def metrics(
self,
metric_type: MetricType = MetricType.TIMESTAMP,
statistic: MetricStatistic = MetricStatistic.MAX,
) -> Dict[str, List[Any]]:
"""Gets all the metrics data, where the keys are the column names, and the values are a list
containing the values in each row. For example, the table:
timestamp energy
0 0.1
1 0.2
would be represented as:
{ "timestamp" : [0, 1], "energy" : [0.1, 0.2] }
values may be integers, floats, strings or None.
Args:
metric_type (MetricType): The type of metrics to get. Default: MetricType.TIMESTAMP.
statistic (MetricStatistic): The statistic to determine which metric value to use
when there is a conflict. Default: MetricStatistic.MAX.
Returns:
Dict[str, List[Union[str, float, int]]] : The metrics data.
"""
parser = LogMetricsParser()
current_time = str(time.time())
for line in self.run_log.splitlines():
if line.startswith("Metrics -"):
parser.parse_log_message(current_time, line)
return parser.get_parsed_metrics(metric_type, statistic)
def _parse_log_query_results(
self, results: List[Any], metric_type: MetricType, statistic: MetricStatistic
) -> Dict[str, List[Union[str, float, int]]]:
"""
Parses CloudWatch Insights results and returns all found metrics.
Args:
results (List[Any]): A structured result from calling CloudWatch Insights to get
logs that contain metrics.
metric_type (MetricType): The type of metrics to get.
statistic (MetricStatistic): The statistic to determine which metric value to use
when there is a conflict.
Returns:
Dict[str, List[Union[str, float, int]]] : The metrics data.
"""
parser = LogMetricsParser()
for result in results:
self._parse_log_line(result, parser)
return parser.get_parsed_metrics(metric_type, statistic)
def get_metrics_for_job(
self,
job_name: str,
metric_type: MetricType = MetricType.TIMESTAMP,
statistic: MetricStatistic = MetricStatistic.MAX,
) -> Dict[str, List[Union[str, float, int]]]:
"""
Synchronously retrieves all the algorithm metrics logged by a given Job.
Args:
job_name (str): The name of the Job. The name must be exact to ensure only the relevant
metrics are retrieved.
metric_type (MetricType): The type of metrics to get. Default is MetricType.TIMESTAMP.
statistic (MetricStatistic): The statistic to determine which metric value to use
when there is a conflict. Default is MetricStatistic.MAX.
Returns:
Dict[str, List[Union[str, float, int]]] : The metrics data, where the keys
are the column names and the values are a list containing the values in each row.
Example:
timestamp energy
0 0.1
1 0.2
would be represented as:
{ "timestamp" : [0, 1], "energy" : [0.1, 0.2] }
values may be integers, floats, strings or None.
"""
timeout_time = time.time() + self._poll_timeout_seconds
parser = LogMetricsParser()
log_streams = self._get_log_streams_for_job(job_name, timeout_time)
for log_stream in log_streams:
self._parse_metrics_from_log_stream(log_stream, timeout_time,
parser)
return parser.get_parsed_metrics(metric_type, statistic)