如何从Zabbix数据库中获取监控数据
做过Zabbix的同学都知道，Zabbix通过专用的Agent或者SNMP收集相关的监控数据，然后存储到数据库里面实时在前台展示。Zabbix监控数据主要分为以下两类：
历史数据：history相关表,从history_uint表里面可以查询到设备监控项目的最大，最小和平均值,即存储监控数据的原始数据。
趋势数据：trends相关表,趋势数据是经过Zabbix计算的数据，数据是从history_uint里面汇总的，从trends_uint可以查看到监控数据每小时最大，最小和平均值，即存储监控数据的汇总数据。
Zabbix可以通过两种方式获取历史数据：
1.通过Zabbix前台获取历史数据
通过Zabbix前台查看历史数据非常简单，可以通过检测中->最新数据 的方式查看。也可以点击右上角的As plain test按钮保存成文本文件。
2.通过前台获取的数据进行处理和二次查询有很多限制，因此可以通过SQL语句直接从后台DB查询数据。
首先大家应该熟悉SQL语句Select 常用用法：
| 1 2 3 4 5 6 7 | SELECT [ ALL | DISTINCT ] Select_List [ INTO [New_Table_name] FROM { Table_name | View_name} [ [,{table2_name | view2_name} [,...] ] [ WHERE Serch_conditions ] [ GROUP BY Group_by_list ] [ HAVING Serch_conditions ] [ ORDER BY Order_list [ ASC | DEsC ] ] |
说明：
1)SELECT子句指定要查询的特定表中的列，它可以是*，表达式，列表等。
2)INTO子句指定要生成新的表。
3)FROM子句指定要查询的表或者视图。
4)WHERE子句用来限定查询的范围和条件。
5)GROUP BY子句指定分组查询子句。
6)HAVING子句用于指定分组子句的条件。
7)ORDER BY可以根据一个或者多个列来排序查询结果，在该子句中，既可以使用列名，也可以使用相对列号，ASC表示升序，DESC表示降序。
8）mysql聚合函数：sum()，count()，avg()，max()，avg()等都是聚合函数，当我们在用聚合函数的时候，一般都要用到GROUP BY 先进行分组，然后再进行聚合函数的运算。运算完后就要用到Having子句进行判断了,例如聚合函数的值是否大于某一个值等等。
从Zabbix数据库中查询监控项目方法,这里已查询主机的网卡流量为例子：
1）通过hosts表查找host的ID。
| 1 2 3 4 5 6 7 | mysql> select host,hostid from hosts where host= "WWW05" ; + -------+--------+ | host | hostid | + -------+--------+ | WWW05 | 10534 | + -------+--------+ 1 row in set (0.00 sec) |
2）通过items表查找主的监控项和key以及itemid。
| 1 2 3 4 5 6 7 | mysql> select itemid, name ,key_ from items where hostid=10534 and key_= "net.if.out[eth0]" ; + --------+-----------------+------------------+ | itemid | name | key_ | + --------+-----------------+------------------+ | 58860 | 发送流量： | net.if. out [eth0] | + --------+-----------------+------------------+ 1 row in set (0.00 sec) |
3）通过itemid查询主机的监控项目（history_uint或者trends_uint)，单位为M。
主机流入流量：
| 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | mysql> select from_unixtime(clock) as DateTime,round(value/1024/1024,2) as Traffic_in from history_uint where itemid= "58855" and from_unixtime(clock)>= ‘2014-09-20‘ and from_unixtime(clock)< ‘2014-09-21‘ limit 20; + ---------------------+------------+ | DateTime | Traffic_in | + ---------------------+------------+ | 2014-09-20 00:00:55 | 0.10 | | 2014-09-20 00:01:55 | 0.09 | | 2014-09-20 00:02:55 | 0.07 | | 2014-09-20 00:03:55 | 0.05 | | 2014-09-20 00:04:55 | 0.03 | | 2014-09-20 00:05:55 | 0.06 | | 2014-09-20 00:06:55 | 0.12 | | 2014-09-20 00:07:55 | 0.05 | | 2014-09-20 00:08:55 | 0.10 | | 2014-09-20 00:09:55 | 0.10 | | 2014-09-20 00:10:55 | 0.12 | | 2014-09-20 00:11:55 | 0.12 | | 2014-09-20 00:12:55 | 0.13 | | 2014-09-20 00:13:55 | 3.16 | | 2014-09-20 00:14:55 | 0.23 | | 2014-09-20 00:15:55 | 0.24 | | 2014-09-20 00:16:55 | 0.26 | | 2014-09-20 00:17:55 | 0.23 | | 2014-09-20 00:18:55 | 0.14 | | 2014-09-20 00:19:55 | 0.16 | + ---------------------+------------+ 20 rows in set (0.82 sec) |
主机流出流量：
| 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | mysql> select from_unixtime(clock) as DateTime,round(value/1024/1024,2) as Traffic_out from history_uint where itemid= "58860" and from_unixtime(clock)>= ‘2014-09-20‘ and from_unixtime(clock)< ‘2014-09-21‘ limit 20; + ---------------------+-------------+ | DateTime | Traffic_out | + ---------------------+-------------+ | 2014-09-20 00:00:00 | 4.13 | | 2014-09-20 00:01:00 | 3.21 | | 2014-09-20 00:02:00 | 2.18 | | 2014-09-20 00:03:01 | 1.61 | | 2014-09-20 00:04:00 | 1.07 | | 2014-09-20 00:05:00 | 0.92 | | 2014-09-20 00:06:00 | 1.23 | | 2014-09-20 00:07:00 | 2.76 | | 2014-09-20 00:08:00 | 1.35 | | 2014-09-20 00:09:00 | 3.11 | | 2014-09-20 00:10:00 | 2.99 | | 2014-09-20 00:11:00 | 2.68 | | 2014-09-20 00:12:00 | 2.55 | | 2014-09-20 00:13:00 | 2.89 | | 2014-09-20 00:14:00 | 4.98 | | 2014-09-20 00:15:00 | 6.56 | | 2014-09-20 00:16:00 | 7.34 | | 2014-09-20 00:17:00 | 6.81 | | 2014-09-20 00:18:00 | 7.67 | | 2014-09-20 00:19:00 | 4.11 | + ---------------------+-------------+ 20 rows in set (0.74 sec) |
