Dataset metadata service#

Dataset metadata lookup. This includes metadata about the data sources reachable from the dataset.

OpenAPI file: DatasetMetadataService.json

Types#

Abs#

Computes the absolute value of each point in the series.

x NumericSeries required: Input numeric series.

AbsoluteThreshold#

Threshold defined as a real number corresponding the unit of a series.

value DoubleConstant required: Allowed spread, in the series’ own unit.

AbsoluteTimestampSeries#

Replaces values in a series with the absolute timestamps.

input Series required
timeUnit TimeUnit required: The time unit used to define the output values. Throws an error if nanosecond or finer.

Acos#

Computes the arccosine of each value, returning radians.

x NumericSeries required: Input numeric series (values in [-1, 1]).

Add#

Adds two numeric series pointwise.

left NumericSeries required: Left-hand operand.
right NumericSeries required: Right-hand operand.

AfterPersistenceWindow#

The first point in the output range will be the first point after the condition has been true for the min duration and min points.

An empty JSON object, {}.

AggregateEnumSeries#

Aggregates values with duplicate timestamps in the input series values into a single value using the specified aggregation function.

input EnumSeries required
function EnumAggregationFunction required

AggregateNumericSeries#

DEPRECATED. Use a dedicated group-by-and-aggregate nodes instead.

Aggregates values with duplicate timestamps in the input series values into a single value using the specified aggregation function.

input NumericSeries required
function NumericAggregationFunction required
groupByTags array of StringConstant: Tags to group by for the aggregation. If left empty, the tags to group by will be equivalent to those in the input series. If specified, the result will be grouped ONLY by the specified tags. The tags specified here MUST be a (non-strict) subset of the input series’s group by tags.
aggregateByAllGroupings boolean: This field’s purpose is to distinguish between the two flavors of groupByTags being empty. It has no effect when groupByTags is non-empty. When true and groupByTags is empty, aggregate across all series in the input. When false and groupByTags is empty, the result will be grouped by the same tags as the input series.
interpolationConfiguration InterpolationConfiguration deprecated: If provided, interpolates values at timestamps where the input series has values before aggregating. If not provided, only aggregates when timestamps match exactly (existing behavior). Deprecated: Setting interpolation on this node is deprecated.

AggregateUnderRangesSeries#

Aggregates the input series under the ranges in the provided ranges series, and outputs a new series with one point at the start of each range, where the value is the aggregation result. If a range has no points, no point will be produced for it. If a range has no start, the point produced for it will be at the start of the compute request range.

input NumericSeries required
ranges RangeSeries required
operation NumericAggregationFunction required deprecated: Deprecated: Use a dedicated group-by-and-aggregate node instead (coming in a follow-up PR). This field is retained as required for backwards compatibility with existing callers.

AggregationBuilder#

Set type to the name of one of the other fields, and set only that field.

rollingTime RollingTimeAggregationBuilder
rollingPoints RollingPointsAggregationBuilder
groupBy GroupByAggregationBuilder

Alignment#

Specifies how to set the timestamp grid for multi-input operations.

Set type to the name of one of the other fields, and set only that field.

driverSeries DriverSeries
union Union

AllowNegativeValues#

An empty JSON object, {}.

AnchorAlignedDataset#

Aligns each anchored portion of the input dataset onto a common anchor timestamp while preserving grouping tags. Without a reference the selected anchor becomes timestamp zero, so the output is in a relative time domain; with a reference the anchors are aligned onto the referenced portion’s anchor and the output stays in the input’s absolute time domain. Currently run boundary, event, and range anchors are supported, and every storage-backed leaf of the input must resolve to run-backed branches.

input Dataset required: The dataset to align.
anchor DatasetAnchor required: Selects the timestamp each anchored portion of the input is aligned by.
reference AnchorReference: When present, each anchor is aligned onto the referenced anchor timestamp instead of onto timestamp zero, so output remains in the input’s absolute time domain and the referenced portion is unshifted. When absent, the selected anchor becomes timestamp zero.

AnchorReference#

Selects the anchor timestamp every other anchor is aligned onto.

Set type to the name of one of the other fields, and set only that field.

earliestAnchor EarliestAnchorReference: Aligns every anchor onto the earliest anchor resolved from the input, so the earliest-anchored run is unshifted and every other run shifts backwards onto it.

