使用ganglia监控mongodb数据库collection的增长

    同事有个需求，需要监控mongodb数据库中某一个collection的数据增长情况，原因是由于有定时任务不断往数据库里填充数据，如果定时任务挂掉了可以及时重启任务，保证数据的准确性。其实也可以监控定时任务的执行情况，之后再研究。
    跟博客：使用ganglia监控mongodb集群   文章介绍的一样，使用python脚本来扩展，所以也就不多说，直接上传脚本代码
1. 创建mongodb_collection.pyconf脚本（collection根据情况换成表名）

# mongodb_collection.pyconf
modules {
    module {
        name = "mongodb_EPGInfo_www"    #EPGInfo表示数据库名，www表示collection的名字
        language = "python"
        param total_count{
            value = "/opt/mongodb/bin/mongo --host 10.9.201.190 --port 27017 EPGInfo --quiet --eval 'printjson(db.().count())'"            #语句的作用是获得www表中的记录数
        }
    }
}
collection_group {
    collect_every = 30
    time_threshold = 90
    metric {
        name = "www_count_total"
        title = "Total Count"
    }
    metric {
        name = "www_count_insert"
        title = "Insert per Sec"
    }
}

    具体说明看代码中的注释
2. 创建mongodb_collection.py脚本

#!/usr/bin/env python

import os
import json
import string
import time
import copy
import re

PARAMS = {
    "total_count" : "/opt/mongodb/bin/mongo --host 10.9.201.190 --port 27017 EPGInfo --quiet --eval 'printjson(db.().count())'"
}

NAME_PREFIX = 'www_'

METRICS = {
    'time' : 0,
    'data' : {}
}

LAST_METRICS = copy.deepcopy(METRICS)
METRICS_CACHE_TTL = 3

def get_metrics():
    """Return all metrics"""
    global METRICS, LAST_METRICS
    if (time.time() - METRICS['time']) > METRICS_CACHE_TTL:
        metrics = {}
    # get raw metric data
    o = os.popen(PARAMS['total_count'])
    # clean up
    metrics_str = ''.join(o.readlines()).strip() # convert to string
    metrics_str = re.sub('\w+\((.*)\)', r"\1", metrics_str) # remove functions

    metrics['count_total']=float(json.loads(metrics_str))     #增加监控字典
    metrics['count_insert']=metrics['count_total']            #增加监控字典
    # update cache
    LAST_METRICS = copy.deepcopy(METRICS)
    METRICS = {
        'time': time.time(),
        'data': metrics
    }
    print(METRICS)
    return [METRICS, LAST_METRICS]

def get_value(name):
    """Return a value for the requested metric"""
    # get metrics
    metrics = get_metrics()[0]
    print(metrics)
    # get value
    name = name[len(NAME_PREFIX):] # remove prefix from name
    try:
        result = metrics['data'][name]
    except StandardError:
        result = 0
    return result

def get_rate(name):
    """Return change over time for the requested metric"""
    # get metrics
    [curr_metrics, last_metrics] = get_metrics()
    # get rate
    name = name[len(NAME_PREFIX):] # remove prefix from name
    try:
        rate = float(curr_metrics['data'][name] - last_metrics['data'][name]) / \
        float(curr_metrics['time'] - last_metrics['time'])
        if rate < 0:
            rate = float(0)
    except StandardError:
        rate = float(0)
    return rate

def get_total_count(name):
    total_count = get_value(name)
    return total_count

def get_count_insert(name):
    count_insert = get_rate(name)
    return count_insert

def metric_init(lparams):
    global PARAMS

    # set parameters
    for key in lparams:
        PARAMS[key] = lparams[key]

    # define descriptors
    time_max = 60
    groups = 'EPGInfo_www'
    descriptors = [
        {
            'name': NAME_PREFIX + 'count_total',
            'call_back': get_total_count,
            'time_max': time_max,
            'value_type': 'float',
            'units': 'Total',
            'slope': 'both',
            'format': '%f',
            'description': 'Total Count',
            'groups': groups
        },
        {
            'name': NAME_PREFIX + 'count_insert',
            'call_back': get_count_insert,
            'time_max': time_max,
            'value_type': 'float',
            'units': 'Inserts/Sec',
            'slope': 'both',
            'format': '%f',
            'description': 'Insert per Sec',
            'groups': groups
        }
    ]
    return descriptors

def metric_cleanup():
    pass

if __name__ == '__main__':
    descriptors = metric_init(PARAMS)
    while True:
        for d in descriptors:
            print (('%s = %s') % (d['name'], d['format'])) % (d['call_back'](d['name']))
        print ''
        time.sleep(METRICS_CACHE_TTL)

    具体说明看代码中的注释