Class Aggregation.Builder (3.4.1)

Describes how to combine multiple time series to provide a different view of the data. Aggregation of time series is done in two steps. First, each time series in the set is aligned to the same time interval boundaries, then the set of time series is optionally reduced in number. Alignment consists of applying the per_series_aligner operation to each time series after its data has been divided into regular alignment_period time intervals. This process takes all of the data points in an alignment period, applies a mathematical transformation such as averaging, minimum, maximum, delta, etc., and converts them into a single data point per period. Reduction is when the aligned and transformed time series can optionally be combined, reducing the number of time series through similar mathematical transformations. Reduction involves applying a cross_series_reducer to all the time series, optionally sorting the time series into subsets with group_by_fields, and applying the reducer to each subset. The raw time series data can contain a huge amount of information from multiple sources. Alignment and reduction transforms this mass of data into a more manageable and representative collection of data, for example "the 95% latency across the average of all tasks in a cluster". This representative data can be more easily graphed and comprehended, and the individual time series data is still available for later drilldown. For more details, see Filtering and aggregation.

Protobuf type google.monitoring.v3.Aggregation

The set of fields to preserve when cross_series_reducer is specified. The group_by_fields determine how the time series are partitioned into subsets prior to applying the aggregation operation. Each subset contains time series that have the same value for each of the grouping fields. Each individual time series is a member of exactly one subset. The cross_series_reducer is applied to each subset of time series. It is not possible to reduce across different resource types, so this field implicitly contains resource.type. Fields not specified in group_by_fields are aggregated away. If group_by_fields is not specified and all the time series have the same resource type, then the time series are aggregated into a single output time series. If cross_series_reducer is not defined, this field is ignored.

repeated string group_by_fields = 5;

The set of fields to preserve when cross_series_reducer is specified. The group_by_fields determine how the time series are partitioned into subsets prior to applying the aggregation operation. Each subset contains time series that have the same value for each of the grouping fields. Each individual time series is a member of exactly one subset. The cross_series_reducer is applied to each subset of time series. It is not possible to reduce across different resource types, so this field implicitly contains resource.type. Fields not specified in group_by_fields are aggregated away. If group_by_fields is not specified and all the time series have the same resource type, then the time series are aggregated into a single output time series. If cross_series_reducer is not defined, this field is ignored.

repeated string group_by_fields = 5;

The set of fields to preserve when cross_series_reducer is specified. The group_by_fields determine how the time series are partitioned into subsets prior to applying the aggregation operation. Each subset contains time series that have the same value for each of the grouping fields. Each individual time series is a member of exactly one subset. The cross_series_reducer is applied to each subset of time series. It is not possible to reduce across different resource types, so this field implicitly contains resource.type. Fields not specified in group_by_fields are aggregated away. If group_by_fields is not specified and all the time series have the same resource type, then the time series are aggregated into a single output time series. If cross_series_reducer is not defined, this field is ignored.

repeated string group_by_fields = 5;

The alignment_period specifies a time interval, in seconds, that is used to divide the data in all the time series into consistent blocks of time. This will be done before the per-series aligner can be applied to the data. The value must be at least 60 seconds. If a per-series aligner other than ALIGN_NONE is specified, this field is required or an error is returned. If no per-series aligner is specified, or the aligner ALIGN_NONE is specified, then this field is ignored. The maximum value of the alignment_period is 104 weeks (2 years) for charts, and 90,000 seconds (25 hours) for alerting policies.

.google.protobuf.Duration alignment_period = 1;

The reduction operation to be used to combine time series into a single time series, where the value of each data point in the resulting series is a function of all the already aligned values in the input time series. Not all reducer operations can be applied to all time series. The valid choices depend on the metric_kind and the value_type of the original time series. Reduction can yield a time series with a different metric_kind or value_type than the input time series. Time series data must first be aligned (see per_series_aligner) in order to perform cross-time series reduction. If cross_series_reducer is specified, then per_series_aligner must be specified, and must not be ALIGN_NONE. An alignment_period must also be specified; otherwise, an error is returned.