AndSeries#

Combines two boolean series point-wise using logical AND, producing true where both inputs are true and false otherwise.

left BooleanSeries required
right BooleanSeries required

ApproximateThresholdOperator#

EQUAL_TO
NOT_EQUAL_TO

ApproximateThresholdRanges#

Produces a list of ranges for which the threshold condition is satisfied.

input NumericSeries required
threshold DoubleConstant required
tolerance DoubleConstant required
operator ApproximateThresholdOperator required
persistenceWindowConfiguration PersistenceWindowConfiguration

ArithmeticSeries#

inputs map of LocalVariableName to NumericSeries
expression string required
interpolationConfiguration InterpolationConfiguration deprecated: Defaults to forward fill interpolation with a 1s interpolation radius Deprecated: Setting interpolation on this node is deprecated.

ArraySeries#

Set type to the name of one of the other fields, and set only that field.

numeric1d Numeric1dArraySeries
enum1d Enum1dArraySeries

Asin#

Computes the arcsine of each value, returning radians.

x NumericSeries required: Input numeric series (values in [-1, 1]).

Asset#

Asset reference for Dataset.asset. The rid field accepts either a literal asset RID or a StringConstant reference resolved from Context.

rid StringConstant required: Resource identifier of an asset

AssetChannel#

assetRid StringConstant required
dataScopeName StringConstant required: Used to disambiguate when multiple data scopes within this asset contain channels with the same name.
channel StringConstant required
additionalTags map of string to StringConstant deprecated: Deprecated: Use additionalTagFilters
additionalTagFilters TagFilters: Tags to filter the channel by, in addition to tag filters defined for a given Asset data scope. Throws on collisions with tag keys already defined for the given Asset data scope. Only returns points that match both sets of tag filters. For log series, include arg filters here in addition to tag filters.
tagsToGroupBy array of string deprecated: Deprecated: Use groupByTags instead. Throws if both tagsToGroupBy and groupByTags are specified.
groupByTags array of StringConstant: Tags that the channel should be grouped by. If this is non-empty a grouped result will be returned with an entry for each grouping. Only one of tagsToGroupBy and groupByTags should be specified.

AssetsSearchTarget#

Search assets. Each match expands to one grouping per data scope on that asset.

query ResourceSearchQuery required: Predicate tree used to filter matching assets.

Atan2#

Computes the two-argument arctangent atan2(y, x) using signs to determine the quadrant.

y NumericSeries required: Y-coordinate series.
x NumericSeries required: X-coordinate series.

Average#

A average that gives the same weight to each observation inside the time window

An empty JSON object, {}.

BandPassConfiguration#

lowPassbandFrequency DoubleConstant required
highPassbandFrequency DoubleConstant required

BandStopConfiguration#

lowStopbandFrequency DoubleConstant required
highStopbandFrequency DoubleConstant required

BatchDataSourceStreamingSupport#

Diagnostic details for a data source within a batched metadata request that does not support streaming.

dataSource DataSource required
unsupportedReason StreamingNotSupportedReason required: Why this data source does not support live streaming.
requestIds array of string: Request ids of the datasets that included this data source.

BatchStreamingSupport#

Whether the dataset supports live streaming, plus unsupported data source diagnostics.

supportsStreaming boolean required: True iff unsupportedDataSources is empty.
unsupportedDataSources array of BatchDataSourceStreamingSupport: Diagnostic entries for data sources reachable from the dataset that do not support live streaming. A data source may appear multiple times if multiple checks fail.

BinaryArithmeticOperation#

ATAN2: Calculates the angle measure between the x-axis and a ray from the origin to a point (input2, input1) in radians. Note the order of arguments.

BinaryArithmeticSeries#

Applies a point-wise transformation to a pair of series.

input1 NumericSeries required
input2 NumericSeries required
operation BinaryArithmeticOperation required
interpolationConfiguration InterpolationConfiguration deprecated: Defaults to forward fill interpolation with a 1s interpolation radius Deprecated: Setting interpolation on this node is deprecated.

BitAnd#

Applies a bitwise AND between each value (cast to int64) and the operand.

input NumericSeries required: Input numeric series (values cast to int64).
operand IntegerConstant required: The value to AND with each point.

BitAndFunction#

operand integer (int64) required

BitOperationFunction#

Set type to the name of one of the other fields, and set only that field.

and BitAndFunction
or BitOrFunction
xor BitXorFunction
shiftRight BitShiftRightFunction
shiftLeft BitShiftLeftFunction
bitTest BitTestFunction

BitOperationSeries#

Casts input series values to long before applying the bitwise operation.

input NumericSeries required
function BitOperationFunction required

BitOr#

Applies a bitwise OR between each value (cast to int64) and the operand.

input NumericSeries required: Input numeric series (values cast to int64).
operand IntegerConstant required: The value to OR with each point.

