TimeSeriesBuffer

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: Any): Boolean

def add(v: Double): Unit

Add a constant value to all positions of this buffer.

def add(tags: Map[String, String], block: Block): Int

def add(ts: TimeSeriesBuffer): Unit

Add the corresponding positions of the two buffers.

def apply(t: Long): Double

final def asInstanceOf[T0]: T0

def binaryOp(ts: TimeSeries, labelFmt: String, f: BinaryOp): TimeSeries

def blend(ts: TimeSeries): TimeSeries

def bounded(s: Long, e: Long): ArrayTimeSeq

def canEqual(other: Any): Boolean

def clone(): AnyRef

def consolidate(multiple: Int, cf: ConsolidationFunction): TimeSeriesBuffer

Returns a new buffer with values consolidated to a larger step size.

def consolidate(step: Long, cf: ConsolidationFunction): TimeSeries

def copy: TimeSeriesBuffer

Create a deep copy of this buffer.

def count(tags: Map[String, String], block: Block): Int

def count(ts: TimeSeriesBuffer): Unit

Updates each position by 1 if the corresponding position in the other buffer is a valid number, i.e., is not equal NaN.

val data: ArrayTimeSeq

def datapoint(timestamp: Long): Datapoint

def divide(v: Double): Unit

Divide a constant value to all positions of this buffer.

def divide(ts: TimeSeriesBuffer): Unit

Divide the corresponding positions of the two buffers.

def dsType: DsType

final def eq(arg0: AnyRef): Boolean

def equals(other: Any): Boolean

def foreach(s: Long, e: Long)(f: (Long, Double) ⇒ Unit): Unit

Fast loop with no intermediate object creation.

def foreach(f: (String, String) ⇒ Unit): Unit

Code that just needs to iterate over all tags should use this method.

final def getClass(): Class[_]

def getValue(timestamp: Long): Double

def hashCode(): Int

lazy val id: ItemId

Unique id based on the tags.

def idString: String

Standard string representation of the id.

def initCount(): Unit

Setup this buffer array as a count.

def isAllNaN: Boolean

Returns true if the buffer is all NaN values.

def isExpired: Boolean

Returns true if the item is expired and no data is available.

final def isInstanceOf[T0]: Boolean

def label: String

def mapTimeSeq(f: (TimeSeq) ⇒ TimeSeq): TimeSeries

def mapValues(f: (Double) ⇒ Double): TimeSeq

def max(tags: Map[String, String], block: Block): Int

def max(ts: TimeSeriesBuffer): Unit

Updates each position we the max value between the two buffers.

def merge(ts: TimeSeriesBuffer): Unit

Merge with another metric buffer.

def min(tags: Map[String, String], block: Block): Int

def min(ts: TimeSeriesBuffer): Unit

Updates each position we the min value between the two buffers.

def multiply(v: Double): Unit

Multiply a constant value to all positions of this buffer.

def multiply(ts: TimeSeriesBuffer): Unit

Multiply the corresponding positions of the two buffers.

final def ne(arg0: AnyRef): Boolean

def normalize(step: Long, start: Long, size: Int): TimeSeriesBuffer

Returns a new buffer normalized to the specified settings.

final def notify(): Unit

final def notifyAll(): Unit

def offset(dur: Long): TimeSeries

def start: Long

def step: Long

def subtract(v: Double): Unit

Subtract a constant value to all positions of this buffer.

def subtract(ts: TimeSeriesBuffer): Unit

Subtract the corresponding positions of the two buffers.

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

var tags: Map[String, String]

The tags associated with this item.

def toString(): String

def unConsolidate(s: Long, e: Long, step: Long): TimeSeriesBuffer

Returns a new buffer with values un-consolidated to a smaller step size.

def unaryOp(labelFmt: String, f: (Double) ⇒ Double): TimeSeries

def values: Array[Double]

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

final def wait(arg0: Long): Unit

final def wait(): Unit

def withLabel(s: String): TimeSeries

def withTags(ts: Map[String, String]): TimeSeries

def finalize(): Unit