.google.monitoring.v3.Aggregation.Reducer cross_series_reducer = 4;

The set of fields to preserve when cross_series_reducer is specified. The group_by_fields determine how the time series are partitioned into subsets prior to applying the aggregation operation. Each subset contains time series that have the same value for each of the grouping fields. Each individual time series is a member of exactly one subset. The cross_series_reducer is applied to each subset of time series. It is not possible to reduce across different resource types, so this field implicitly contains resource.type. Fields not specified in group_by_fields are aggregated away. If group_by_fields is not specified and all the time series have the same resource type, then the time series are aggregated into a single output time series. If cross_series_reducer is not defined, this field is ignored.

repeated string group_by_fields = 5;

An Aligner describes how to bring the data points in a single time series into temporal alignment. Except for ALIGN_NONE, all alignments cause all the data points in an alignment_period to be mathematically grouped together, resulting in a single data point for each alignment_period with end timestamp at the end of the period. Not all alignment operations may be applied to all time series. The valid choices depend on the metric_kind and value_type of the original time series. Alignment can change the metric_kind or the value_type of the time series. Time series data must be aligned in order to perform cross-time series reduction. If cross_series_reducer is specified, then per_series_aligner must be specified and not equal to ALIGN_NONE and alignment_period must be specified; otherwise, an error is returned.

.google.monitoring.v3.Aggregation.Aligner per_series_aligner = 2;

The alignment_period specifies a time interval, in seconds, that is used to divide the data in all the time series into consistent blocks of time. This will be done before the per-series aligner can be applied to the data. The value must be at least 60 seconds. If a per-series aligner other than ALIGN_NONE is specified, this field is required or an error is returned. If no per-series aligner is specified, or the aligner ALIGN_NONE is specified, then this field is ignored. The maximum value of the alignment_period is 104 weeks (2 years) for charts, and 90,000 seconds (25 hours) for alerting policies.

.google.protobuf.Duration alignment_period = 1;

The alignment_period specifies a time interval, in seconds, that is used to divide the data in all the time series into consistent blocks of time. This will be done before the per-series aligner can be applied to the data. The value must be at least 60 seconds. If a per-series aligner other than ALIGN_NONE is specified, this field is required or an error is returned. If no per-series aligner is specified, or the aligner ALIGN_NONE is specified, then this field is ignored. The maximum value of the alignment_period is 104 weeks (2 years) for charts, and 90,000 seconds (25 hours) for alerting policies.

.google.protobuf.Duration alignment_period = 1;

The alignment_period specifies a time interval, in seconds, that is used to divide the data in all the time series into consistent blocks of time. This will be done before the per-series aligner can be applied to the data. The value must be at least 60 seconds. If a per-series aligner other than ALIGN_NONE is specified, this field is required or an error is returned. If no per-series aligner is specified, or the aligner ALIGN_NONE is specified, then this field is ignored. The maximum value of the alignment_period is 104 weeks (2 years) for charts, and 90,000 seconds (25 hours) for alerting policies.

.google.protobuf.Duration alignment_period = 1;

The reduction operation to be used to combine time series into a single time series, where the value of each data point in the resulting series is a function of all the already aligned values in the input time series. Not all reducer operations can be applied to all time series. The valid choices depend on the metric_kind and the value_type of the original time series. Reduction can yield a time series with a different metric_kind or value_type than the input time series. Time series data must first be aligned (see per_series_aligner) in order to perform cross-time series reduction. If cross_series_reducer is specified, then per_series_aligner must be specified, and must not be ALIGN_NONE. An alignment_period must also be specified; otherwise, an error is returned.

.google.monitoring.v3.Aggregation.Reducer cross_series_reducer = 4;

The reduction operation to be used to combine time series into a single time series, where the value of each data point in the resulting series is a function of all the already aligned values in the input time series. Not all reducer operations can be applied to all time series. The valid choices depend on the metric_kind and the value_type of the original time series. Reduction can yield a time series with a different metric_kind or value_type than the input time series. Time series data must first be aligned (see per_series_aligner) in order to perform cross-time series reduction. If cross_series_reducer is specified, then per_series_aligner must be specified, and must not be ALIGN_NONE. An alignment_period must also be specified; otherwise, an error is returned.