BitOrFunction#

operand integer (int64) required

BitShiftLeft#

Left-shifts the bits in each value (cast to int64) by the given number of positions.

input NumericSeries required: Input numeric series (values cast to int64).
operand IntegerConstant required: Number of positions to shift left.

BitShiftLeftFunction#

Shifts the bits in each value left according to the given operand.

operand integer required

BitShiftRight#

Right-shifts the bits in each value (cast to int64) by the given number of positions.

input NumericSeries required: Input numeric series (values cast to int64).
operand IntegerConstant required: Number of positions to shift right.

BitShiftRightFunction#

Right shifts the bits in each value right according to the given operand.

operand integer required

BitTest#

Returns the bit at the specified index for each value (cast to int64), where index 0 is the least significant bit.

input NumericSeries required: Input numeric series (values cast to int64).
index IntegerConstant required: Zero-based bit index, where 0 is the least significant bit.

BitTestFunction#

Returns the bit at the specified index, where the right-most bit has index 0.

index integer required

BitXor#

Applies a bitwise XOR between each value (cast to int64) and the operand.

input NumericSeries required: Input numeric series (values cast to int64).
operand IntegerConstant required: The value to XOR with each point.

BitXorFunction#

operand integer (int64) required

BooleanRanges#

Produces ranges spanning the regions where a boolean input is true.

The condition is evaluated point-wise at each aligned timestamp; the numeric series it compares are aligned against each other the same way arithmetic between them would be.

input BooleanSeries required: The condition whose true regions become ranges.
minPoints IntegerConstant: Minimum number of matching points. Defaults to 1.
minDuration compute.api.Duration: Minimum matching duration. Defaults to one nanosecond.
rangeStart RangeStart: Selects whether the output begins at the first match or after persistence is satisfied.

BooleanSeries#

Set type to the name of one of the other fields, and set only that field.

greaterThan GreaterThanSeries
lessThan LessThanSeries
equalTo EqualToSeries
notEqualTo NotEqualToSeries
greaterThanOrEqualTo GreaterThanOrEqualToSeries
lessThanOrEqualTo LessThanOrEqualToSeries
and AndSeries
or OrSeries

BuiltinConstant#

A system-defined constant referenceable by name. The server resolves the symbol to its numeric value during query resolution.

Set type to the name of one of the other fields, and set only that field.

math MathConstant
physical PhysicalConstant

BuiltInCurveFit#

A closed-form curve fit (exponential, logarithmic, or power) of the enclosing target (y) against the chosen independent variable (x): either sample time (a time variable) or another series (a numeric variable).

independentVariable CurveFitVariable required: The x axis the target is fit against — either relative sample time or another series.

CategoricalEqualityRangesV2#

Produces ranges where all categorical inputs are equal or are not all equal.

inputs array of EnumSeries: The series compared against each other. At least two are required.
minPoints IntegerConstant: Minimum number of matching points. Defaults to 1.
minDuration compute.api.Duration: Minimum matching duration. Defaults to one nanosecond.
rangeStart RangeStart: Selects whether the output begins at the first match or after persistence is satisfied.
equalityOperator EqualityOperator required

CategoricalOnChangeRangesV2#

Produces a zero-duration range whenever a categorical input changes value.

input EnumSeries required

CategoricalStaleRangesV2#

Produces ranges where a categorical input has no data for at least a duration.

input EnumSeries required
threshold compute.api.Duration required: Minimum gap without data that produces an output range.

CategoryFilterRangesV2#

Produces ranges where a categorical input matches a set of values.

input EnumSeries required
values array of StringConstant: Category labels matched against each input point.
minPoints IntegerConstant: Minimum number of matching points. Defaults to 1.
minDuration compute.api.Duration: Minimum matching duration. Defaults to one nanosecond.
rangeStart RangeStart: Selects whether the output begins at the first match or after persistence is satisfied.
operator EnumFilterOperator required

ChannelSeries#

Deprecated: prefer SelectSeries-based nodes with an explicit dataset (or VariableValue.series when binding a series to a variable), which select from an arbitrary dataset and let the consuming node decide the series type.

Set type to the name of one of the other fields, and set only that field.

dataSource DataSourceChannel
asset AssetChannel
run RunChannel

CombinedDataset#

Combines multiple datasets into a single dataset by taking the union of all points from each input (akin to SQL {@code UNION ALL}). Duplicate timestamps are preserved rather than merged; callers that need aggregation should wrap the selected series downstream.

inputs array of Dataset: The datasets to combine.

