def METHOD_NAME(self, stats):
    """
    Given the statistics that are uploaded to wmstats, create different
    documents to post to MonIT AMQ (aggregation-friendly docs).
    """
    mapMetricToType = {'uniqueJobsPerSite': 'work_site_unique',  # respecting data location constraints
                       'possibleJobsPerSite': 'work_site_possible',
                       'uniqueJobsPerSiteAAA': 'work_site_uniqueAAA',  # assume work can run anywhere
                       'possibleJobsPerSiteAAA': 'work_site_possibleAAA'}
    commonInfo = {"agent_url": "global_workqueue"}
    docs = []
    for status, data in viewitems(stats['workByStatus']):
        doc = dict()
        doc["type"] = "work_info"
        doc["status"] = status
        doc["num_elem"] = data.get('num_elem', 0)  # total number of workqueue elements
        doc["sum_jobs"] = data.get('sum_jobs', 0)  # total number of top level jobs
        doc["max_jobs_elem"] = data.get('max_jobs_elem', 0)  # largest # of jobs found in a WQE
        docs.append(doc)
    for status, data in viewitems(stats['workByStatusAndPriority']):
        for item in data:
            doc = dict()
            doc["type"] = "work_prio_status"
            doc["status"] = status
            doc.update(item)
            docs.append(doc)
    for item in stats['workByAgentAndStatus']:
        doc = dict()
        doc["type"] = "work_agent_status"
        doc["status"] = item['status']
        doc["agent_name"] = item['agent_name']
        doc["num_elem"] = item['num_elem']  # total number of workqueue elements
        doc["sum_jobs"] = item['sum_jobs']  # total number of top level jobs
        doc["max_jobs_elem"] = item['max_jobs_elem']  # largest # of jobs found in a WQE
        docs.append(doc)
    for item in stats['workByAgentAndPriority']:
        doc = dict()
        doc["type"] = "work_agent_prio"
        doc["priority"] = item['priority']
        doc["agent_name"] = item['agent_name']
        doc["num_elem"] = item['num_elem']  # total number of workqueue elements
        doc["sum_jobs"] = item['sum_jobs']  # total number of top level jobs
        doc["max_jobs_elem"] = item['max_jobs_elem']  # largest # of jobs found in a WQE
        docs.append(doc)
    # let's remap Jobs --> sum_jobs , and NumElems --> num_elem
    for metric in mapMetricToType:
        for status, sites in viewitems(stats[metric]):
            if not sites:
                # no work in this status available for any sites, skip!
                continue
            for site in sites:
                doc = dict()
                doc["type"] = mapMetricToType[metric]
                doc["status"] = status
                doc["site_name"] = site
                doc['num_elem'] = sites[site]['num_elem']
                doc['sum_jobs'] = int(sites[site]['sum_jobs'])
                docs.append(doc)
    # mark every single document as being from global_workqueue
    for doc in docs:
        doc.update(commonInfo)
    self.logger.info("%i docs created to post to MonIT", len(docs))
    return docs