.google.monitoring.v3.Aggregation.Reducer cross_series_reducer = 4;

The set of fields to preserve when cross_series_reducer is specified. The group_by_fields determine how the time series are partitioned into subsets prior to applying the aggregation operation. Each subset contains time series that have the same value for each of the grouping fields. Each individual time series is a member of exactly one subset. The cross_series_reducer is applied to each subset of time series. It is not possible to reduce across different resource types, so this field implicitly contains resource.type. Fields not specified in group_by_fields are aggregated away. If group_by_fields is not specified and all the time series have the same resource type, then the time series are aggregated into a single output time series. If cross_series_reducer is not defined, this field is ignored.

repeated string group_by_fields = 5;

The set of fields to preserve when cross_series_reducer is specified. The group_by_fields determine how the time series are partitioned into subsets prior to applying the aggregation operation. Each subset contains time series that have the same value for each of the grouping fields. Each individual time series is a member of exactly one subset. The cross_series_reducer is applied to each subset of time series. It is not possible to reduce across different resource types, so this field implicitly contains resource.type. Fields not specified in group_by_fields are aggregated away. If group_by_fields is not specified and all the time series have the same resource type, then the time series are aggregated into a single output time series. If cross_series_reducer is not defined, this field is ignored.

repeated string group_by_fields = 5;

The set of fields to preserve when cross_series_reducer is specified. The group_by_fields determine how the time series are partitioned into subsets prior to applying the aggregation operation. Each subset contains time series that have the same value for each of the grouping fields. Each individual time series is a member of exactly one subset. The cross_series_reducer is applied to each subset of time series. It is not possible to reduce across different resource types, so this field implicitly contains resource.type. Fields not specified in group_by_fields are aggregated away. If group_by_fields is not specified and all the time series have the same resource type, then the time series are aggregated into a single output time series. If cross_series_reducer is not defined, this field is ignored.

repeated string group_by_fields = 5;

The set of fields to preserve when cross_series_reducer is specified. The group_by_fields determine how the time series are partitioned into subsets prior to applying the aggregation operation. Each subset contains time series that have the same value for each of the grouping fields. Each individual time series is a member of exactly one subset. The cross_series_reducer is applied to each subset of time series. It is not possible to reduce across different resource types, so this field implicitly contains resource.type. Fields not specified in group_by_fields are aggregated away. If group_by_fields is not specified and all the time series have the same resource type, then the time series are aggregated into a single output time series. If cross_series_reducer is not defined, this field is ignored.

repeated string group_by_fields = 5;

An Aligner describes how to bring the data points in a single time series into temporal alignment. Except for ALIGN_NONE, all alignments cause all the data points in an alignment_period to be mathematically grouped together, resulting in a single data point for each alignment_period with end timestamp at the end of the period. Not all alignment operations may be applied to all time series. The valid choices depend on the metric_kind and value_type of the original time series. Alignment can change the metric_kind or the value_type of the time series. Time series data must be aligned in order to perform cross-time series reduction. If cross_series_reducer is specified, then per_series_aligner must be specified and not equal to ALIGN_NONE and alignment_period must be specified; otherwise, an error is returned.

.google.monitoring.v3.Aggregation.Aligner per_series_aligner = 2;

An Aligner describes how to bring the data points in a single time series into temporal alignment. Except for ALIGN_NONE, all alignments cause all the data points in an alignment_period to be mathematically grouped together, resulting in a single data point for each alignment_period with end timestamp at the end of the period. Not all alignment operations may be applied to all time series. The valid choices depend on the metric_kind and value_type of the original time series. Alignment can change the metric_kind or the value_type of the time series. Time series data must be aligned in order to perform cross-time series reduction. If cross_series_reducer is specified, then per_series_aligner must be specified and not equal to ALIGN_NONE and alignment_period must be specified; otherwise, an error is returned.

