com.holdenkarau.spark.testing

JavaStreamingSuiteBase

class JavaStreamingSuiteBase extends JavaSuiteBase with StreamingSuiteCommon

This is the base trait for Spark Streaming testsuite. This provides basic functionality to run user-defined set of input on user-defined stream operations, and verify the output matches as expected.

This implementation is designed to work with JUnit for java users.

Note: this always uses the manual clock to control Spark Streaming's batches.

Linear Supertypes
StreamingSuiteCommon, Logging, JavaSuiteBase, SharedJavaSparkContext, SparkContextProvider, AnyRef, Any
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Inherited
  1. JavaStreamingSuiteBase
  2. StreamingSuiteCommon
  3. Logging
  4. JavaSuiteBase
  5. SharedJavaSparkContext
  6. SparkContextProvider
  7. AnyRef
  8. Any
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Instance Constructors

  1. new JavaStreamingSuiteBase()

Value Members

  1. final def !=(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  2. final def !=(arg0: Any): Boolean

    Definition Classes
    Any
  3. final def ##(): Int

    Definition Classes
    AnyRef → Any
  4. final def ==(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  5. final def ==(arg0: Any): Boolean

    Definition Classes
    Any
  6. def actuallyWait: Boolean

    Definition Classes
    StreamingSuiteCommon
  7. def appID(): String

  8. final def asInstanceOf[T0]: T0

    Definition Classes
    Any
  9. def batchDuration: Duration

    Definition Classes
    StreamingSuiteCommon
  10. def beforeAllTestCasesHook(): Unit

    Attributes
    protected[com.holdenkarau.spark.testing]
    Definition Classes
    SharedJavaSparkContext
  11. lazy val checkpointDir: String

    Definition Classes
    StreamingSuiteCommon
  12. def clone(): AnyRef

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  13. def compareArrays[U](i1: Array[U], i2: Array[U]): Unit

    Utility wrapper around assertArrayEquals that resolves the types

    Utility wrapper around assertArrayEquals that resolves the types

    Definition Classes
    JavaSuiteBase
  14. def conf: SparkConf

    Definition Classes
    JavaStreamingSuiteBase → StreamingSuiteCommon → SharedJavaSparkContextSparkContextProvider
  15. final def eq(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  16. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any
  17. val eventuallyTimeout: Timeout

    Definition Classes
    StreamingSuiteCommon
  18. def finalize(): Unit

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  19. def framework: String

    Definition Classes
    StreamingSuiteCommon
  20. final def getClass(): Class[_]

    Definition Classes
    AnyRef → Any
  21. def hashCode(): Int

    Definition Classes
    AnyRef → Any
  22. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any
  23. def isTraceEnabled(): Boolean

    Attributes
    protected
    Definition Classes
    Logging
  24. def jsc(): JavaSparkContext

    Definition Classes
    SharedJavaSparkContext
  25. def log: Logger

    Attributes
    protected
    Definition Classes
    Logging
  26. def logDebug(msg: ⇒ String, throwable: Throwable): Unit

    Attributes
    protected
    Definition Classes
    Logging
  27. def logDebug(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging
  28. def logError(msg: ⇒ String, throwable: Throwable): Unit

    Attributes
    protected
    Definition Classes
    Logging
  29. def logError(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging
  30. def logInfo(msg: ⇒ String, throwable: Throwable): Unit

    Attributes
    protected
    Definition Classes
    Logging
  31. def logInfo(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging
  32. def logName: String

    Attributes
    protected
    Definition Classes
    Logging
  33. def logTrace(msg: ⇒ String, throwable: Throwable): Unit

    Attributes
    protected
    Definition Classes
    Logging
  34. def logTrace(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging
  35. def logWarning(msg: ⇒ String, throwable: Throwable): Unit

    Attributes
    protected
    Definition Classes
    Logging
  36. def logWarning(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging
  37. def master: String

    Definition Classes
    StreamingSuiteCommon
  38. def maxWaitTimeMillis: Int

    Definition Classes
    StreamingSuiteCommon
  39. final def ne(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  40. final def notify(): Unit

