t

com.holdenkarau.spark.testing

DatasetSuiteBaseLike

trait DatasetSuiteBaseLike extends DataFrameSuiteBaseLike

Linear Supertypes
DataFrameSuiteBaseLike, Serializable, Serializable, TestSuiteLike, SparkContextProvider, AnyRef, Any
Known Subclasses
DatasetSuiteBase, JavaDatasetSuiteBase
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Inherited
  1. DatasetSuiteBaseLike
  2. DataFrameSuiteBaseLike
  3. Serializable
  4. Serializable
  5. TestSuiteLike
  6. SparkContextProvider
  7. AnyRef
  8. Any
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Visibility
  1. Public
  2. All

Abstract Value Members

  1. abstract def assert[U](message: String, expected: U, actual: U)(implicit CT: ClassTag[U]): Unit
    Definition Classes
    TestSuiteLike
  2. abstract def assert[U](expected: U, actual: U)(implicit CT: ClassTag[U]): Unit
    Definition Classes
    TestSuiteLike
  3. abstract def assertEmpty[U](arr: Array[U])(implicit CT: ClassTag[U]): Unit
    Definition Classes
    TestSuiteLike
  4. abstract def assertTrue(expected: Boolean): Unit
    Definition Classes
    TestSuiteLike
  5. abstract def fail(message: String): Unit
    Definition Classes
    TestSuiteLike
  6. abstract def sc: SparkContext
    Definition Classes
    SparkContextProvider

Concrete Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  4. def appID: String
    Definition Classes
    SparkContextProvider
  5. def appName: String
    Definition Classes
    SparkContextProvider
  6. def approxEquals(r1: Row, r2: Row, tol: Double, tolTimestamp: Duration): Boolean
    Definition Classes
    DataFrameSuiteBaseLike
  7. def approxEquals(r1: Row, r2: Row, tolTimestamp: Duration): Boolean
    Definition Classes
    DataFrameSuiteBaseLike
  8. def approxEquals(r1: Row, r2: Row, tol: Double): Boolean
    Definition Classes
    DataFrameSuiteBaseLike
  9. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  10. def assertDataFrameApproximateEquals(expected: DataFrame, result: DataFrame, tol: Double, tolTimestamp: Duration, customShow: (DataFrame) ⇒ Unit = _.show()): Unit

    Compares if two DataFrames are equal, checks that the schemas are the same.

    Compares if two DataFrames are equal, checks that the schemas are the same. When comparing inexact fields uses tol & tolTimestamp.

    tol

    max acceptable numeric tolerance, should be less than 1.

    tolTimestamp

    max acceptable timestamp tolerance.

    customShow

    unit function to customize the show method when dataframes are not equal. IE: df.show(false) or df.toJSON.show(false).

    Definition Classes
    DataFrameSuiteBaseLike
  11. def assertDataFrameDataEquals(expected: DataFrame, result: DataFrame): Unit

    Compares if two DataFrames are equal without caring about order of rows, by finding elements in one DataFrame that is not in the other.

    Compares if two DataFrames are equal without caring about order of rows, by finding elements in one DataFrame that is not in the other. The resulting DataFrame should be empty inferring the two DataFrames have the same elements. Does not compare the schema.

    Definition Classes
    DataFrameSuiteBaseLike
  12. def assertDataFrameEquals(expected: DataFrame, result: DataFrame, customShow: (DataFrame) ⇒ Unit = _.show()): Unit

    Compares if two DataFrames are equal, checks the schema and then if that matches checks if the rows are equal.

    Compares if two DataFrames are equal, checks the schema and then if that matches checks if the rows are equal.

    customShow

    unit function to customize the show method when dataframes are not equal. IE: df.show(false) or df.toJSON.show(false).

    Definition Classes
    DataFrameSuiteBaseLike
  13. def assertDataFrameNoOrderEquals(expected: DataFrame, result: DataFrame): Unit

    Compares if two DataFrames are equal without caring about order of rows, by finding elements in one DataFrame that is not in the other.

    Compares if two DataFrames are equal without caring about order of rows, by finding elements in one DataFrame that is not in the other. The resulting DataFrame should be empty inferring the two DataFrames have the same elements. Also verifies that the schema is identical.

    Definition Classes
    DataFrameSuiteBaseLike
  14. def assertDatasetApproximateEquals[U](expected: Dataset[U], result: Dataset[U], tol: Double, tolTimestamp: Duration, customShow: (DataFrame) ⇒ Unit = _.show())(implicit UCT: ClassTag[U]): Unit

    Compares if two Datasets are equal, Datasets should have the same type.

    Compares if two Datasets are equal, Datasets should have the same type. When comparing inexact fields uses tol & tolTimestamp.

    tol

    max acceptable tolerance for numeric (between(0, 1))

    tolTimestamp

    max acceptable timestamp tolerance.

    customShow

    unit function to customize the show method when dataframes are not equal. IE: df.show(false) or df.toJSON.show(false).

