installation/rpm/

2、具体设置

在 InfluxDB 中创建一个 Telegraf 数据库：

[root@zuozewei ~]# influxConnected to http://localhost:8086 version 1.6.2InfluxDB shell version: 1.6.2> create user "telegraf" with password 'telegraf'> create database telegraf> show databasesname: databasesname----_internaltelegraf

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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()

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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=0oracle_wait_class,fqdn=localhost.localdomain,delphix=none,db=172.16.106.251:1521/orcl,wait_class=CPU wait_value=0.003oracle_wait_class,fqdn=localhost.localdomain,delphix=none,db=172.16.106.251:1521/orcl,wait_class=CPU_OS wait_value=0.778oracle_wait_class,fqdn=localhost.localdomain,delphix=none,db=172.16.106.251:1521/orcl,wait_class=Commit wait_value=0oracle_wait_class,fqdn=localhost.localdomain,delphix=none,db=172.16.106.251:1521/orcl,wait_class=Concurrency wait_value=0.001oracle_wait_class,fqdn=localhost.localdomain,delphix=none,db=172.16.106.251:1521/orcl,wait_class=Configuration wait_value=0oracle_wait_class,fqdn=localhost.localdomain,delphix=none,db=172.16.106.251:1521/orcl,wait_class=Network wait_value=0oracle_wait_class,fqdn=localhost.localdomain,delphix=none,db=172.16.106.251:1521/orcl,wait_class=Other wait_value=0oracle_wait_class,fqdn=localhost.localdomain,delphix=none,db=172.16.106.251:1521/orcl,wait_class=System_I/O wait_value=0.001oracle_wait_class,fqdn=localhost.localdomain,delphix=none,db=172.16.106.251:1521/orcl,wait_class=User_I/O wait_value=0oracle_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=0.122oracle_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=21.595oracle_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=0.001oracle_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=0.001oracle_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=0.081oracle_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=0.268oracle_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=0.716oracle_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=0.076oracle_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

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定义一个 shell 脚本执行 Python 脚本

#!/usr/bin/env bashpython /home/oracle/scripts/oracle_metrics.sh -f "influx" "ALL" "-u" "system" "-p" "xxxx" "-s" "172.16.106.251:1521/orcl"

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

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启动 telegraf：

telegraf -config /etc/telegraf/telegraf.conf

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3、数据可视化

查询 InfluxDB 数据库

[root@localhost log]# influxConnected to http://localhost:8086 version 1.7.4InfluxDB shell version: 1.7.4Enter an InfluxQL query> show databasesname: databasesname----_internaltelegraf> use telegrafUsing database telegraf> show measurementsname: measurementsname----oracle_fra_pctusedoracle_sysmetricoracle_tablespacesoracle_wait_classoracle_wait_event> select * from oracle_sysmetric limit 5name: oracle_sysmetrictime                db                      delphix fqdn                  host                  metric_name                                   metric_value----                --                      ------- ----                  ----                  -----------                                   ------------1554277680000000000 172.16.14.251:1521/orcl none    localhost.localdomain localhost.localdomain Active_Parallel_Sessions                      01554277680000000000 172.16.14.251:1521/orcl none    localhost.localdomain localhost.localdomain Active_Serial_Sessions                        11554277680000000000 172.16.14.251:1521/orcl none    localhost.localdomain localhost.localdomain Average_Active_Sessions                       0.01380294950841554277680000000000 172.16.14.251:1521/orcl none    localhost.localdomain localhost.localdomain Average_Synchronous_Single-Block_Read_Latency 0.58751554277680000000000 172.16.14.251:1521/orcl none    localhost.localdomain localhost.localdomain Background_CPU_Usage_Per_Sec                  0.104149308449>

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Grafana 效果图如下：

五、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。

本文资料：

https://github.com/zuozewei/blog-example/tree/master/Performance-testing/03-performance-monitoring/telegraf-Influxdb-grafana-python-oracle

参考资料：

[1]: https://cx-oracle.readthedocs.io/en/latest/index.html
[2]: http://datavirtualizer.com/wait-event-and-wait-class-metrics-vs-vsystem_event/
[3]: https://docs.influxdata.com/influxdb/v1.7/write_protocols/

发布于: 2 小时前阅读数: 7

原文链接:【http://xie.infoq.cn/article/c3d60b7098525beac98431a9b】。未经作者许可，禁止转载。

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性能监控之 Telegraf+InfluxDB+Grafana+Python 实现 Oracle 实时监控

一、前言

二、实现的效果

三、预备知识

1、Oracle 动态性能视图

2、cx_Oracle

2.1、基本要求

2.2、快速安装

四、解决方案

1、安装

2、具体设置

3、数据可视化

五、小结

zuozewei

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