Class

it.agilelab.bigdata.wasp.consumers.spark.strategies.gdpr.hdfs

HdfsDeletionHandler

Related Doc: package hdfs

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class HdfsDeletionHandler extends Logging

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Instance Constructors

  1. new HdfsDeletionHandler(fs: FileSystem, config: HdfsDeletionConfig, spark: SparkSession)

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Value Members

  1. final def !=(arg0: Any): Boolean

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  2. final def ##(): Int

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  3. final def ==(arg0: Any): Boolean

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  4. final def asInstanceOf[T0]: T0

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  5. def clone(): AnyRef

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  6. val dataPath: Path

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  7. def delete(filesToFilter: List[String]): Try[Unit]

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    Deletes the keys to delete stored in config.keysToDelete from the files filesToFilter.

    Deletes the keys to delete stored in config.keysToDelete from the files filesToFilter. All files to filter are read and merged into a DataFrame, and then only the rows that do not match the RawMatchingStrategy and PartitionPruningStrategy defined in config are written into a staging directory. Once the new files are correctly written into the staging directory, the original filesToFilter are deleted, and the newly written files are moved to the data directory.

  8. final def eq(arg0: AnyRef): Boolean

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  9. def equals(arg0: Any): Boolean

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  10. def finalize(): Unit

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  11. final def getClass(): Class[_]

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  12. def hashCode(): Int

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  13. final def isInstanceOf[T0]: Boolean

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  14. val logger: WaspLogger

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  15. final def ne(arg0: AnyRef): Boolean

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  16. final def notify(): Unit

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  17. final def notifyAll(): Unit

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  18. val stagingPath: Path

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  19. final def synchronized[T0](arg0: ⇒ T0): T0

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  20. def toString(): String

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  21. final def wait(): Unit

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  22. final def wait(arg0: Long, arg1: Int): Unit

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  23. final def wait(arg0: Long): Unit

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