CombineStructSeries#

Combines named input series into one struct-valued series. Each map key becomes a field name in the resulting struct; a downstream UDF receives the struct as a JSON object keyed by these names and parses it itself. Alignment uses the interpolation configuration before producing row-aligned values.

inputs map of string to Series: Input series keyed by struct field name.
interpolationConfiguration InterpolationConfiguration deprecated: Optional interpolation rules used when aligning input series before combining them. Deprecated: Setting interpolation on this node is deprecated.

compute.api.Duration#

A length of time. Can be constructed from literal values in various units or composed via arithmetic. Used for window sizes, time shifts, persistence thresholds, and resampling intervals.

Set type to the name of one of the other fields, and set only that field.

reference Reference
nanoseconds DurationNanoseconds
milliseconds DurationMilliseconds
seconds DurationSeconds
minutes DurationMinutes
hours DurationHours
days DurationDays
add DurationAdd
subtract DurationSubtract
negate DurationNegate

ComputeEventQuery#

Set type to the name of one of the other fields, and set only that field.

searchText StringConstant
after TimestampConstant: Filters to events after this timestamp, exclusive. This includes events that start before, but end after this time.
before TimestampConstant: Filters to events before this timestamp, exclusive. This includes events that start before, but end after this time.
advancedTimeFilter EventTimeFilter
asset StringConstant
template StringConstant
workbook StringConstant
dataReview StringConstant
originType SearchEventOriginType
dataReviewCheck StringConstant
dispositionStatus EventDispositionStatus
priority StringConstant
assignee StringConstant
eventType EventType
createdBy StringConstant
label StringConstant
property Property
and array of ComputeEventQuery
or array of ComputeEventQuery
not ComputeEventQuery
workspace StringConstant
procedure StringConstant
procedureExecution StringConstant
stepId StringConstant

ComputeNode#

Set type to the name of one of the other fields, and set only that field.

enum EnumSeries
numeric NumericSeries
log LogSeries
ranges RangeSeries
array ArraySeries
struct StructSeries
curveFit CurveFit: Deprecated: use curveV2 (CurveFitV2) instead.
curveV2 CurveFitV2
video Reference
raw Reference deprecated: Deprecated: wrap raw references in a typed compute node.

ComputeNodeWithContext#

seriesNode ComputeNode required
context Context required

ConstantNumericSeries#

A synthetic series that produces a constant value across the entire time range.

Set type to the name of one of the other fields, and set only that field.

double DoubleConstant: Create from a floating-point constant.

ContainsSeries#

Maps each log line to 1.0 when operator matches it and 0.0 otherwise.

input LogSeries required
operator LogFilterOperator required

Context#

variables map of VariableName to VariableValue
functionVariables map of FunctionReference to FunctionVariables deprecated: Deprecated: This field is deprecated and will be removed in a future version.
datasetReferences map of DatasetReferenceName to Dataset: Named datasets looked up by DatasetReference nodes in the compute tree.
defaultFillStrategy FillStrategy: Default fill strategy applied at every multi-input alignment boundary where no per-node interpolationConfiguration is specified. When absent, falls back to the server-configured default (forward fill with a 1 second fill limit).
defaultAlignmentStrategy Alignment: Default alignment strategy applied at every multi-input alignment boundary where no per-node alignment strategy is specified. When absent, falls back to the server default (driver-series alignment).
applyDataScopeOffsets boolean: When true, dataset resolution applies each data scope’s persisted offset as a time shift, and the client must not pre-apply those offsets itself. When absent or false, scope offsets are left to the client, preserving behavior for legacy clients that inject equivalent timeShift nodes into the compute request. Read from the context in scope at resolution time.
resolveAssetsThroughDatasets boolean: When true, Dataset.asset, the asset-typed sources of Dataset.run, and asset or run search expand through each asset’s mirrored derived dataset instead of its data scopes. Branches then carry the dataset’s declared channel-search split tag keys in place of the reserved DATA_SCOPE tag, so callers must filter and group on those keys; the definition’s own time shifts apply regardless of applyDataScopeOffsets; and an asset with no mirrored dataset resolves to no data. When absent or false, assets expand from their data scopes as before.

Cos#

Computes the trigonometric cosine of each value (input in radians).

x NumericSeries required: Input numeric series (radians).

