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）
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# mongodb_collection.pyconf
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modules {
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module {
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name = "mongodb_EPGInfo_www" #EPGInfo表示数据库名，www表示collection的名字
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language = "python"
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param total_count{
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value = "/opt/mongodb/bin/mongo --host 10.9.201.190 --port 27017 EPGInfo --quiet --eval ‘printjson(db.www.find().count())‘" #语句的作用是获得www表中的记录数
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}
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}
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}
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collection_group {
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collect_every = 30
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time_threshold = 90
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metric {
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name = "www_count_total"
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title = "Total Count"
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}
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metric {
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name = "www_count_insert"
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title = "Insert per Sec"
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}
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}
具体说明看代码中的注释
2. 创建mongodb_collection.py脚本
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#!/usr/bin/env python
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import os
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import json
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import string
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import time
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import copy
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import re
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PARAMS = {
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"total_count" : "/opt/mongodb/bin/mongo --host 10.9.201.190 --port 27017 EPGInfo --quiet --eval ‘printjson(db.www.find().count())‘"
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}
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NAME_PREFIX = ‘www_‘
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METRICS = {
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‘time‘ : 0,
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‘data‘ : {}
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}
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LAST_METRICS = copy.deepcopy(METRICS)
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METRICS_CACHE_TTL = 3
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def get_metrics():
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"""Return all metrics"""
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global METRICS, LAST_METRICS
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if (time.time() - METRICS[‘time‘]) > METRICS_CACHE_TTL:
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metrics = {}
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# get raw metric data
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o = os.popen(PARAMS[‘total_count‘])
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# clean up
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metrics_str = ‘‘.join(o.readlines()).strip() # convert to string
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metrics_str = re.sub(‘\w+\((.*)\)‘, r"\1", metrics_str) # remove functions
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metrics[‘count_total‘]=float(json.loads(metrics_str)) #增加监控字典
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metrics[‘count_insert‘]=metrics[‘count_total‘] #增加监控字典
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# update cache
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LAST_METRICS = copy.deepcopy(METRICS)
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METRICS = {
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‘time‘: time.time(),
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‘data‘: metrics
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}
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print(METRICS)
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return [METRICS, LAST_METRICS]
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def get_value(name):
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"""Return a value for the requested metric"""
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# get metrics
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metrics = get_metrics()[0]
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print(metrics)
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# get value
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name = name[len(NAME_PREFIX):] # remove prefix from name
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try:
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result = metrics[‘data‘][name]
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except StandardError:
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result = 0
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return result
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def get_rate(name):
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"""Return change over time for the requested metric"""
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# get metrics
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[curr_metrics, last_metrics] = get_metrics()
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# get rate
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name = name[len(NAME_PREFIX):] # remove prefix from name
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try:
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rate = float(curr_metrics[‘data‘][name] - last_metrics[‘data‘][name]) /
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float(curr_metrics[‘time‘] - last_metrics[‘time‘])
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if rate < 0:
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rate = float(0)
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except StandardError:
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rate = float(0)
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return rate
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def get_total_count(name):
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total_count = get_value(name)
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return total_count
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def get_count_insert(name):
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count_insert = get_rate(name)
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return count_insert
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def metric_init(lparams):
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global PARAMS
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# set parameters
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for key in lparams:
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PARAMS[key] = lparams[key]
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# define descriptors
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time_max = 60
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groups = ‘EPGInfo_www‘
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descriptors = [
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{
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‘name‘: NAME_PREFIX + ‘count_total‘,
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‘call_back‘: get_total_count,
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‘time_max‘: time_max,
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‘value_type‘: ‘float‘,
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‘units‘: ‘Total‘,
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‘slope‘: ‘both‘,
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‘format‘: ‘%f‘,
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‘description‘: ‘Total Count‘,
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‘groups‘: groups
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},
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{
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‘name‘: NAME_PREFIX + ‘count_insert‘,
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‘call_back‘: get_count_insert,
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‘time_max‘: time_max,
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‘value_type‘: ‘float‘,
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‘units‘: ‘Inserts/Sec‘,
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‘slope‘: ‘both‘,
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‘format‘: ‘%f‘,
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‘description‘: ‘Insert per Sec‘,
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‘groups‘: groups
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}
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]
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return descriptors
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def metric_cleanup():
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pass
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if __name__ == ‘__main__‘:
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descriptors = metric_init(PARAMS)
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while True:
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for d in descriptors:
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print ((‘%s = %s‘) % (d[‘name‘], d[‘format‘])) % (d[‘call_back‘](d[‘name‘]))
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print ‘‘
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time.sleep(METRICS_CACHE_TTL)
具体说明看代码中的注释
使用ganglia监控mongodb数据库collection的增长
原文：http://blog.chinaunix.net/uid-13869856-id-5015899.html