.google.monitoring.v3.Aggregation.Aligner per_series_aligner = 2;

The alignment_period specifies a time interval, in seconds, that is used to divide the data in all the time series into consistent blocks of time. This will be done before the per-series aligner can be applied to the data. The value must be at least 60 seconds. If a per-series aligner other than ALIGN_NONE is specified, this field is required or an error is returned. If no per-series aligner is specified, or the aligner ALIGN_NONE is specified, then this field is ignored. The maximum value of the alignment_period is 104 weeks (2 years) for charts, and 90,000 seconds (25 hours) for alerting policies.

.google.protobuf.Duration alignment_period = 1;

The alignment_period specifies a time interval, in seconds, that is used to divide the data in all the time series into consistent blocks of time. This will be done before the per-series aligner can be applied to the data. The value must be at least 60 seconds. If a per-series aligner other than ALIGN_NONE is specified, this field is required or an error is returned. If no per-series aligner is specified, or the aligner ALIGN_NONE is specified, then this field is ignored. The maximum value of the alignment_period is 104 weeks (2 years) for charts, and 90,000 seconds (25 hours) for alerting policies.

.google.protobuf.Duration alignment_period = 1;

The alignment_period specifies a time interval, in seconds, that is used to divide the data in all the time series into consistent blocks of time. This will be done before the per-series aligner can be applied to the data. The value must be at least 60 seconds. If a per-series aligner other than ALIGN_NONE is specified, this field is required or an error is returned. If no per-series aligner is specified, or the aligner ALIGN_NONE is specified, then this field is ignored. The maximum value of the alignment_period is 104 weeks (2 years) for charts, and 90,000 seconds (25 hours) for alerting policies.

.google.protobuf.Duration alignment_period = 1;

The alignment_period specifies a time interval, in seconds, that is used to divide the data in all the time series into consistent blocks of time. This will be done before the per-series aligner can be applied to the data. The value must be at least 60 seconds. If a per-series aligner other than ALIGN_NONE is specified, this field is required or an error is returned. If no per-series aligner is specified, or the aligner ALIGN_NONE is specified, then this field is ignored. The maximum value of the alignment_period is 104 weeks (2 years) for charts, and 90,000 seconds (25 hours) for alerting policies.

.google.protobuf.Duration alignment_period = 1;

The reduction operation to be used to combine time series into a single time series, where the value of each data point in the resulting series is a function of all the already aligned values in the input time series. Not all reducer operations can be applied to all time series. The valid choices depend on the metric_kind and the value_type of the original time series. Reduction can yield a time series with a different metric_kind or value_type than the input time series. Time series data must first be aligned (see per_series_aligner) in order to perform cross-time series reduction. If cross_series_reducer is specified, then per_series_aligner must be specified, and must not be ALIGN_NONE. An alignment_period must also be specified; otherwise, an error is returned.

.google.monitoring.v3.Aggregation.Reducer cross_series_reducer = 4;

The reduction operation to be used to combine time series into a single time series, where the value of each data point in the resulting series is a function of all the already aligned values in the input time series. Not all reducer operations can be applied to all time series. The valid choices depend on the metric_kind and the value_type of the original time series. Reduction can yield a time series with a different metric_kind or value_type than the input time series. Time series data must first be aligned (see per_series_aligner) in order to perform cross-time series reduction. If cross_series_reducer is specified, then per_series_aligner must be specified, and must not be ALIGN_NONE. An alignment_period must also be specified; otherwise, an error is returned.

.google.monitoring.v3.Aggregation.Reducer cross_series_reducer = 4;

The set of fields to preserve when cross_series_reducer is specified. The group_by_fields determine how the time series are partitioned into subsets prior to applying the aggregation operation. Each subset contains time series that have the same value for each of the grouping fields. Each individual time series is a member of exactly one subset. The cross_series_reducer is applied to each subset of time series. It is not possible to reduce across different resource types, so this field implicitly contains resource.type. Fields not specified in group_by_fields are aggregated away. If group_by_fields is not specified and all the time series have the same resource type, then the time series are aggregated into a single output time series. If cross_series_reducer is not defined, this field is ignored.

repeated string group_by_fields = 5;

An Aligner describes how to bring the data points in a single time series into temporal alignment. Except for ALIGN_NONE, all alignments cause all the data points in an alignment_period to be mathematically grouped together, resulting in a single data point for each alignment_period with end timestamp at the end of the period. Not all alignment operations may be applied to all time series. The valid choices depend on the metric_kind and value_type of the original time series. Alignment can change the metric_kind or the value_type of the time series. Time series data must be aligned in order to perform cross-time series reduction. If cross_series_reducer is specified, then per_series_aligner must be specified and not equal to ALIGN_NONE and alignment_period must be specified; otherwise, an error is returned.

