com.google.monitoring.v3

Enum Aggregation.Reducer

java.lang.Object

java.lang.Enum<Aggregation.Reducer>

com.google.monitoring.v3.Aggregation.Reducer

All Implemented Interfaces:

com.google.protobuf.Internal.EnumLite, com.google.protobuf.ProtocolMessageEnum, Serializable, Comparable<Aggregation.Reducer>

Enclosing class:

Aggregation

public static enum Aggregation.Reducer
extends Enum<Aggregation.Reducer>
implements com.google.protobuf.ProtocolMessageEnum

 A Reducer operation describes how to aggregate data points from multiple
 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.
 

Protobuf enum google.monitoring.v3.Aggregation.Reducer

Enum Constant Summary

Enum Constants

Enum Constant and Description
REDUCE_COUNT Reduce by computing the number of data points across time series for each alignment period.
REDUCE_COUNT_FALSE Reduce by computing the number of `False`-valued data points across time series for each alignment period.
REDUCE_COUNT_TRUE Reduce by computing the number of `True`-valued data points across time series for each alignment period.
REDUCE_FRACTION_TRUE Reduce by computing the ratio of the number of `True`-valued data points to the total number of data points for each alignment period.
REDUCE_MAX Reduce by computing the maximum value across time series for each alignment period.
REDUCE_MEAN Reduce by computing the mean value across time series for each alignment period.
REDUCE_MIN Reduce by computing the minimum value across time series for each alignment period.
REDUCE_NONE No cross-time series reduction.
REDUCE_PERCENTILE_05 Reduce by computing the [5th percentile](https://en.wikipedia.org/wiki/Percentile) of data points across time series for each alignment period.
REDUCE_PERCENTILE_50 Reduce by computing the [50th percentile](https://en.wikipedia.org/wiki/Percentile) of data points across time series for each alignment period.
REDUCE_PERCENTILE_95 Reduce by computing the [95th percentile](https://en.wikipedia.org/wiki/Percentile) of data points across time series for each alignment period.
REDUCE_PERCENTILE_99 Reduce by computing the [99th percentile](https://en.wikipedia.org/wiki/Percentile) of data points across time series for each alignment period.
REDUCE_STDDEV Reduce by computing the standard deviation across time series for each alignment period.
REDUCE_SUM Reduce by computing the sum across time series for each alignment period.
UNRECOGNIZED

Field Summary

Fields

Modifier and Type	Field and Description
static int	REDUCE_COUNT_FALSE_VALUE Reduce by computing the number of `False`-valued data points across time series for each alignment period.
static int	REDUCE_COUNT_TRUE_VALUE Reduce by computing the number of `True`-valued data points across time series for each alignment period.
static int	REDUCE_COUNT_VALUE Reduce by computing the number of data points across time series for each alignment period.
static int	REDUCE_FRACTION_TRUE_VALUE Reduce by computing the ratio of the number of `True`-valued data points to the total number of data points for each alignment period.
static int	REDUCE_MAX_VALUE Reduce by computing the maximum value across time series for each alignment period.
static int	REDUCE_MEAN_VALUE Reduce by computing the mean value across time series for each alignment period.
static int	REDUCE_MIN_VALUE Reduce by computing the minimum value across time series for each alignment period.
static int	REDUCE_NONE_VALUE No cross-time series reduction.
static int	REDUCE_PERCENTILE_05_VALUE Reduce by computing the [5th percentile](https://en.wikipedia.org/wiki/Percentile) of data points across time series for each alignment period.
static int	REDUCE_PERCENTILE_50_VALUE Reduce by computing the [50th percentile](https://en.wikipedia.org/wiki/Percentile) of data points across time series for each alignment period.
static int	REDUCE_PERCENTILE_95_VALUE Reduce by computing the [95th percentile](https://en.wikipedia.org/wiki/Percentile) of data points across time series for each alignment period.
static int	REDUCE_PERCENTILE_99_VALUE Reduce by computing the [99th percentile](https://en.wikipedia.org/wiki/Percentile) of data points across time series for each alignment period.
static int	REDUCE_STDDEV_VALUE Reduce by computing the standard deviation across time series for each alignment period.
static int	REDUCE_SUM_VALUE Reduce by computing the sum across time series for each alignment period.

Method Summary

Modifier and Type	Method and Description
static Aggregation.Reducer	forNumber(int value)
static com.google.protobuf.Descriptors.EnumDescriptor	getDescriptor()
com.google.protobuf.Descriptors.EnumDescriptor	getDescriptorForType()
int	getNumber()
com.google.protobuf.Descriptors.EnumValueDescriptor	getValueDescriptor()
static com.google.protobuf.Internal.EnumLiteMap<Aggregation.Reducer>	internalGetValueMap()
static Aggregation.Reducer	valueOf(com.google.protobuf.Descriptors.EnumValueDescriptor desc)
static Aggregation.Reducer	valueOf(int value) Deprecated. Use forNumber(int) instead.
static Aggregation.Reducer	valueOf(String name) Returns the enum constant of this type with the specified name.
static Aggregation.Reducer[]	values() Returns an array containing the constants of this enum type, in the order they are declared.

