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_line(self, result_entry: List[Dict[str, Any]], parser: LogMetricsParser) -> None:
"""
Parses the single entry from CloudWatch Insights results and adds any metrics it finds
to 'all_metrics' along with the timestamp for the entry.
Args:
result_entry (List[Dict[str, Any]]): A structured result from calling CloudWatch
Insights to get logs that contain metrics. A single entry contains the message
(the actual line logged to output), the timestamp (generated by CloudWatch Logs),
and other metadata that we (currently) do not use.
parser (LogMetricsParser) : The CWL metrics parser.
"""
message = self._get_element_from_log_line("@message", result_entry)
if message:
timestamp = self._get_element_from_log_line("@timestamp", result_entry)
parser.parse_log_message(timestamp, message)
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 _parse_metrics_from_log_stream(
self,
stream_name: str,
timeout_time: float,
parser: LogMetricsParser,
) -> None:
"""
Synchronously retrieves the algorithm metrics logged in a given job log stream.
Args:
stream_name (str): The name of the log stream.
timeout_time (float) : We stop getting metrics if the current time is beyond
the timeout time.
parser (LogMetricsParser) : The CWL metrics parser.
Returns:
None
"""
kwargs = {
"logGroupName": self.LOG_GROUP_NAME,
"logStreamName": stream_name,
"startFromHead": True,
"limit": 10000,
}
previous_token = None
while time.time() < timeout_time:
response = self._logs_client.get_log_events(**kwargs)
for event in response.get("events"):
message = event.get("message")
if self._is_metrics_message(message):
parser.parse_log_message(event.get("timestamp"), message)
next_token = response.get("nextForwardToken")
if not next_token or next_token == previous_token:
return
previous_token = next_token
kwargs["nextToken"] = next_token
self._logger.warning(
"Timed out waiting for all metrics. Data may be incomplete.")
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)