decisionai_plugin/common/tsanaclient.py [182:205]:
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        end_str = dt_to_str(end_time)
        start_str = dt_to_str(start_time)

        multi_series_data = []
        total_point_num = 0
        loop = 0

        # Query each series's tag
        for data in series_sets:
            dim = {}
            if 'dimensionFilter' not in data:
                data['dimensionFilter'] = data['filters']

            for dimkey in data['dimensionFilter']:
                dim[dimkey] = [data['dimensionFilter'][dimkey]]

            skip = 0
            count = 0
            para = dict(metricId=data['metricId'], dimensionFilter=dim, activeSince=start_str)
            gran_info = (data['metricMeta']['granularityName'], data['metricMeta']['granularityAmount'])
            data_point_num_per_series = len(get_time_list(start_time, end_time, gran_info))
            series_limit_per_call = min(max(100000 // data_point_num_per_series, 1), 1000)

            while True:
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decisionai_plugin/common/tsanaclient.py [316:339]:
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        end_str = dt_to_str(end_time)
        start_str = dt_to_str(start_time)

        multi_series_data = []
        total_point_num = 0
        loop = 0

        # Query each series's tag
        for data in series_sets:
            dim = {}
            if 'dimensionFilter' not in data:
                data['dimensionFilter'] = data['filters']

            for dimkey in data['dimensionFilter']:
                dim[dimkey] = [data['dimensionFilter'][dimkey]]

            skip = 0
            count = 0
            para = dict(metricId=data['metricId'], dimensionFilter=dim, activeSince=start_str)
            gran_info = (data['metricMeta']['granularityName'], data['metricMeta']['granularityAmount'])
            data_point_num_per_series = len(get_time_list(start_time, end_time, gran_info))
            series_limit_per_call = min(max(100000 // data_point_num_per_series, 1), 1000)

            while True:
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