Methods inherited from class java.lang.Enum

clone, compareTo, equals, finalize, getDeclaringClass, hashCode, name, ordinal, toString, valueOf

Methods inherited from class java.lang.Object

getClass, notify, notifyAll, wait, wait, wait

Enum Constant Detail

REDUCE_NONE

public static final Aggregation.Reducer REDUCE_NONE

 No cross-time series reduction. The output of the `Aligner` is
 returned.
 

REDUCE_NONE = 0;

REDUCE_MEAN

public static final Aggregation.Reducer REDUCE_MEAN

 Reduce by computing the mean value across time series for each
 alignment period. This reducer is valid for
 [DELTA][google.api.MetricDescriptor.MetricKind.DELTA] and
 [GAUGE][google.api.MetricDescriptor.MetricKind.GAUGE] metrics with
 numeric or distribution values. The `value_type` of the output is
 [DOUBLE][google.api.MetricDescriptor.ValueType.DOUBLE].
 

REDUCE_MEAN = 1;

REDUCE_MIN

public static final Aggregation.Reducer REDUCE_MIN

 Reduce by computing the minimum value across time series for each
 alignment period. This reducer is valid for `DELTA` and `GAUGE` metrics
 with numeric values. The `value_type` of the output is the same as the
 `value_type` of the input.
 

REDUCE_MIN = 2;

REDUCE_MAX

public static final Aggregation.Reducer REDUCE_MAX

 Reduce by computing the maximum value across time series for each
 alignment period. This reducer is valid for `DELTA` and `GAUGE` metrics
 with numeric values. The `value_type` of the output is the same as the
 `value_type` of the input.
 

REDUCE_MAX = 3;

REDUCE_SUM

public static final Aggregation.Reducer REDUCE_SUM

 Reduce by computing the sum across time series for each
 alignment period. This reducer is valid for `DELTA` and `GAUGE` metrics
 with numeric and distribution values. The `value_type` of the output is
 the same as the `value_type` of the input.
 

REDUCE_SUM = 4;

REDUCE_STDDEV

public static final Aggregation.Reducer REDUCE_STDDEV

 Reduce by computing the standard deviation across time series
 for each alignment period. This reducer is valid for `DELTA` and
 `GAUGE` metrics with numeric or distribution values. The `value_type`
 of the output is `DOUBLE`.
 

REDUCE_STDDEV = 5;

REDUCE_COUNT

public static final Aggregation.Reducer REDUCE_COUNT

 Reduce by computing the number of data points across time series
 for each alignment period. This reducer is valid for `DELTA` and
 `GAUGE` metrics of numeric, Boolean, distribution, and string
 `value_type`. The `value_type` of the output is `INT64`.
 

REDUCE_COUNT = 6;

REDUCE_COUNT_TRUE

public static final Aggregation.Reducer REDUCE_COUNT_TRUE

 Reduce by computing the number of `True`-valued data points across time
 series for each alignment period. This reducer is valid for `DELTA` and
 `GAUGE` metrics of Boolean `value_type`. The `value_type` of the output
 is `INT64`.
 

REDUCE_COUNT_TRUE = 7;

REDUCE_COUNT_FALSE

public static final Aggregation.Reducer REDUCE_COUNT_FALSE

 Reduce by computing the number of `False`-valued data points across time
 series for each alignment period. This reducer is valid for `DELTA` and
 `GAUGE` metrics of Boolean `value_type`. The `value_type` of the output
 is `INT64`.
 

REDUCE_COUNT_FALSE = 15;

REDUCE_FRACTION_TRUE

public static final Aggregation.Reducer REDUCE_FRACTION_TRUE

 Reduce by computing the ratio of the number of `True`-valued data points
 to the total number of data points for each alignment period. This
 reducer is valid for `DELTA` and `GAUGE` metrics of Boolean `value_type`.
 The output value is in the range [0.0, 1.0] and has `value_type`
 `DOUBLE`.
 

REDUCE_FRACTION_TRUE = 8;

REDUCE_PERCENTILE_99

public static final Aggregation.Reducer REDUCE_PERCENTILE_99

 Reduce by computing the [99th
 percentile](https://en.wikipedia.org/wiki/Percentile) of data points
 across time series for each alignment period. This reducer is valid for
 `GAUGE` and `DELTA` metrics of numeric and distribution type. The value
 of the output is `DOUBLE`.
 

