DetectAnomalies¶
-
class
DetectAnomalies.DetectAnomalies(concurrency=1, concurrentTimeout=100.0, customInterval=None, errorCol=None, granularity=None, handler=None, maxAnomalyRatio=None, outputCol=None, period=None, sensitivity=None, series=None, subscriptionKey=None, timeout=60.0, url=None)[source]¶ Bases:
mmlspark.Utils.ComplexParamsMixin,pyspark.ml.util.JavaMLReadable,pyspark.ml.util.JavaMLWritable,pyspark.ml.wrapper.JavaTransformerParameters: - concurrency (int) – max number of concurrent calls (default: 1)
- concurrentTimeout (double) – max number seconds to wait on futures if concurrency >= 1 (default: 100.0)
- customInterval (object) – Custom Interval is used to set non-standard time interval, for example, if the series is 5 minutes, request can be set as granularity=minutely, customInterval=5.
- errorCol (str) – column to hold http errors (default: [self.uid]_error)
- granularity (object) – Can only be one of yearly, monthly, weekly, daily, hourly or minutely.Granularity is used for verify whether input series is valid.
- handler (object) – Which strategy to use when handling requests (default: UserDefinedFunction(<function2>,StringType,None))
- maxAnomalyRatio (object) – Optional argument, advanced model parameter, max anomaly ratio in a time series.
- outputCol (str) – The name of the output column (default: [self.uid]_output)
- period (object) – Optional argument, periodic value of a time series.If the value is null or does not present, the API will determine the period automatically.
- sensitivity (object) – Optional argument, advanced model parameter, between 0-99,the lower the value is, the larger the margin value will be which means less anomalies will be accepted
- series (object) – Time series data points. Points should be sorted by timestamp in ascending orderto match the anomaly detection result. If the data is not sorted correctly orthere is duplicated timestamp, the API will not work.In such case, an error message will be returned.
- subscriptionKey (object) – the API key to use
- timeout (double) – number of seconds to wait before closing the connection (default: 60.0)
- url (str) – Url of the service
-
getConcurrentTimeout()[source]¶ Returns: max number seconds to wait on futures if concurrency >= 1 (default: 100.0) Return type: double
-
getCustomInterval()[source]¶ Returns: Custom Interval is used to set non-standard time interval, for example, if the series is 5 minutes, request can be set as granularity=minutely, customInterval=5. Return type: object
-
getErrorCol()[source]¶ Returns: column to hold http errors (default: [self.uid]_error) Return type: str
-
getGranularity()[source]¶ Returns: Can only be one of yearly, monthly, weekly, daily, hourly or minutely.Granularity is used for verify whether input series is valid. Return type: object
-
getHandler()[source]¶ Returns: Which strategy to use when handling requests (default: UserDefinedFunction(<function2>,StringType,None)) Return type: object
-
getMaxAnomalyRatio()[source]¶ Returns: Optional argument, advanced model parameter, max anomaly ratio in a time series. Return type: object
-
getOutputCol()[source]¶ Returns: The name of the output column (default: [self.uid]_output) Return type: str
-
getPeriod()[source]¶ Returns: Optional argument, periodic value of a time series.If the value is null or does not present, the API will determine the period automatically. Return type: object
-
getSensitivity()[source]¶ Returns: Optional argument, advanced model parameter, between 0-99,the lower the value is, the larger the margin value will be which means less anomalies will be accepted Return type: object
-
getSeries()[source]¶ Returns: Time series data points. Points should be sorted by timestamp in ascending orderto match the anomaly detection result. If the data is not sorted correctly orthere is duplicated timestamp, the API will not work.In such case, an error message will be returned. Return type: object
-
getTimeout()[source]¶ Returns: number of seconds to wait before closing the connection (default: 60.0) Return type: double
-
setConcurrency(value)[source]¶ Parameters: concurrency (int) – max number of concurrent calls (default: 1)
-
setConcurrentTimeout(value)[source]¶ Parameters: concurrentTimeout (double) – max number seconds to wait on futures if concurrency >= 1 (default: 100.0)
-
setCustomInterval(value)[source]¶ Parameters: customInterval (object) – Custom Interval is used to set non-standard time interval, for example, if the series is 5 minutes, request can be set as granularity=minutely, customInterval=5.
