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c

bio.ferlab.datalake.spark3.etl.v2

RawToNormalizedETL

class RawToNormalizedETL extends ETL

Linear Supertypes
ETL, Runnable, AnyRef, Any
Known Subclasses
RawFileToNormalizedETL
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Inherited
  1. RawToNormalizedETL
  2. ETL
  3. Runnable
  4. AnyRef
  5. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new RawToNormalizedETL(source: DatasetConf, mainDestination: DatasetConf, transformations: List[Transformation])(implicit conf: Configuration)

Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  4. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  5. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native() @HotSpotIntrinsicCandidate()
  6. implicit val conf: Configuration
    Definition Classes
    RawToNormalizedETL → ETL
  7. def defaultRepartition: (DataFrame) ⇒ DataFrame
    Definition Classes
    ETL
  8. val defaultRowPerPartition: Int
    Definition Classes
    ETL
  9. def defaultSampling: PartialFunction[String, (DataFrame) ⇒ DataFrame]
    Definition Classes
    ETL
  10. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  11. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  12. def extract(lastRunDateTime: LocalDateTime, currentRunDateTime: LocalDateTime)(implicit spark: SparkSession): Map[String, DataFrame]

    Reads data from a file system and produce a Map[DatasetConf, DataFrame].

    Reads data from a file system and produce a Map[DatasetConf, DataFrame]. This method should avoid transformation and joins but can implement filters in order to make the ETL more efficient.

    spark

    an instance of SparkSession

    returns

    all the data needed to pass to the transform method and produce the desired output.

    Definition Classes
    RawToNormalizedETL → ETL
  13. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  14. def getLastRunDateFor(ds: DatasetConf)(implicit spark: SparkSession): LocalDateTime

    If possible, fetch the last run date time from the dataset passed in argument

    If possible, fetch the last run date time from the dataset passed in argument

    ds

    dataset

    spark

    a spark session

    returns

    the last run date or the minDateTime

    Definition Classes
    ETL
  15. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  16. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  17. def load(data: Map[String, DataFrame], lastRunDateTime: LocalDateTime = minDateTime, currentRunDateTime: LocalDateTime = LocalDateTime.now(), repartition: (DataFrame) ⇒ DataFrame = defaultRepartition)(implicit spark: SparkSession): Map[String, DataFrame]

    Loads the output data into a persistent storage.

    Loads the output data into a persistent storage. The output destination can be any of: object store, database or flat files...

    data

    output data produced by the transform method.

    spark

    an instance of SparkSession

    Definition Classes
    ETL
  18. val log: Logger
    Definition Classes
    ETL
  19. val mainDestination: DatasetConf
    Definition Classes
    RawToNormalizedETL → ETL
  20. val maxDateTime: LocalDateTime
    Definition Classes
    ETL
  21. val minDateTime: LocalDateTime
    Definition Classes
    ETL
  22. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  23. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  24. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  25. def publish()(implicit spark: SparkSession): Unit

    OPTIONAL - Contains all actions needed to be done in order to make the data available to users like creating a view with the data.

    OPTIONAL - Contains all actions needed to be done in order to make the data available to users like creating a view with the data.

    spark

    an instance of SparkSession

    Definition Classes
    ETL
  26. def reset()(implicit spark: SparkSession): Unit

    Reset the ETL by removing the destination dataset.

    Reset the ETL by removing the destination dataset.

    Definition Classes
    ETL
  27. def run(runSteps: Seq[RunStep] = RunStep.default_load, lastRunDateTime: Option[LocalDateTime] = None, currentRunDateTime: Option[LocalDateTime] = None)(implicit spark: SparkSession): Map[String, DataFrame]

    Entry point of the etl - execute this method in order to run the whole ETL

    Entry point of the etl - execute this method in order to run the whole ETL

    spark

    an instance of SparkSession

    Definition Classes
    ETL → Runnable
  28. def sampling: PartialFunction[String, (DataFrame) ⇒ DataFrame]

    Logic used when the ETL is run as a SAMPLE_LOAD

    Logic used when the ETL is run as a SAMPLE_LOAD

    Definition Classes
    ETL
  29. val source: DatasetConf
  30. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  31. def toString(): String
    Definition Classes
    AnyRef → Any
  32. def transform(data: Map[String, DataFrame], lastRunDateTime: LocalDateTime, currentRunDateTime: LocalDateTime)(implicit spark: SparkSession): Map[String, DataFrame]

    Takes a Map[DataSource, DataFrame] as input and apply a set of transformation to it to produce the ETL output.

    Takes a Map[DataSource, DataFrame] as input and apply a set of transformation to it to produce the ETL output. It is recommended to not read any additional data but to use the extract() method instead to inject input data.

    data

    input data

    spark

    an instance of SparkSession

    Definition Classes
    RawToNormalizedETL → ETL
  33. val transformations: List[Transformation]
  34. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  35. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  36. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Deprecated Value Members

  1. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] ) @Deprecated
    Deprecated

Inherited from ETL

Inherited from Runnable

Inherited from AnyRef

Inherited from Any

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