Count#

The number of points inside the time window.

An empty JSON object, {}.

CumulativeSumSeries#

Calculates the running total of the series values.

input NumericSeries required
startTimestamp TimestampConstant required

CurveFit#

Deprecated: use CurveFitV2 instead.

curveFitPlotType CurveFitPlotType required
curveFitDetails CurveFitDetails required
curveFitOptions CurveFitOptions required

CurveFitBoundsConfiguration#

min DoubleConstant
max DoubleConstant

CurveFitDetails#

Set type to the name of one of the other fields, and set only that field.

exponential ExponentialCurve
logarithmic LogarithmicCurve
polynomial PolynomialCurve
power PowerCurve

CurveFitOptions#

startTime TimestampConstant required
endTime TimestampConstant required

CurveFitPlotType#

Set type to the name of one of the other fields, and set only that field.

timeSeries TimeSeriesCurveFit
scatter ScatterCurveFit

CurveFitRange#

startTime TimestampConstant required
endTime TimestampConstant required

CurveFitSeriesVariable#

series NumericSeries required
boundsConfig CurveFitBoundsConfiguration: Optional inclusive bounds selecting which variable samples are fit. Samples outside the bounds are excluded.

CurveFitTarget#

The series a curve is fit against (the y of the fit). Modeled as a union so additional target types can be added in the future; today the only arm is a numeric series.

Set type to the name of one of the other fields, and set only that field.

numeric CurveFitSeriesVariable

CurveFitTimeVariable#

timeUnit TimeUnit: The unit of the time variable in the formula expression. If not specified, the time unit is assumed to be seconds.

CurveFitV2#

target CurveFitTarget required: Target to fit the equation against.
fitRange CurveFitRange required: The range to fit the curve over
curveToFit CurveFitV2Details required: The curve type to fit against the target series.

CurveFitV2Details#

Set type to the name of one of the other fields, and set only that field.

exponential BuiltInCurveFit
logarithmic BuiltInCurveFit
polynomial PolynomialCurveFit
power BuiltInCurveFit
custom CustomCurveFit

CurveFitVariable#

A series a curve fit reads from: another numeric series, or the target’s own sample timestamps. Used both as the named formula inputs of a custom fit and as the independent (x) axis of a built-in fit.

Set type to the name of one of the other fields, and set only that field.

numeric CurveFitSeriesVariable
time CurveFitTimeVariable

CustomCurveFit#

formula StringConstant required: A mathematical expression in terms of variable and parameter names, e.g. a * x + b * sin(x). Variable names must match keys in the variables map; parameter names must match keys in the parameters map.
variables map of LocalVariableName to CurveFitVariable: Named input series referenced in the formula. Keys must match the variable names used in the formula expression.
parameters map of string to DoubleConstant: Named fitting parameters and their initial guesses. Keys must match the parameter names used in the formula expression; values are the starting points passed to the optimizer. The target the curve is fit against is the y of the enclosing curve fit (the timeSeries series values, or the scatter y series).

Dataset#

A logical bundle of named series. For the time being, columns are each a time series (series name + tags). A dataset is either rooted in persisted data (asset or dataset) or defined as a transformation of another dataset.

Set type to the name of one of the other fields, and set only that field.

asset Asset: Single asset. Expands to one grouping per data scope on the asset. Groupings are tagged by assetRid and dataScope so callers can safely compose multiple assets with combine.
run Run: Single run. Expands to one grouping per data source attached to the run: asset-typed sources contribute one grouping per data scope on the asset; dataset-typed sources contribute one grouping per dataset. Groupings are tagged by runRid and dataScope; asset-typed groupings additionally carry assetRid so callers can safely compose multiple runs with combine.
saved SavedDataset
search SearchDataset
combine CombinedDataset
tag TaggedDataset
filter FilteredDataset
timeShift TimeShiftedDataset
alignByAnchor AnchorAlignedDataset
withSeries WithSeriesDataset
dropSeries DropSeriesDataset
reference DatasetReference
withDimensions DimensionsDataset

DatasetAnchor#

Set type to the name of one of the other fields, and set only that field.

run IntervalAnchor: Uses the start or end of each run as its anchor. The input dataset must resolve exclusively to run-backed branches.

DatasetReference#

References a named dataset in Context.datasetReferences.

name StringConstant required: Name of the dataset reference to resolve from the context.