.google.monitoring.v3.Aggregation.Aligner per_series_aligner = 2;

An Aligner describes how to bring the data points in a single time series into temporal alignment. Except for ALIGN_NONE, all alignments cause all the data points in an alignment_period to be mathematically grouped together, resulting in a single data point for each alignment_period with end timestamp at the end of the period. Not all alignment operations may be applied to all time series. The valid choices depend on the metric_kind and value_type of the original time series. Alignment can change the metric_kind or the value_type of the time series. Time series data must be aligned in order to perform cross-time series reduction. If cross_series_reducer is specified, then per_series_aligner must be specified and not equal to ALIGN_NONE and alignment_period must be specified; otherwise, an error is returned.

.google.monitoring.v3.Aggregation.Aligner per_series_aligner = 2;

Name	Description
values	`Iterable<String>` The groupByFields to add.

Type	Description
Aggregation.Builder	This builder for chaining.

Name	Description
value	`String` The groupByFields to add.

Type	Description
Aggregation.Builder	This builder for chaining.

Name	Description
value	`ByteString` The bytes of the groupByFields to add.

Type	Description
Aggregation.Reducer	The crossSeriesReducer.

Type	Description
int	The enum numeric value on the wire for crossSeriesReducer.

Name	Description
index	`int` The index of the element to return.

Type	Description
String	The groupByFields at the given index.

Type	Description
ByteString	The bytes of the groupByFields at the given index.

Type	Description
ProtocolStringList	A list containing the groupByFields.

Type	Description
Aggregation.Aligner	The perSeriesAligner.

Type	Description
int	The enum numeric value on the wire for perSeriesAligner.

Type	Description
boolean	Whether the alignmentPeriod field is set.

Name	Description
input	`CodedInputStream`
extensionRegistry	`ExtensionRegistryLite`

Name	Description
oneof	`OneofDescriptor`

Name	Description
field	`FieldDescriptor`
index	`int`
value	`Object`

Inheritance

Implements

Inherited Members

Static Methods

getDescriptor()

Methods

addAllGroupByFields(Iterable<String> values)

addGroupByFields(String value)

addGroupByFieldsBytes(ByteString value)

addRepeatedField(Descriptors.FieldDescriptor field, Object value)

build()

buildPartial()

clear()

clearAlignmentPeriod()

clearCrossSeriesReducer()

clearField(Descriptors.FieldDescriptor field)

clearGroupByFields()

clearOneof(Descriptors.OneofDescriptor oneof)

clearPerSeriesAligner()

clone()

getAlignmentPeriod()

getAlignmentPeriodBuilder()

getAlignmentPeriodOrBuilder()

getCrossSeriesReducer()

getCrossSeriesReducerValue()

getDefaultInstanceForType()

getDescriptorForType()

getGroupByFields(int index)

getGroupByFieldsBytes(int index)

getGroupByFieldsCount()

getGroupByFieldsList()

getPerSeriesAligner()

getPerSeriesAlignerValue()

hasAlignmentPeriod()

internalGetFieldAccessorTable()

isInitialized()

mergeAlignmentPeriod(Duration value)

mergeFrom(Aggregation other)

mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

mergeFrom(Message other)

mergeUnknownFields(UnknownFieldSet unknownFields)

setAlignmentPeriod(Duration value)

setAlignmentPeriod(Duration.Builder builderForValue)

setCrossSeriesReducer(Aggregation.Reducer value)

setCrossSeriesReducerValue(int value)

setField(Descriptors.FieldDescriptor field, Object value)

setGroupByFields(int index, String value)

setPerSeriesAligner(Aggregation.Aligner value)

setPerSeriesAlignerValue(int value)

setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)

setUnknownFields(UnknownFieldSet unknownFields)