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{"watcher/datasource/base.py":[{"author":{"_account_id":21692,"name":"licanwei","email":"li.canwei2@zte.com.cn","username":"licanwei"},"change_message_id":"f4803d46a9e0c7d8d4ff13f72f4cc9fd91e07d78","unresolved":false,"context_lines":[{"line_number":58,"context_line":"    )"},{"line_number":59,"context_line":""},{"line_number":60,"context_line":"    @abc.abstractmethod"},{"line_number":61,"context_line":"    def statistic_aggregation(self, resource_id, meter_name, period,"},{"line_number":62,"context_line":"                              granularity, aggregation\u003dNone):"},{"line_number":63,"context_line":"        pass"},{"line_number":64,"context_line":""},{"line_number":65,"context_line":"    @abc.abstractmethod"}],"source_content_type":"text/x-python","patch_set":3,"id":"5f93b717_bdd41b49","line":62,"range":{"start_line":61,"start_character":30,"end_line":62,"end_character":59},"updated":"2018-02-02 03:02:41.000000000","message":"Contrast to the define in ceilometer.py, here lacks some parameters.\n def statistic_aggregation(self, resource_id\u003dNone, meter_name\u003dNone, period\u003d300, granularity\u003d300, dimensions\u003dNone, aggregation\u003d\u0027avg\u0027, group_by\u003d\u0027*\u0027):","commit_id":"1b5e7f5ccbb9da373342e574b0527943163b0a07"},{"author":{"_account_id":19055,"name":"Alexander Chadin","email":"joker946@gmail.com","username":"joker946"},"change_message_id":"9cdd520129633a4d9fa9eb319e5f8939e90d6fa6","unresolved":false,"context_lines":[{"line_number":58,"context_line":"    )"},{"line_number":59,"context_line":""},{"line_number":60,"context_line":"    @abc.abstractmethod"},{"line_number":61,"context_line":"    def statistic_aggregation(self, resource_id, meter_name, period,"},{"line_number":62,"context_line":"                              granularity, aggregation\u003dNone):"},{"line_number":63,"context_line":"        pass"},{"line_number":64,"context_line":""},{"line_number":65,"context_line":"    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group_by\u003d\u0027*\u0027):"},{"line_number":77,"context_line":"        pass"},{"line_number":78,"context_line":""},{"line_number":79,"context_line":"    @abc.abstractmethod"}],"source_content_type":"text/x-python","patch_set":3,"id":"5f93b717_bd397ba4","line":76,"range":{"start_line":74,"start_character":46,"end_line":76,"end_character":39},"updated":"2018-02-02 03:02:41.000000000","message":"why add meter_name,dimensions and group_by? it seems useless.","commit_id":"1b5e7f5ccbb9da373342e574b0527943163b0a07"},{"author":{"_account_id":19055,"name":"Alexander Chadin","email":"joker946@gmail.com","username":"joker946"},"change_message_id":"9cdd520129633a4d9fa9eb319e5f8939e90d6fa6","unresolved":false,"context_lines":[{"line_number":71,"context_line":"        pass"},{"line_number":72,"context_line":""},{"line_number":73,"context_line":"    @abc.abstractmethod"},{"line_number":74,"context_line":"    def get_host_cpu_usage(self, resource_id, meter_name, 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util \u003d self.datasource_backend.statistic_aggregation("},{"line_number":293,"context_line":"                        instance.uuid, self._meter, self._period,"},{"line_number":294,"context_line":"                        self._granularity, aggregation\u003d\u0027mean\u0027)"},{"line_number":295,"context_line":"                except Exception as exc:"}],"source_content_type":"text/x-python","patch_set":2,"id":"5f93b717_9a2e4590","line":292,"range":{"start_line":292,"start_character":51,"end_line":292,"end_character":72},"updated":"2018-01-31 05:29:06.000000000","message":"statistic_aggregation in monasca.py has the diffrent input parameters.","commit_id":"8f1678495de5bfe96aece622b15260e6bc5f5de3"},{"author":{"_account_id":19055,"name":"Alexander Chadin","email":"joker946@gmail.com","username":"joker946"},"change_message_id":"d66049c89cd5d7f8f2960e81480f052079ee3d27","unresolved":false,"context_lines":[{"line_number":289,"context_line":"            for instance in 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