GarbageCollector

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. val bitwiseOR: (Int, Int) ⇒ Int

   

6. def clone(): AnyRef

   

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

   

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8. def equals(arg0: Any): Boolean

   

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9. def finalize(): Unit

   

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10. def getAddressesToDelete(expiredRangeIDs: Dataset[String], keepRangeIDs: Dataset[String], repo: String, storageNS: String, numRangePartitions: Int, numAddressPartitions: Int): Dataset[String]

    

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

    

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12. def getCommitsDF(commitDFLocation: String): Dataset[Row]

    

13. def getExpiredAddresses(repo: String, storageNS: String, runID: String, commitDFLocation: String, numCommitPartitions: Int, numRangePartitions: Int, numAddressPartitions: Int): Dataset[String]

    

14. def getRangeIDsForCommits(commitIDs: Dataset[String], repo: String): Dataset[String]

    

15. def hashCode(): Int

    

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16. final def isInstanceOf[T0]: Boolean

    

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17. def minus(left: Dataset[String], right: Dataset[String], partitioner: Partitioner): Dataset[String]

    

    Compute a distinct antijoin using partitioner.

    Compute a distinct antijoin using partitioner. This is the same as

        left.distinct.except(right.distinct)
    

    but forces our plan. Useful when Spark is unable to predict the structure and/or size of either argument.

    returns

    all elements in left that are not in right.

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

    

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19. final def notify(): Unit

    

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20. final def notifyAll(): Unit

    

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21. val rangeGetter: RangeGetter

    

22. lazy val spark: SparkSession

    

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

    

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24. def toString(): String

    

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25. final def wait(): Unit

    

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

    

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

    

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