4）如果是两台设备，汇总流量，假如公司出口有两台设备，可以用下面的SQL语句汇总每天的流量。下面SQL语句是汇总上面主机网卡的进出流量的。
| 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | mysql> select from_unixtime(clock, "%Y-%m-%d %H:%i" ) as DateTime, sum (round(value/1024/1024,2)) as Traffic_total from history_uint where itemid in (58855,58860) and from_unixtime(clock)>= ‘2014-09-20‘ and from_unixtime(clock)< ‘2014-09-21‘ group by from_unixtime(clock, "%Y-%m-%d %H:%i" ) limit 20; + ------------------+---------------+ | DateTime | Traffic_total | + ------------------+---------------+ | 2014-09-20 00:00 | 4.23 | | 2014-09-20 00:01 | 3.30 | | 2014-09-20 00:02 | 2.25 | | 2014-09-20 00:03 | 1.66 | | 2014-09-20 00:04 | 1.10 | | 2014-09-20 00:05 | 0.98 | | 2014-09-20 00:06 | 1.35 | | 2014-09-20 00:07 | 2.81 | | 2014-09-20 00:08 | 1.45 | | 2014-09-20 00:09 | 3.21 | | 2014-09-20 00:10 | 3.11 | | 2014-09-20 00:11 | 2.80 | | 2014-09-20 00:12 | 2.68 | | 2014-09-20 00:13 | 6.05 | | 2014-09-20 00:14 | 5.21 | | 2014-09-20 00:15 | 6.80 | | 2014-09-20 00:16 | 7.60 | | 2014-09-20 00:17 | 7.04 | | 2014-09-20 00:18 | 7.81 | | 2014-09-20 00:19 | 4.27 | + ------------------+---------------+ 20 rows in set (1.52 sec) |
5)查询一天中主机流量的最大值，最小值和平均值。
| 1 2 3 4 5 6 7 | mysql> select date as DateTime,round( min (traffic)/2014/1024,2) as TotalMinIN,round( avg (traffic)/1024/1024,2) as TotalAvgIN,round( max (traffic)/1024/1024,2) as TotalMaxIN from ( select from_unixtime(clock, "%Y-%m-%d" ) as date , sum (value) as traffic from history_uint where itemid in (58855,58860) and from_unixtime(clock)>= ‘2014-09-20‘ and from_unixtime(clock)< ‘2014-09-21‘ group by from_unixtime(clock, "%Y-%m-%d %H:%i" ) ) tmp; + ------------+------------+------------+------------+ | DateTime | TotalMinIN | TotalAvgIN | TotalMaxIN | + ------------+------------+------------+------------+ | 2014-09-20 | 0.01 | 4.63 | 191.30 | + ------------+------------+------------+------------+ 1 row in set (1.74 sec) |
6）查询主机组里面所有主机CPU Idle平均值（原始值）。
| 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | mysql> select from_unixtime(hi.clock, "%Y-%m-%d %H:%i" ) as DateTime,g. name as Group_Name,h.host as Host, hi.value as Cpu_Avg_Idle from hosts_groups as hg join groups g on g.groupid = hg.groupid join items i on hg.hostid = i.hostid join hosts h on h.hostid=i.hostid join history hi on i.itemid = hi.itemid where g. name = ‘上海机房--项目测试‘ and i.key_= ‘system.cpu.util[,idle]‘ and from_unixtime(clock)>= ‘2014-09-24‘ and from_unixtime(clock)< ‘2014-09-25‘ group by h.host,from_unixtime(hi.clock, "%Y-%m-%d %H:%i" ) limit 10; + ------------------+----------------------------+----------+--------------+ | DateTime | Group_Name | Host | Cpu_Avg_Idle | + ------------------+----------------------------+----------+--------------+ | 2014-09-24 00:02 | 上海机房 --项目测试 | testwb01 | 94.3960 | | 2014-09-24 00:07 | 上海机房 --项目测试 | testwb01 | 95.2086 | | 2014-09-24 00:12 | 上海机房 --项目测试 | testwb01 | 95.4308 | | 2014-09-24 00:17 | 上海机房 --项目测试 | testwe01 | 95.4580 | | 2014-09-24 00:22 | 上海机房 --项目测试 | testwb01 | 95.4611 | | 2014-09-24 00:27 | 上海机房 --项目测试 | testwb01 | 95.2939 | | 2014-09-24 00:32 | 上海机房 --项目测试 | testwb01 | 96.0896 | | 2014-09-24 00:37 | 上海机房 --项目测试 | testwb01 | 96.5286 | | 2014-09-24 00:42 | 上海机房 --项目测试 | testwb01 | 96.8086 | | 2014-09-24 00:47 | 上海机房 --项目测试 | testwb01 | 96.6854 | + ------------------+----------------------------+----------+--------------+ 10 rows in set (0.75 sec) |
