github.com/m3db/m3@v1.5.0/src/metrics/transformation/func.go (about)

     1  // Copyright (c) 2018 Uber Technologies, Inc.
     2  //
     3  // Permission is hereby granted, free of charge, to any person obtaining a copy
     4  // of this software and associated documentation files (the "Software"), to deal
     5  // in the Software without restriction, including without limitation the rights
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     7  // copies of the Software, and to permit persons to whom the Software is
     8  // furnished to do so, subject to the following conditions:
     9  //
    10  // The above copyright notice and this permission notice shall be included in
    11  // all copies or substantial portions of the Software.
    12  //
    13  // THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
    14  // IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
    15  // FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
    16  // AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
    17  // LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
    18  // OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
    19  // THE SOFTWARE.
    20  
    21  package transformation
    22  
    23  import (
    24  	"math"
    25  	"time"
    26  )
    27  
    28  var (
    29  	emptyDatapoint = Datapoint{Value: math.NaN()}
    30  )
    31  
    32  // Datapoint is a metric data point containing a timestamp in
    33  // Unix nanoseconds since epoch and a value.
    34  type Datapoint struct {
    35  	TimeNanos int64
    36  	Value     float64
    37  }
    38  
    39  // IsEmpty returns whether this is an empty datapoint.
    40  func (dp Datapoint) IsEmpty() bool { return math.IsNaN(dp.Value) }
    41  
    42  // UnaryTransform is a unary transformation that takes a single
    43  // datapoint as input and transforms it into a datapoint as output.
    44  // It can keep state if it requires.
    45  type UnaryTransform interface {
    46  	Evaluate(dp Datapoint) Datapoint
    47  }
    48  
    49  // UnaryTransformFn implements UnaryTransform as a function.
    50  type UnaryTransformFn func(dp Datapoint) Datapoint
    51  
    52  // Evaluate implements UnaryTransform as a function.
    53  func (fn UnaryTransformFn) Evaluate(dp Datapoint) Datapoint {
    54  	return fn(dp)
    55  }
    56  
    57  // FeatureFlags holds options passed into transformations from
    58  // the aggregator configuration file.
    59  // nolint:gofumpt
    60  type FeatureFlags struct {
    61  }
    62  
    63  // BinaryTransform is a binary transformation that takes the
    64  // previous and the current datapoint as input and produces
    65  // a single datapoint as the transformation result.
    66  // It can keep state if it requires.
    67  type BinaryTransform interface {
    68  	Evaluate(prev, curr Datapoint, flags FeatureFlags) Datapoint
    69  }
    70  
    71  // BinaryTransformFn implements BinaryTransform as a function.
    72  type BinaryTransformFn func(prev, curr Datapoint, flags FeatureFlags) Datapoint
    73  
    74  // Evaluate implements BinaryTransform as a function.
    75  func (fn BinaryTransformFn) Evaluate(prev, curr Datapoint, flags FeatureFlags) Datapoint {
    76  	return fn(prev, curr, flags)
    77  }
    78  
    79  // UnaryMultiOutputTransform is like UnaryTransform, but can output an additional datapoint.
    80  // The additional datapoint is not passed to subsequent transforms.
    81  type UnaryMultiOutputTransform interface {
    82  	// Evaluate applies the transform on the provided datapoint.
    83  	Evaluate(dp Datapoint, resolution time.Duration) (Datapoint, Datapoint)
    84  }
    85  
    86  // UnaryMultiOutputTransformFn implements UnaryMultiOutputTransform as a function.
    87  type UnaryMultiOutputTransformFn func(dp Datapoint, resolution time.Duration) (Datapoint, Datapoint)
    88  
    89  // Evaluate applies the transform on the provided datapoint.
    90  func (fn UnaryMultiOutputTransformFn) Evaluate(dp Datapoint, resolution time.Duration) (Datapoint, Datapoint) {
    91  	return fn(dp, resolution)
    92  }