parameters: (self, perf_context_ts, stats_freq_sec, cumulative)
docstring: perf_context_ts is expected to be in the following format:
          Dict[metric, Dict[timestamp, value]], where for
          each (metric, timestamp) pair, the value is database-wide (i.e.
          summed over all the threads involved)
          if stats_freq_sec == 0, per-metric only one value is reported
docstring_summary: perf_context_ts is expected to be in the following format:
          Dict[metric, Dict[timestamp, value]], where for
          each (metric, timestamp) pair, the value is database-wide (i.e.
          summed over all the threads involved)
          if stats_freq_sec == 0, per-metric only one value is reported
docstring_tokens: perf_context_ts is expected to be in the following format : Dict [ metric Dict [ timestamp value ]] where for each ( metric timestamp ) pair the value is database - wide ( i . e . summed over all the threads involved ) if stats_freq_sec == 0 per - metric only one value is reported
function: def __init__(self, perf_context_ts, stats_freq_sec, cumulative):
          '''
          perf_context_ts is expected to be in the following format:
          Dict[metric, Dict[timestamp, value]], where for
          each (metric, timestamp) pair, the value is database-wide (i.e.
          summed over all the threads involved)
          if stats_freq_sec == 0, per-metric only one value is reported
          '''
          super().__init__()
          self.stats_freq_sec = stats_freq_sec
          self.keys_ts = {NO_ENTITY: perf_context_ts}
          if cumulative:
              self.unaccumulate_metrics()
function_tokens: def __init__ ( self , perf_context_ts , stats_freq_sec , cumulative ) : super ( ) . __init__ ( ) self . stats_freq_sec = stats_freq_sec self . keys_ts = { NO_ENTITY : perf_context_ts } if cumulative : self . unaccumulate_metrics ( )