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c

org.apache.spark.sql.catalyst.csv

CSVInferSchema

class CSVInferSchema extends Serializable

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Instance Constructors

  1. new CSVInferSchema(options: CSVOptions)

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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    @native()
  11. def infer(tokenRDD: RDD[Array[String]], header: Array[String]): StructType

    Similar to the JSON schema inference

    Similar to the JSON schema inference

    1. Infer type of each row 2. Merge row types to find common type 3. Replace any null types with string type
  12. def inferField(typeSoFar: DataType, field: String): DataType

    Infer type of string field.

    Infer type of string field. Given known type Double, and a string "1", there is no point checking if it is an Int, as the final type must be Double or higher.

  13. def inferRowType(rowSoFar: Array[DataType], next: Array[String]): Array[DataType]
  14. final def isInstanceOf[T0]: Boolean
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  15. def mergeRowTypes(first: Array[DataType], second: Array[DataType]): Array[DataType]
  16. final def ne(arg0: AnyRef): Boolean
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  17. final def notify(): Unit
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    @native()
  18. final def notifyAll(): Unit
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    @native()
  19. val options: CSVOptions
  20. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
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  21. def toString(): String
    Definition Classes
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  22. def toStructFields(fieldTypes: Array[DataType], header: Array[String]): Array[StructField]
  23. final def wait(): Unit
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  24. final def wait(arg0: Long, arg1: Int): Unit
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  25. final def wait(arg0: Long): Unit
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