    Definition Classes
    AnyRef
  41. final def notifyAll(): Unit

    Definition Classes
    AnyRef
  42. def numInputPartitions: Int

    Definition Classes
    StreamingSuiteCommon
  43. def runBefore(): Unit

    Definition Classes
    SharedJavaSparkContext
  44. def sc(): SparkContext

  45. 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
    SharedJavaSparkContextSparkContextProvider
  46. final def synchronized[T0](arg0: ⇒ T0): T0

    Definition Classes
    AnyRef
  47. def testOperation[U, V, W](input1: List[List[U]], input2: List[List[V]], operation: Function2[JavaDStream[U], JavaDStream[V], JavaDStream[W]], expectedOutput: List[List[W]], ordered: Boolean): Unit

    Test binary DStream operation with two lists of inputs, with number of batches to run same as the number of input values.

    Test binary DStream operation with two lists of inputs, with number of batches to run same as the number of input values. The size of the two input lists should be equal.

    Each input micro-batch is a list of values or as null to simulate empty batch.

    input1

    First sequence of input collections

    input2

    Second sequence of input collections

    operation

    Binary DStream operation to be applied to the 2 inputs

    expectedOutput

    Sequence of expected output collections

    ordered

    Compare output values with expected output values within the same output batch ordered or unOrdered. Comparing doubles may not work well in case of unordered.

  48. def testOperation[U, V, W](input1: List[List[U]], input2: List[List[V]], operation: Function2[JavaDStream[U], JavaDStream[V], JavaDStream[W]], expectedOutput: List[List[W]]): Unit

    Test binary DStream operation with two lists of inputs, with number of batches to run same as the number of input values.

    Test binary DStream operation with two lists of inputs, with number of batches to run same as the number of input values. The size of the two input lists should be equal.

    Each input micro-batch is a list of values or as null to simulate empty batch.

    input1

    First sequence of input collections

    input2

    Second sequence of input collections

    operation

    Binary DStream operation to be applied to the 2 inputs

    expectedOutput

    Sequence of expected output collections

  49. def testOperation[U, V](input: List[List[U]], operation: Function[JavaDStream[U], JavaDStream[V]], expectedOutput: List[List[V]], ordered: Boolean): Unit

    Test unary DStream operation with a list of inputs, with number of batches to run same as the number of input values.

    Test unary DStream operation with a list of inputs, with number of batches to run same as the number of input values.

    Each input micro-batch is a list of values or as null to simulate empty batch.

    input

    Sequence of input collections

    operation

    Binary DStream operation to be applied to the 2 inputs

    expectedOutput

    Sequence of expected output collections

    ordered

    Compare output values with expected output values within the same output batch ordered or unordered. Comparing doubles may not work well in case of unordered.

  50. def testOperation[U, V](input: List[List[U]], operation: Function[JavaDStream[U], JavaDStream[V]], expectedOutput: List[List[V]]): Unit

    Test unary DStream operation with a list of inputs, with number of batches to run same as the number of input values.

    Test unary DStream operation with a list of inputs, with number of batches to run same as the number of input values.

    Each input micro-batch is a list of values or as null to simulate empty batch.

    input

    Sequence of input collections

    operation

    Binary DStream operation to be applied to the 2 inputs

    expectedOutput

    Sequence of expected output collections

  51. def toString(): String

    Definition Classes
    AnyRef → Any
  52. def useManualClock: Boolean

    Definition Classes
    StreamingSuiteCommon
  53. def verifyOutput[V](output: Seq[Seq[V]], expectedOutput: Seq[Seq[V]], ordered: Boolean)(implicit arg0: ClassTag[V]): Unit

    Verify whether the output values after running a DStream operation is same as the expected output values, by comparing the output collections either as lists (order matters) or sets (order does not matter)

  54. final def wait(arg0: Long, arg1: Int): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  55. final def wait(arg0: Long): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  56. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from StreamingSuiteCommon

Inherited from Logging

Inherited from JavaSuiteBase

Inherited from SharedJavaSparkContext

Inherited from SparkContextProvider

Inherited from AnyRef

Inherited from Any

Ungrouped