7)查询主机组里面所有主机CPU Idle平均值（汇总值）。
| 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | mysql> select from_unixtime(hi.clock, "%Y-%m-%d %H:%i" ) as Date ,g. name as Group_Name,h.host as Host, hi.value_avg as Cpu_Avg_Idle from hosts_groups as hg join groups g on g.groupid = hg.groupid join items i on hg.hostid = i.hostid join hosts h on h.hostid=i.hostid join trends hi on i.itemid = hi.itemid where g. name = ‘上海机房--项目测试‘ and i.key_= ‘system.cpu.util[,idle]‘ and from_unixtime(clock)>= ‘2014-09-10‘ and from_unixtime(clock)< ‘2014-09-11‘ group by h.host,from_unixtime(hi.clock, "%Y-%m-%d %H:%i" ) limit 10; + ------------------+----------------------------+----------+--------------+ | Date | Group_Name | Host | Cpu_Avg_Idle | + ------------------+----------------------------+----------+--------------+ | 2014-09-10 00:00 | 上海机房 --项目测试 | testwb01 | 99.9826 | | 2014-09-10 01:00 | 上海机房 --项目测试 | testwb01 | 99.9826 | | 2014-09-10 02:00 | 上海机房 --项目测试 | testwb01 | 99.9825 | | 2014-09-10 03:00 | 上海机房 --项目测试 | testwb01 | 99.9751 | | 2014-09-10 04:00 | 上海机房 --项目测试 | testwb01 | 99.9843 | | 2014-09-10 05:00 | 上海机房 --项目测试 | testwb01 | 99.9831 | | 2014-09-10 06:00 | 上海机房 --项目测试 | testwb01 | 99.9829 | | 2014-09-10 07:00 | 上海机房 --项目测试 | testwb01 | 99.9843 | | 2014-09-10 08:00 | 上海机房 --项目测试 | testwb01 | 99.9849 | | 2014-09-10 09:00 | 上海机房 --项目测试 | testwb01 | 99.9849 | + ------------------+----------------------------+----------+--------------+ 10 rows in set (0.01 sec) |
8）其它与Zabbix相关的SQL语句。
查询主机已经添加但没有开启监控主机：
| 1 | select host from hosts where status=1; |
查询NVPS的值：
| 1 2 3 4 5 6 7 | mysql> SELECT round( SUM (1.0/i.delay),2) AS qps FROM items i,hosts h WHERE i.status= ‘0‘ AND i.hostid=h.hostid AND h.status= ‘0‘ AND i.delay<>0; + --------+ | qps | + --------+ | 503.40 | + --------+ 1 row in set (0.11 sec) |
查询IDC机房的资产信息：
| 1 2 3 4 5 6 7 8 | mysql> select name ,os,tag,hardware from host_inventory where hostid in ( select hostid from hosts_groups where groupid=69) limit 2; + -------+----------------------------+------+-------------------+ | name | os | tag | hardware | + -------+----------------------------+------+-------------------+ | SHDBM | CentOS release 5.2 (Final) | i686 | ProLiant DL360 G5 | | SHDBS | CentOS release 5.2 (Final) | i686 | ProLiant DL360 G5 | + -------+----------------------------+------+-------------------+ 2 rows in set (0.00 sec) |
查询Zabbix interval分布情况：
| 1 2 3 4 5 6 7 8 9 10 11 12 13 | mysql> select delay, count (*),concat(round( count (*) / ( select count (*) from items where status=0)*100,2), "%" ) as percent from items where status=0 group by delay order by 2 desc ; + -------+----------+---------+ | delay | count (*) | percent | + -------+----------+---------+ | 3600 | 41168 | 38.92% | | 300 | 35443 | 33.51% | | 600 | 16035 | 15.16% | | 60 | 12178 | 11.51% | | 0 | 902 | 0.85% | | 36000 | 46 | 0.04% | | 30 | 1 | 0.00% | + -------+----------+---------+ 7 rows in set (0.68 sec) |
总结：通过SQL语句可以查询出任何监控项目的数据，并且在SQL语句的末尾通过into outfile ‘/tmp/zabbix_result.txt‘直接把查询的结果保存到系统上面,方便后续操作.
引用:http://www.xici.net/d221092545.html
