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object OrcUtils extends Logging

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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. def addSparkVersionMetadata(writer: Writer): Unit

    Add a metadata specifying Spark version.

  5. final def asInstanceOf[T0]: T0
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  6. def clone(): AnyRef
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  9. val extensionsForCompressionCodecNames: Map[String, String]
  10. def finalize(): Unit
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  11. final def getClass(): Class[_]
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  13. def inferSchema(sparkSession: SparkSession, files: Seq[FileStatus], options: Map[String, String]): Option[StructType]
  14. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
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  15. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
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  16. final def isInstanceOf[T0]: Boolean
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  17. def isTraceEnabled(): Boolean
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  18. def listOrcFiles(pathStr: String, conf: Configuration): Seq[Path]
  19. def log: Logger
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  20. def logDebug(msg: ⇒ String, throwable: Throwable): Unit
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  21. def logDebug(msg: ⇒ String): Unit
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  22. def logError(msg: ⇒ String, throwable: Throwable): Unit
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  23. def logError(msg: ⇒ String): Unit
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  24. def logInfo(msg: ⇒ String, throwable: Throwable): Unit
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  25. def logInfo(msg: ⇒ String): Unit
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  26. def logName: String
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  27. def logTrace(msg: ⇒ String, throwable: Throwable): Unit
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  28. def logTrace(msg: ⇒ String): Unit
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  29. def logWarning(msg: ⇒ String, throwable: Throwable): Unit
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  30. def logWarning(msg: ⇒ String): Unit
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  31. final def ne(arg0: AnyRef): Boolean
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  32. final def notify(): Unit
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  33. final def notifyAll(): Unit
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  34. def orcResultSchemaString(canPruneCols: Boolean, dataSchema: StructType, resultSchema: StructType, partitionSchema: StructType, conf: Configuration): String

    returns

    Returns the result schema string based on the canPruneCols flag. resultSchemaString will be created using resultsSchema in case of canPruneCols is true and for canPruneCols as false value resultSchemaString will be created using the actual dataSchema.

  35. def orcTypeDescriptionString(dt: DataType): String

    Given a StructType object, this methods converts it to corresponding string representation in ORC.

  36. def readCatalystSchema(file: Path, conf: Configuration, ignoreCorruptFiles: Boolean): Option[StructType]
  37. def readOrcSchemasInParallel(files: Seq[FileStatus], conf: Configuration, ignoreCorruptFiles: Boolean): Seq[StructType]

    Reads ORC file schemas in multi-threaded manner, using native version of ORC.

    Reads ORC file schemas in multi-threaded manner, using native version of ORC. This is visible for testing.

  38. def readSchema(sparkSession: SparkSession, files: Seq[FileStatus]): Option[StructType]
  39. def readSchema(file: Path, conf: Configuration, ignoreCorruptFiles: Boolean): Option[TypeDescription]
  40. def requestedColumnIds(isCaseSensitive: Boolean, dataSchema: StructType, requiredSchema: StructType, reader: Reader, conf: Configuration): Option[(Array[Int], Boolean)]

    returns

    Returns the combination of requested column ids from the given ORC file and boolean flag to find if the pruneCols is allowed or not. Requested Column id can be -1, which means the requested column doesn't exist in the ORC file. Returns None if the given ORC file is empty.

  41. final def synchronized[T0](arg0: ⇒ T0): T0
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  42. def toString(): String
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  43. final def wait(): Unit
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  44. final def wait(arg0: Long, arg1: Int): Unit
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  45. final def wait(arg0: Long): Unit
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