-
setCustomIntervalCol(value)[source]¶ Parameters: customInterval (object) – Custom Interval is used to set non-standard time interval, for example, if the series is 5 minutes, request can be set as granularity=minutely, customInterval=5.
-
setErrorCol(value)[source]¶ Parameters: errorCol (str) – column to hold http errors (default: [self.uid]_error)
-
setGranularity(value)[source]¶ Parameters: granularity (object) – Can only be one of yearly, monthly, weekly, daily, hourly or minutely.Granularity is used for verify whether input series is valid.
-
setGranularityCol(value)[source]¶ Parameters: granularity (object) – Can only be one of yearly, monthly, weekly, daily, hourly or minutely.Granularity is used for verify whether input series is valid.
-
setHandler(value)[source]¶ Parameters: handler (object) – Which strategy to use when handling requests (default: UserDefinedFunction(<function2>,StringType,None))
-
setMaxAnomalyRatio(value)[source]¶ Parameters: maxAnomalyRatio (object) – Optional argument, advanced model parameter, max anomaly ratio in a time series.
-
setMaxAnomalyRatioCol(value)[source]¶ Parameters: maxAnomalyRatio (object) – Optional argument, advanced model parameter, max anomaly ratio in a time series.
-
setOutputCol(value)[source]¶ Parameters: outputCol (str) – The name of the output column (default: [self.uid]_output)
-
setParams(concurrency=1, concurrentTimeout=100.0, customInterval=None, errorCol=None, granularity=None, handler=None, maxAnomalyRatio=None, outputCol=None, period=None, sensitivity=None, series=None, subscriptionKey=None, timeout=60.0, url=None)[source]¶ Set the (keyword only) parameters
Parameters: - concurrency (int) – max number of concurrent calls (default: 1)
- concurrentTimeout (double) – max number seconds to wait on futures if concurrency >= 1 (default: 100.0)
- customInterval (object) – Custom Interval is used to set non-standard time interval, for example, if the series is 5 minutes, request can be set as granularity=minutely, customInterval=5.
- errorCol (str) – column to hold http errors (default: [self.uid]_error)
- granularity (object) – Can only be one of yearly, monthly, weekly, daily, hourly or minutely.Granularity is used for verify whether input series is valid.
- handler (object) – Which strategy to use when handling requests (default: UserDefinedFunction(<function2>,StringType,None))
- maxAnomalyRatio (object) – Optional argument, advanced model parameter, max anomaly ratio in a time series.
- outputCol (str) – The name of the output column (default: [self.uid]_output)
- period (object) – Optional argument, periodic value of a time series.If the value is null or does not present, the API will determine the period automatically.
- sensitivity (object) – Optional argument, advanced model parameter, between 0-99,the lower the value is, the larger the margin value will be which means less anomalies will be accepted
- series (object) – Time series data points. Points should be sorted by timestamp in ascending orderto match the anomaly detection result. If the data is not sorted correctly orthere is duplicated timestamp, the API will not work.In such case, an error message will be returned.
- subscriptionKey (object) – the API key to use
- timeout (double) – number of seconds to wait before closing the connection (default: 60.0)
- url (str) – Url of the service
-
setPeriod(value)[source]¶ Parameters: period (object) – Optional argument, periodic value of a time series.If the value is null or does not present, the API will determine the period automatically.
-
setPeriodCol(value)[source]¶ Parameters: period (object) – Optional argument, periodic value of a time series.If the value is null or does not present, the API will determine the period automatically.
-
setSensitivity(value)[source]¶ Parameters: sensitivity (object) – Optional argument, advanced model parameter, between 0-99,the lower the value is, the larger the margin value will be which means less anomalies will be accepted
-
setSensitivityCol(value)[source]¶ Parameters: sensitivity (object) – Optional argument, advanced model parameter, between 0-99,the lower the value is, the larger the margin value will be which means less anomalies will be accepted
-
setSeries(value)[source]¶ Parameters: series (object) – Time series data points. Points should be sorted by timestamp in ascending orderto match the anomaly detection result. If the data is not sorted correctly orthere is duplicated timestamp, the API will not work.In such case, an error message will be returned.
-
setSeriesCol(value)[source]¶ Parameters: series (object) – Time series data points. Points should be sorted by timestamp in ascending orderto match the anomaly detection result. If the data is not sorted correctly orthere is duplicated timestamp, the API will not work.In such case, an error message will be returned.