final case class HistogramDataPoint(attributes: Seq[KeyValue] = _root_.scala.Seq.empty, startTimeUnixNano: Long = 0L, timeUnixNano: Long = 0L, count: Long = 0L, sum: Option[Double] = _root_.scala.None, bucketCounts: Seq[Long] = _root_.scala.Seq.empty, explicitBounds: Seq[Double] = _root_.scala.Seq.empty, exemplars: Seq[Exemplar] = _root_.scala.Seq.empty, flags: Int = 0, min: Option[Double] = _root_.scala.None, max: Option[Double] = _root_.scala.None, unknownFields: UnknownFieldSet = ...) extends GeneratedMessage with Updatable[HistogramDataPoint] with Product with Serializable

HistogramDataPoint is a single data point in a timeseries that describes the time-varying values of a Histogram. A Histogram contains summary statistics for a population of values, it may optionally contain the distribution of those values across a set of buckets.

If the histogram contains the distribution of values, then both "explicit_bounds" and "bucket counts" fields must be defined. If the histogram does not contain the distribution of values, then both "explicit_bounds" and "bucket_counts" must be omitted and only "count" and "sum" are known.

attributes

The set of key/value pairs that uniquely identify the timeseries from where this point belongs. The list may be empty (may contain 0 elements). Attribute keys MUST be unique (it is not allowed to have more than one attribute with the same key).

startTimeUnixNano

StartTimeUnixNano is optional but strongly encouraged, see the the detailed comments above Metric. Value is UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January 1970.

timeUnixNano

TimeUnixNano is required, see the detailed comments above Metric. Value is UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January 1970.

count

count is the number of values in the population. Must be non-negative. This value must be equal to the sum of the "count" fields in buckets if a histogram is provided.

sum

sum of the values in the population. If count is zero then this field must be zero. Note: Sum should only be filled out when measuring non-negative discrete events, and is assumed to be monotonic over the values of these events. Negative events *can* be recorded, but sum should not be filled out when doing so. This is specifically to enforce compatibility w/ OpenMetrics, see: https://github.com/OpenObservability/OpenMetrics/blob/main/specification/OpenMetrics.md#histogram

bucketCounts

bucket_counts is an optional field contains the count values of histogram for each bucket. The sum of the bucket_counts must equal the value in the count field. The number of elements in bucket_counts array must be by one greater than the number of elements in explicit_bounds array.

explicitBounds

explicit_bounds specifies buckets with explicitly defined bounds for values. The boundaries for bucket at index i are: (-infinity, explicit_bounds[i]] for i == 0 (explicit_bounds[i-1], explicit_bounds[i]] for 0 < i < size(explicit_bounds) (explicit_bounds[i-1], +infinity) for i == size(explicit_bounds) The values in the explicit_bounds array must be strictly increasing. Histogram buckets are inclusive of their upper boundary, except the last bucket where the boundary is at infinity. This format is intentionally compatible with the OpenMetrics histogram definition.

exemplars

(Optional) List of exemplars collected from measurements that were used to form the data point

flags

Flags that apply to this specific data point. See DataPointFlags for the available flags and their meaning.

min

min is the minimum value over (start_time, end_time].

max

max is the maximum value over (start_time, end_time].

Annotations
@SerialVersionUID()
Linear Supertypes
Updatable[HistogramDataPoint], GeneratedMessage, Serializable, Serializable, Product, Equals, AnyRef, Any
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  1. HistogramDataPoint
  2. Updatable
  3. GeneratedMessage
  4. Serializable
  5. Serializable
  6. Product
  7. Equals
  8. AnyRef
  9. Any
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Instance Constructors

  1. new HistogramDataPoint(attributes: Seq[KeyValue] = _root_.scala.Seq.empty, startTimeUnixNano: Long = 0L, timeUnixNano: Long = 0L, count: Long = 0L, sum: Option[Double] = _root_.scala.None, bucketCounts: Seq[Long] = _root_.scala.Seq.empty, explicitBounds: Seq[Double] = _root_.scala.Seq.empty, exemplars: Seq[Exemplar] = _root_.scala.Seq.empty, flags: Int = 0, min: Option[Double] = _root_.scala.None, max: Option[Double] = _root_.scala.None, unknownFields: UnknownFieldSet = ...)

    attributes

    The set of key/value pairs that uniquely identify the timeseries from where this point belongs. The list may be empty (may contain 0 elements). Attribute keys MUST be unique (it is not allowed to have more than one attribute with the same key).

    startTimeUnixNano

    StartTimeUnixNano is optional but strongly encouraged, see the the detailed comments above Metric. Value is UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January 1970.

    timeUnixNano

    TimeUnixNano is required, see the detailed comments above Metric. Value is UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January 1970.

    count

    count is the number of values in the population. Must be non-negative. This value must be equal to the sum of the "count" fields in buckets if a histogram is provided.

    sum

    sum of the values in the population. If count is zero then this field must be zero. Note: Sum should only be filled out when measuring non-negative discrete events, and is assumed to be monotonic over the values of these events. Negative events *can* be recorded, but sum should not be filled out when doing so. This is specifically to enforce compatibility w/ OpenMetrics, see: https://github.com/OpenObservability/OpenMetrics/blob/main/specification/OpenMetrics.md#histogram

    bucketCounts

    bucket_counts is an optional field contains the count values of histogram for each bucket. The sum of the bucket_counts must equal the value in the count field. The number of elements in bucket_counts array must be by one greater than the number of elements in explicit_bounds array.