  15. def assertDatasetEquals[U](expected: Dataset[U], result: Dataset[U])(implicit UCT: ClassTag[U]): Unit

    Check if two Datasets are equals, Datasets should have the same type.

    Check if two Datasets are equals, Datasets should have the same type. This method could be customized by overriding equals method for the given class type.

  16. def assertSchemasEqual(expected: StructType, result: StructType): Unit

    Compare if two schemas are equal, ignoring autoGeneratedAlias magic

    Compare if two schemas are equal, ignoring autoGeneratedAlias magic

    Definition Classes
    DataFrameSuiteBaseLike
  17. def assertSmallDataFrameDataEquals(expected: DataFrame, result: DataFrame): Unit

    Compares if two DataFrames are equal without caring about order of rows, by finding elements in one DataFrame that is not in the other.

    Compares if two DataFrames are equal without caring about order of rows, by finding elements in one DataFrame that is not in the other. Similar to the function assertDataFrameDataEquals but for small DataFrame that can be collected in memory for the comparison.

    Definition Classes
    DataFrameSuiteBaseLike
  18. def builder(): Builder

    Constructs a configuration for hive or iceberg, where the metastore is located in a temp directory.

    Constructs a configuration for hive or iceberg, where the metastore is located in a temp directory.

    Definition Classes
    DataFrameSuiteBaseLike
  19. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native() @IntrinsicCandidate()
  20. def conf: SparkConf
    Definition Classes
    SparkContextProvider
  21. def enableHiveSupport: Boolean
    Attributes
    protected
    Definition Classes
    DataFrameSuiteBaseLike
  22. def enableIcebergSupport: Boolean
    Attributes
    protected
    Definition Classes
    DataFrameSuiteBaseLike
  23. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  24. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  25. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native() @IntrinsicCandidate()
  26. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native() @IntrinsicCandidate()
  27. val icebergWarehouse: String
    Definition Classes
    DataFrameSuiteBaseLike
  28. implicit def impSqlContext: SQLContext
    Attributes
    protected
    Definition Classes
    DataFrameSuiteBaseLike
  29. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  30. lazy val localMetastorePath: String
    Definition Classes
    DataFrameSuiteBaseLike
  31. lazy val localWarehousePath: String
    Definition Classes
    DataFrameSuiteBaseLike
  32. val maxUnequalRowsToShow: Int
    Definition Classes
    DataFrameSuiteBaseLike
  33. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  34. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @IntrinsicCandidate()
  35. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @IntrinsicCandidate()
  36. def setup(sc: SparkContext): Unit

    Setup work to be called when creating a new SparkContext.

    Setup work to be called when creating a new SparkContext. Default implementation currently sets a checkpoint directory.

    This _should_ be called by the context provider automatically.

    Definition Classes
    SparkContextProvider
  37. lazy val spark: SparkSession
    Definition Classes
    DataFrameSuiteBaseLike
    Annotations
    @transient()
  38. def sqlBeforeAllTestCases(): Unit
    Definition Classes
    DataFrameSuiteBaseLike
  39. lazy val sqlContext: SQLContext
    Definition Classes
    DataFrameSuiteBaseLike
    Annotations
    @transient()
  40. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  41. lazy val tempDir: File
    Definition Classes
    DataFrameSuiteBaseLike
  42. def toString(): String
    Definition Classes
    AnyRef → Any
  43. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  44. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  45. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Deprecated Value Members

  1. def assertDataFrameApproximateEquals(expected: DataFrame, result: DataFrame, tol: Double): Unit

    Compares if two DataFrames are equal, checks that the schemas are the same.

    Compares if two DataFrames are equal, checks that the schemas are the same. When comparing inexact fields uses tol.

    tol

    max acceptable tolerance for numeric (between(0, 1)) & timestamp (millis).

    Definition Classes
    DataFrameSuiteBaseLike
    Annotations
    @deprecated
    Deprecated

    (Since version 1.5.0) Use assertDataFrameApproximateEquals with timestamp tolerance

  2. def assertDatasetApproximateEquals[U](expected: Dataset[U], result: Dataset[U], tol: Double)(implicit UCT: ClassTag[U]): Unit

    Compares if two Datasets are equal, Datasets should have the same type.

    Compares if two Datasets are equal, Datasets should have the same type. When comparing inexact fields uses tol.

    tol

    max acceptable tolerance for numeric (between(0, 1)) & timestamp (millis).

    Annotations
    @deprecated
    Deprecated

    (Since version 1.5.0) Use assertDatasetApproximateEquals with timestamp tolerance

  3. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] ) @Deprecated
    Deprecated

Inherited from DataFrameSuiteBaseLike

Inherited from Serializable

Inherited from Serializable

Inherited from TestSuiteLike

Inherited from SparkContextProvider

Inherited from AnyRef

Inherited from Any

Ungrouped