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org.apache.spark.sql.execution.datasources.json

JsonIngestionUtil

Related Doc: package json

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object JsonIngestionUtil

Code here comes from org.apache.spark.sql.execution.datasources.json.InferSchema

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  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. def compareTypes(context: List[String], schemaType: (String, DataType, Boolean), datasetType: (String, DataType, Boolean)): List[String]

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    similar to compatibleType(...) but instead of creating a new datatype, simply check the compatibility

    similar to compatibleType(...) but instead of creating a new datatype, simply check the compatibility

    context

    : full path to attribute, makes error messages more understandable

    schemaType

    : (attributeName, attributeType, isRequired) coming from the schema

    returns

    List of errors, Nil when datasetType is compatible with schemaType

  7. def compareTypes(schemaType: DataType, datasetType: DataType): List[String]

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  8. def compatibleType(t1: DataType, t2: DataType): DataType

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

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  10. def equals(arg0: Any): Boolean

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  11. val factory: JsonFactory

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  12. def finalize(): Unit

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  13. val findTightestCommonTypeOfTwo: (DataType, DataType) ⇒ Option[DataType]

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

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  15. def hashCode(): Int

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  16. def inferSchema(parser: JsonParser): DataType

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  17. final def isInstanceOf[T0]: Boolean

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  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. def parseRDD(inputRDD: RDD[Row], schemaSparkType: DataType): RDD[Either[List[String], (String, String)]]

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  22. def parseString(content: String): Try[DataType]

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  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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