Packages

c

io.projectglow

GlowBase

class GlowBase extends AnyRef

The entry point for all language specific functionality, meaning methods that cannot be expressed as SparkSQL expressions.

We should expose as little functionality as is necessary through this object and should prefer generic methods with stringly-typed arguments to reduce language-specific maintenance burden.

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Glow
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Instance Constructors

  1. new GlowBase()

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. final def eq(arg0: AnyRef): Boolean
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  7. def equals(arg0: Any): Boolean
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  8. def finalize(): Unit
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  9. final def getClass(): Class[_]
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  10. def hashCode(): Int
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  11. final def isInstanceOf[T0]: Boolean
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  12. final def ne(arg0: AnyRef): Boolean
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  13. final def notify(): Unit
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  14. final def notifyAll(): Unit
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    @native()
  15. def register(spark: SparkSession): Unit
  16. final def synchronized[T0](arg0: ⇒ T0): T0
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  17. def toString(): String
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  18. def transform(operationName: String, df: DataFrame, options: Map[String, String]): DataFrame
  19. def transform(operationName: String, df: DataFrame, options: (String, String)*): DataFrame
  20. def transform(operationName: String, df: DataFrame, options: Map[String, String]): DataFrame

    Apply a named transformation to a DataFrame of genomic data.

    Apply a named transformation to a DataFrame of genomic data. All parameters apart from the input data and its schema are provided through the case-insensitive options map.

    There are no bounds on what the transformer may do. For instance, it's legal for the transformer to materialize the input DataFrame.

    returns

    The transformed DataFrame

  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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