REDUCE_PERCENTILE_99 = 9;

REDUCE_PERCENTILE_95

public static final Aggregation.Reducer REDUCE_PERCENTILE_95

 Reduce by computing the [95th
 percentile](https://en.wikipedia.org/wiki/Percentile) of data points
 across time series for each alignment period. This reducer is valid for
 `GAUGE` and `DELTA` metrics of numeric and distribution type. The value
 of the output is `DOUBLE`.
 

REDUCE_PERCENTILE_95 = 10;

REDUCE_PERCENTILE_50

public static final Aggregation.Reducer REDUCE_PERCENTILE_50

 Reduce by computing the [50th
 percentile](https://en.wikipedia.org/wiki/Percentile) of data points
 across time series for each alignment period. This reducer is valid for
 `GAUGE` and `DELTA` metrics of numeric and distribution type. The value
 of the output is `DOUBLE`.
 

REDUCE_PERCENTILE_50 = 11;

REDUCE_PERCENTILE_05

public static final Aggregation.Reducer REDUCE_PERCENTILE_05

 Reduce by computing the [5th
 percentile](https://en.wikipedia.org/wiki/Percentile) of data points
 across time series for each alignment period. This reducer is valid for
 `GAUGE` and `DELTA` metrics of numeric and distribution type. The value
 of the output is `DOUBLE`.
 

REDUCE_PERCENTILE_05 = 12;

UNRECOGNIZED

public static final Aggregation.Reducer UNRECOGNIZED

Field Detail

REDUCE_NONE_VALUE

public static final int REDUCE_NONE_VALUE

 No cross-time series reduction. The output of the `Aligner` is
 returned.
 

REDUCE_NONE = 0;

See Also:

Constant Field Values

REDUCE_MEAN_VALUE

public static final int REDUCE_MEAN_VALUE

 Reduce by computing the mean value across time series for each
 alignment period. This reducer is valid for
 [DELTA][google.api.MetricDescriptor.MetricKind.DELTA] and
 [GAUGE][google.api.MetricDescriptor.MetricKind.GAUGE] metrics with
 numeric or distribution values. The `value_type` of the output is
 [DOUBLE][google.api.MetricDescriptor.ValueType.DOUBLE].
 

REDUCE_MEAN = 1;

See Also:

Constant Field Values

REDUCE_MIN_VALUE

public static final int REDUCE_MIN_VALUE

 Reduce by computing the minimum value across time series for each
 alignment period. This reducer is valid for `DELTA` and `GAUGE` metrics
 with numeric values. The `value_type` of the output is the same as the
 `value_type` of the input.
 

REDUCE_MIN = 2;

See Also:

Constant Field Values

REDUCE_MAX_VALUE

public static final int REDUCE_MAX_VALUE

 Reduce by computing the maximum value across time series for each
 alignment period. This reducer is valid for `DELTA` and `GAUGE` metrics
 with numeric values. The `value_type` of the output is the same as the
 `value_type` of the input.
 

REDUCE_MAX = 3;

See Also:

Constant Field Values

REDUCE_SUM_VALUE

public static final int REDUCE_SUM_VALUE

 Reduce by computing the sum across time series for each
 alignment period. This reducer is valid for `DELTA` and `GAUGE` metrics
 with numeric and distribution values. The `value_type` of the output is
 the same as the `value_type` of the input.
 

REDUCE_SUM = 4;

See Also:

Constant Field Values

REDUCE_STDDEV_VALUE

public static final int REDUCE_STDDEV_VALUE

 Reduce by computing the standard deviation across time series
 for each alignment period. This reducer is valid for `DELTA` and
 `GAUGE` metrics with numeric or distribution values. The `value_type`
 of the output is `DOUBLE`.
 

REDUCE_STDDEV = 5;

See Also:

Constant Field Values

REDUCE_COUNT_VALUE

public static final int REDUCE_COUNT_VALUE

 Reduce by computing the number of data points across time series
 for each alignment period. This reducer is valid for `DELTA` and
 `GAUGE` metrics of numeric, Boolean, distribution, and string
 `value_type`. The `value_type` of the output is `INT64`.
 

REDUCE_COUNT = 6;

See Also:

Constant Field Values

REDUCE_COUNT_TRUE_VALUE

public static final int REDUCE_COUNT_TRUE_VALUE

 Reduce by computing the number of `True`-valued data points across time
 series for each alignment period. This reducer is valid for `DELTA` and
 `GAUGE` metrics of Boolean `value_type`. The `value_type` of the output
 is `INT64`.
 

REDUCE_COUNT_TRUE = 7;

See Also:

Constant Field Values

REDUCE_COUNT_FALSE_VALUE

public static final int REDUCE_COUNT_FALSE_VALUE

 Reduce by computing the number of `False`-valued data points across time
 series for each alignment period. This reducer is valid for `DELTA` and
 `GAUGE` metrics of Boolean `value_type`. The `value_type` of the output
 is `INT64`.
 

