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：
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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。
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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。
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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：
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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：
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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。
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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。
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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）。
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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）。
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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：
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select
host
from
hosts
where
status=1;
|
查询NVPS的值：
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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：
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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：
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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