MemoryStream

Instance Constructors

new MemoryStream(id: Int, sqlContext: SQLContext)(implicit arg0: Encoder[A])

Value Members

final def !=(arg0: Any): Boolean

Definition Classes
AnyRef → Any
final def ##(): Int

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

Definition Classes
AnyRef → Any
def addData(data: TraversableOnce[A]): Offset
def addData(data: A*): Offset
final def asInstanceOf[T0]: T0

Definition Classes
Any
val batches: ListBuffer[Dataset[A]]

All batches from lastCommittedOffset + 1 to currentOffset, inclusive.
All batches from lastCommittedOffset + 1 to currentOffset, inclusive. Stored in a ListBuffer to facilitate removing committed batches.

Attributes
protected
def clone(): AnyRef

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( ... )
def commit(end: Offset): Unit

Informs the source that Spark has completed processing all data for offsets less than or equal to end and will only request offsets greater than end in the future.
Informs the source that Spark has completed processing all data for offsets less than or equal to end and will only request offsets greater than end in the future.

Definition Classes
MemoryStream → Source
var currentOffset: LongOffset

Attributes
protected
val encoder: ExpressionEncoder[A]

Attributes
protected
final def eq(arg0: AnyRef): Boolean

Definition Classes
AnyRef
def finalize(): Unit

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( classOf[java.lang.Throwable] )
def getBatch(start: Option[Offset], end: Offset): DataFrame

Returns the data that is between the offsets (start, end].
Returns the data that is between the offsets (start, end]. When start is None, then the batch should begin with the first record. This method must always return the same data for a particular start and end pair; even after the Source has been restarted on a different node.
Higher layers will always call this method with a value of start greater than or equal to the last value passed to commit and a value of end less than or equal to the last value returned by getOffset
It is possible for the Offset type to be a SerializedOffset when it was obtained from the log. Moreover, StreamExecution only compares the Offset JSON representation to determine if the two objects are equal. This could have ramifications when upgrading Offset JSON formats i.e., two equivalent Offset objects could differ between version. Consequently, StreamExecution may call this method with two such equivalent Offset objects. In which case, the Source should return an empty DataFrame

Definition Classes
MemoryStream → Source
final def getClass(): Class[_]

Definition Classes
AnyRef → Any
def getOffset: Option[Offset]

Returns the maximum available offset for this source.
Returns the maximum available offset for this source. Returns None if this source has never received any data.

Definition Classes
MemoryStream → Source
val id: Int
def initializeLogIfNecessary(isInterpreter: Boolean): Unit

Attributes
protected
Definition Classes
Logging
final def isInstanceOf[T0]: Boolean

Definition Classes
Any
def isTraceEnabled(): Boolean

Attributes
protected
Definition Classes
Logging
var lastOffsetCommitted: LongOffset

Last offset that was discarded, or -1 if no commits have occurred.
Last offset that was discarded, or -1 if no commits have occurred. Note that the value -1 is used in calculations below and isn't just an arbitrary constant.

Attributes
protected
def log: Logger

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

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

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

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

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

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

Attributes
protected
Definition Classes
Logging
def logName: String

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

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

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

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

Attributes
protected
Definition Classes
Logging
val logicalPlan: StreamingExecutionRelation

Attributes
protected
final def ne(arg0: AnyRef): Boolean

Definition Classes
AnyRef
final def notify(): Unit

Definition Classes
AnyRef
final def notifyAll(): Unit

Definition Classes
AnyRef
val output: Seq[Attribute]

Attributes
protected
def reset(): Unit
def schema: StructType

Returns the schema of the data from this source
Returns the schema of the data from this source

Definition Classes
MemoryStream → Source
val sqlContext: SQLContext
def stop(): Unit

Stop this source and free any resources it has allocated.
Stop this source and free any resources it has allocated.

Definition Classes
MemoryStream → Source
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef
def toDF(): DataFrame
def toDS(): Dataset[A]
def toString(): String

Definition Classes
MemoryStream → AnyRef → Any
final def wait(): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
final def wait(arg0: Long, arg1: Int): Unit

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

Definition Classes
AnyRef
Annotations
@throws( ... )

Related Docs: object MemoryStream | package streaming

case class MemoryStream[A](id: Int, sqlContext: SQLContext)(implicit evidence$2: Encoder[A]) extends Source with Logging with Product with Serializable

Instance Constructors

new MemoryStream(id: Int, sqlContext: SQLContext)(implicit arg0: Encoder[A])

Value Members

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: Any): Boolean

def addData(data: TraversableOnce[A]): Offset

def addData(data: A*): Offset

final def asInstanceOf[T0]: T0

val batches: ListBuffer[Dataset[A]]

def clone(): AnyRef

def commit(end: Offset): Unit

var currentOffset: LongOffset

val encoder: ExpressionEncoder[A]

final def eq(arg0: AnyRef): Boolean

def finalize(): Unit

def getBatch(start: Option[Offset], end: Offset): DataFrame

final def getClass(): Class[_]

def getOffset: Option[Offset]

val id: Int

def initializeLogIfNecessary(isInterpreter: Boolean): Unit

final def isInstanceOf[T0]: Boolean

def isTraceEnabled(): Boolean

var lastOffsetCommitted: LongOffset

def log: Logger

def logDebug(msg: ⇒ String, throwable: Throwable): Unit

def logDebug(msg: ⇒ String): Unit

def logError(msg: ⇒ String, throwable: Throwable): Unit

def logError(msg: ⇒ String): Unit

def logInfo(msg: ⇒ String, throwable: Throwable): Unit

def logInfo(msg: ⇒ String): Unit

def logName: String

def logTrace(msg: ⇒ String, throwable: Throwable): Unit

def logTrace(msg: ⇒ String): Unit

def logWarning(msg: ⇒ String, throwable: Throwable): Unit

def logWarning(msg: ⇒ String): Unit

val logicalPlan: StreamingExecutionRelation

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

val output: Seq[Attribute]

def reset(): Unit

def schema: StructType

val sqlContext: SQLContext

def stop(): Unit

final def synchronized[T0](arg0: ⇒ T0): T0

def toDF(): DataFrame

def toDS(): Dataset[A]

def toString(): String

final def wait(): Unit

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

final def wait(arg0: Long): Unit

Inherited from Serializable

Inherited from Serializable

Inherited from Product

Inherited from Equals

Inherited from Logging

Inherited from Source

Inherited from AnyRef

Inherited from Any

Ungrouped