REDUCE_COUNT_FALSE = 15;

See Also:

Constant Field Values

REDUCE_FRACTION_TRUE_VALUE

public static final int REDUCE_FRACTION_TRUE_VALUE

 Reduce by computing the ratio of the number of `True`-valued data points
 to the total number of data points for each alignment period. This
 reducer is valid for `DELTA` and `GAUGE` metrics of Boolean `value_type`.
 The output value is in the range [0.0, 1.0] and has `value_type`
 `DOUBLE`.
 

REDUCE_FRACTION_TRUE = 8;

See Also:

Constant Field Values

REDUCE_PERCENTILE_99_VALUE

public static final int REDUCE_PERCENTILE_99_VALUE

 Reduce by computing the [99th
 percentile](https://en.wikipedia.org/wiki/Percentile) of data points
 across time series for each alignment period. This reducer is valid for
 `GAUGE` and `DELTA` metrics of numeric and distribution type. The value
 of the output is `DOUBLE`.
 

REDUCE_PERCENTILE_99 = 9;

See Also:

Constant Field Values

REDUCE_PERCENTILE_95_VALUE

public static final int REDUCE_PERCENTILE_95_VALUE

 Reduce by computing the [95th
 percentile](https://en.wikipedia.org/wiki/Percentile) of data points
 across time series for each alignment period. This reducer is valid for
 `GAUGE` and `DELTA` metrics of numeric and distribution type. The value
 of the output is `DOUBLE`.
 

REDUCE_PERCENTILE_95 = 10;

See Also:

Constant Field Values

REDUCE_PERCENTILE_50_VALUE

public static final int REDUCE_PERCENTILE_50_VALUE

 Reduce by computing the [50th
 percentile](https://en.wikipedia.org/wiki/Percentile) of data points
 across time series for each alignment period. This reducer is valid for
 `GAUGE` and `DELTA` metrics of numeric and distribution type. The value
 of the output is `DOUBLE`.
 

REDUCE_PERCENTILE_50 = 11;

See Also:

Constant Field Values

REDUCE_PERCENTILE_05_VALUE

public static final int REDUCE_PERCENTILE_05_VALUE

 Reduce by computing the [5th
 percentile](https://en.wikipedia.org/wiki/Percentile) of data points
 across time series for each alignment period. This reducer is valid for
 `GAUGE` and `DELTA` metrics of numeric and distribution type. The value
 of the output is `DOUBLE`.
 

REDUCE_PERCENTILE_05 = 12;

See Also:

Constant Field Values

Method Detail

values

public static Aggregation.Reducer[] values()

Returns an array containing the constants of this enum type, in the order they are declared. This method may be used to iterate over the constants as follows:

for (Aggregation.Reducer c : Aggregation.Reducer.values())
    System.out.println(c);

Returns:

an array containing the constants of this enum type, in the order they are declared

valueOf

public static Aggregation.Reducer valueOf(String name)

Returns the enum constant of this type with the specified name. The string must match exactly an identifier used to declare an enum constant in this type. (Extraneous whitespace characters are not permitted.)

Parameters:

name - the name of the enum constant to be returned.

Returns:

the enum constant with the specified name

Throws:

IllegalArgumentException - if this enum type has no constant with the specified name

NullPointerException - if the argument is null

getNumber

public final int getNumber()

Specified by:

getNumber in interface com.google.protobuf.Internal.EnumLite

Specified by:

getNumber in interface com.google.protobuf.ProtocolMessageEnum

valueOf

@Deprecated
public static Aggregation.Reducer valueOf(int value)

Deprecated. Use forNumber(int) instead.

Parameters:

value - The numeric wire value of the corresponding enum entry.

Returns:

The enum associated with the given numeric wire value.

forNumber

public static Aggregation.Reducer forNumber(int value)

Parameters:

value - The numeric wire value of the corresponding enum entry.

Returns:

The enum associated with the given numeric wire value.

internalGetValueMap

public static com.google.protobuf.Internal.EnumLiteMap<Aggregation.Reducer> internalGetValueMap()

getValueDescriptor

public final com.google.protobuf.Descriptors.EnumValueDescriptor getValueDescriptor()

Specified by:

getValueDescriptor in interface com.google.protobuf.ProtocolMessageEnum

getDescriptorForType

public final com.google.protobuf.Descriptors.EnumDescriptor getDescriptorForType()

Specified by:

getDescriptorForType in interface com.google.protobuf.ProtocolMessageEnum

getDescriptor

public static final com.google.protobuf.Descriptors.EnumDescriptor getDescriptor()

valueOf

public static Aggregation.Reducer valueOf(com.google.protobuf.Descriptors.EnumValueDescriptor desc)