获取帮助

    输出帮助信息结果如下：

    2.     python main.py start [--role {{agent,collector,monitor}}] # start local service.
    3.     python main.py stop [--role {{agent,collector,monitor}}] # stop local service.
    4.     python main.py start [--user USER] [--host HOST] [--project-path PROJECT_PATH] [--role {{agent,collector,monitor}}]
    5.     # start the remote service.
    6.     python main.py stop [--user USER] [--host HOST] [--project-path PROJECT_PATH] [--role {{agent,collector,
    7.     monitor}}] # stop the remote service.
    8.     python main.py deploy [--user USER] [--host HOST] [--project-path PROJECT_PATH] # deploy project in remote host.
    9.     python main.py diagnosis [--query] [--start_time] [--finish_time] # rca for slow SQL.
    10.     python main.py show_metrics # display all monitored metrics(can only be executed on 'detector' machine).
    11.     python main.py forecast [--metric-name METRIC_NAME] [--period] [--freq]
    12.      [--forecast-method {{auto_arima, fbprophet}}] [--save-path SAVE_PATH] # forecast future trend of
    13.      metric(can only be executed on 'detector' machine).
    15. Anomaly-detection: a time series forecast and anomaly detection tool.
    17. positional arguments:
    18.   {start,stop,deploy,show_metrics,forecast,diagnosis}
    20.   -h, --help            show this help message and exit
    21.   --user USER           User of remote server.
    22.   --host HOST           IP of remote server.
    23.   --project-path PROJECT_PATH
    24.                         Project location in remote server.
    25.   --role {agent,collector,monitor}
    26.                         Run as 'agent', 'collector', 'monitor'. Notes: ensure
    27.                         the normal operation of the openGauss in agent.
    28.   --metric-name METRIC_NAME
    29.                         Metric name to be predicted, you must provide an specified metric name.
    30. .
    31.   --query QUERY         target sql for RCA.
    32.                         Currently, the join operator is not supported, and the accuracy of the result 
    33.                         is not guaranteed for SQL syntax containing "not null and".
    34.   --start_time START_TIME
    35.                         start time of query
    36.   --finish_time FINISH_TIME
    37.                         finish time of query
    39.                         trainnig data.if this parameter is not provided, the
    40.                         default value '100S' will be used.
    41.   --freq FREQ           forecast gap, time unit: S: Second, M: Minute, H:
    42.                         Hour, D: Day, W: Week.
    43.   --forecast-method FORECAST_METHOD
    44.                         Forecast method, default method is 'auto_arima',if
    45.                         want to use 'fbprophet', you should install fbprophet
    46.                         first.
    47.   --save-path SAVE_PATH
    48.                         Save the results to this path using csv format, if
    49.                         this parameter is not provided,, the result wil not be
    50.                         saved.
    51.   -v, --version         show program's version number and exit
    53. epilog:
    54.      the 'a-detection.conf' and 'metric_task.conf' will be read when the program is running,
    55.      the location of them is:
    57.      metric_config: /openGauss-server/src/gausskernel/dbmind/tools/anomaly_detection/task/metric_task.conf.