ai.deepsense.deeplang.doperables
Creates a transformed DataFrame based on input DataFrame.
Creates a transformed DataFrame based on input DataFrame.
Should be implemented in subclasses.
Should be implemented in subclasses. For known schema of input DataFrame, infers schema of output DataFrame. If it is not able to do it for some reasons, it returns None.
Sequence of params without values for this class, parsed from Json.
Sequence of params without values for this class, parsed from Json. If a name of a parameter is unknown, it's ignored JsNull is treated as empty object. JsNull as a value of a parameter unsets param's value.
Sequence of paramPairs for this class, parsed from Json.
Sequence of paramPairs for this class, parsed from Json. If a name of a parameter is unknown, it's ignored JsNull is treated as empty object. JsNull as value of parameter is ignored.
Json describing values associated to parameters.
Json describing values associated to parameters.
Compares 'this' and 'other' params.
Compares 'this' and 'other' params. Objects are equal when they are of the same class and their parameters have the same values set.
True, if 'this' and 'other' are the same.
Sets param values based on provided json.
Sets param values based on provided json. If a name of a parameter is unknown, it's ignored JsNull is treated as empty object.
When ignoreNulls = false, JsNull as a value of a parameter unsets param's value. When ignoreNulls = true, parameters with JsNull values are ignored.
Validates Params entities that contain dynamic parameters' values.
Validates Params entities that contain dynamic parameters' values. Validation errors are wrapped in DeepLangMultiException.
Validates params' values by: 1.
Validates params' values by: 1. testing whether the params have values set (or default values), 2. testing whether the values meet the constraints, 3. testing custom validations, possibly spanning over multiple params.
Operation that is able to take dataframe and split its timestamp column to many columns containing timestamp parts. Client can choose timestamp parts from set: {year, month, day, hour, minutes, seconds} using parameters. Choosing $part value will result in adding new column with name: {original_timestamp_column_name}_$part of IntegerType containing $part value. If a column with that name already exists {original_timestamp_column_name}_$part_N will be used, where N is first not used Int value starting from 1.