    explicitBounds

    explicit_bounds specifies buckets with explicitly defined bounds for values. The boundaries for bucket at index i are: (-infinity, explicit_bounds[i]] for i == 0 (explicit_bounds[i-1], explicit_bounds[i]] for 0 < i < size(explicit_bounds) (explicit_bounds[i-1], +infinity) for i == size(explicit_bounds) The values in the explicit_bounds array must be strictly increasing. Histogram buckets are inclusive of their upper boundary, except the last bucket where the boundary is at infinity. This format is intentionally compatible with the OpenMetrics histogram definition.

    exemplars

    (Optional) List of exemplars collected from measurements that were used to form the data point

    flags

    Flags that apply to this specific data point. See DataPointFlags for the available flags and their meaning.

    min

    min is the minimum value over (start_time, end_time].

    max

    max is the maximum value over (start_time, end_time].

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 addAllAttributes(__vs: Iterable[KeyValue]): HistogramDataPoint
  5. def addAllBucketCounts(__vs: Iterable[Long]): HistogramDataPoint
  6. def addAllExemplars(__vs: Iterable[Exemplar]): HistogramDataPoint
  7. def addAllExplicitBounds(__vs: Iterable[Double]): HistogramDataPoint
  8. def addAttributes(__vs: KeyValue*): HistogramDataPoint
  9. def addBucketCounts(__vs: Long*): HistogramDataPoint
  10. def addExemplars(__vs: Exemplar*): HistogramDataPoint
  11. def addExplicitBounds(__vs: Double*): HistogramDataPoint
  12. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  13. val attributes: Seq[KeyValue]
  14. val bucketCounts: Seq[Long]
  15. def clearAttributes: HistogramDataPoint
  16. def clearBucketCounts: HistogramDataPoint
  17. def clearExemplars: HistogramDataPoint
  18. def clearExplicitBounds: HistogramDataPoint
  19. def clearMax: HistogramDataPoint
  20. def clearMin: HistogramDataPoint
  21. def clearSum: HistogramDataPoint
  22. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native() @HotSpotIntrinsicCandidate()
  23. def companion: HistogramDataPoint.type
    Definition Classes
    HistogramDataPoint → GeneratedMessage
  24. val count: Long
  25. def discardUnknownFields: HistogramDataPoint
  26. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  27. val exemplars: Seq[Exemplar]
  28. val explicitBounds: Seq[Double]
  29. val flags: Int
  30. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  31. def getField(__field: FieldDescriptor): PValue
    Definition Classes
    HistogramDataPoint → GeneratedMessage
  32. def getFieldByNumber(__fieldNumber: Int): Any
    Definition Classes
    HistogramDataPoint → GeneratedMessage
  33. def getMax: Double
  34. def getMin: Double
  35. def getSum: Double
  36. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  37. val max: Option[Double]
  38. val min: Option[Double]
  39. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  40. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  41. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  42. def serializedSize: Int
    Definition Classes
    HistogramDataPoint → GeneratedMessage
  43. val startTimeUnixNano: Long
  44. val sum: Option[Double]
  45. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  46. val timeUnixNano: Long
  47. final def toByteArray: Array[Byte]
    Definition Classes
    GeneratedMessage
  48. final def toByteString: ByteString
    Definition Classes
    GeneratedMessage
  49. final def toPMessage: PMessage
    Definition Classes
    GeneratedMessage
  50. def toProtoString: String
    Definition Classes
    HistogramDataPoint → GeneratedMessage
  51. val unknownFields: UnknownFieldSet
  52. def update(ms: (Lens[HistogramDataPoint, HistogramDataPoint]) ⇒ Mutation[HistogramDataPoint]*): HistogramDataPoint
    Definition Classes
    Updatable
  53. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  54. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  55. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  56. def withAttributes(__v: Seq[KeyValue]): HistogramDataPoint
  57. def withBucketCounts(__v: Seq[Long]): HistogramDataPoint
  58. def withCount(__v: Long): HistogramDataPoint
  59. def withExemplars(__v: Seq[Exemplar]): HistogramDataPoint
  60. def withExplicitBounds(__v: Seq[Double]): HistogramDataPoint
  61. def withFlags(__v: Int): HistogramDataPoint
  62. def withMax(__v: Double): HistogramDataPoint
  63. def withMin(__v: Double): HistogramDataPoint
  64. def withStartTimeUnixNano(__v: Long): HistogramDataPoint
  65. def withSum(__v: Double): HistogramDataPoint
  66. def withTimeUnixNano(__v: Long): HistogramDataPoint
  67. def withUnknownFields(__v: UnknownFieldSet): HistogramDataPoint
  68. final def writeDelimitedTo(output: OutputStream): Unit
    Definition Classes
    GeneratedMessage
  69. def writeTo(_output__: CodedOutputStream): Unit
    Definition Classes
    HistogramDataPoint → GeneratedMessage
  70. final def writeTo(output: OutputStream): Unit
    Definition Classes
    GeneratedMessage

Deprecated Value Members

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

Inherited from Updatable[HistogramDataPoint]

Inherited from GeneratedMessage

Inherited from Serializable

Inherited from Serializable

Inherited from Product

Inherited from Equals

Inherited from AnyRef

Inherited from Any

Ungrouped