DatasetResolutionMetadata#

Metadata derived from resolving a dataset into its contributing data scopes.

latestStandaloneAssetDataTime Timestamp: Latest data timestamp across scopes reached from standalone asset inputs. Asset scopes reached through runs are excluded so clients can combine this value with declared run intervals.
runIntervals array of ResolvedRunInterval: Run intervals in the dataset’s output time domain after time shifts and anchor alignment.
datasetIntervals array of ResolvedDatasetInterval: Time intervals of catalog-dataset scopes reached without an intermediating asset or run — e.g. a saved dataset referenced directly, including each input dataset a derived dataset resolves to. Each interval is the backing dataset’s recorded catalog bounds, transformed into the dataset’s output time domain after time shifts. A dataset with no recorded bounds contributes no interval, as does one whose bounds are relative: those are offsets from an unanchored zero rather than wall-clock times.
alignmentAnchorTimes array of Timestamp: The output-domain time each anchor alignment in this dataset lines its runs up on, one entry per alignByAnchor. Empty when no branch is anchor-aligned.

DataSource#

Set type to the name of one of the other fields, and set only that field.

dataset string (RID)
connection string (RID)
logSet string (RID)
video string (RID)
spatial string (RID)

DataSourceChannel#

dataSourceRid StringConstant required
channel StringConstant required
tags map of string to StringConstant deprecated: Deprecated: Use tagFilters
tagFilters TagFilters: Tags to filter the channel by. Only returns points from the channel where tag values match the provided expression. For log series, include arg filters here in addition to tag filters.
tagsToGroupBy array of string deprecated: Deprecated: Use groupByTags instead. Throws if both tagsToGroupBy and groupByTags are specified.
groupByTags array of StringConstant: Tags that the channel should be grouped by. If this is non-empty a grouped result will be returned with an entry for each grouping. Only one of tagsToGroupBy and groupByTags should be specified.

DataSourceStreamingSupport#

Diagnostic details for a data source within the dataset that does not support streaming.

dataSource DataSource required
unsupportedReason StreamingNotSupportedReason required: Why this data source does not support live streaming.

DerivativeSeries#

Calculates the rate of change between subsequent points.

input NumericSeries required
timeUnit TimeUnit: Time unit used to calculate the derivative. Defaults to seconds if not specified.
negativeValuesConfiguration NegativeValueConfiguration: Defines the strategy for handling negative output values. Defaults to allowNegativeValues if not specified.

DerivedSeries#

Represents a derived series within a compute graph. This is a series that is derived from a function within a module.

Set type to the name of one of the other fields, and set only that field.

function FunctionDerivedSeries

Dimension#

A value derived per asset or run, injected as a tag.

tagKey StringConstant: The tag key to inject the value under. Defaults to the key derived by value.
value DimensionValue required: The value to inject.

DimensionsDataset#

Injects one tag per dimension onto every series of the underlying dataset, valued from the asset or run the series belongs to. This makes resource metadata usable as a grouping, filtering and aggregation dimension with selectTags, tag predicates and groupByTags. Group by the dimension together with ASSET_RID (or RUN_RID) to keep each resource separate, or by the dimension alone to pivot so that resources sharing a value fall into one group.

Dimensions are only supported on asset and run branches. Any other branch, such as a saved dataset or a derived series from withSeries, gets the reserved value NOMINAL_ABSENT for every dimension. To group derived series by a dimension, apply withDimensions to the withSeries input instead, so that the series they are computed from carry the dimension tags. A dimension tag replaces a series tag with the same key.

input Dataset required: The underlying dataset to tag.
dimensions array of Dimension: The dimensions to inject. Must not be empty, must have at most 10 entries, and every dimension must have a distinct tag key. A tag key must not be a ReservedTagKey, start with EVENT_LABEL_PREFIX:, or start with NOMINAL_.

DimensionValue#

Set type to the name of one of the other fields, and set only that field.

stringProperty StringPropertyDimension: The value of a string property on the asset or run.
identity IdentityDimension: The value of an asset’s primary key under one of its types.

Divide#

Divides left by right pointwise.

left NumericSeries required: Numerator.
right NumericSeries required: Denominator.

DoubleConstant#

A floating-point constant that can be a literal value, a named variable reference, or a named builtin constant.

Set type to the name of one of the other fields, and set only that field.

literal number: Create from a literal floating-point value.
variable string: Create from a named reference name.
builtin BuiltinConstant: Create from a named builtin constant; the server resolves the numeric value.

DriverSeries#

Uses the driver series timestamps as the alignment grid.

An empty JSON object, {}.

DropSeriesDataset#

Removes series from the base dataset by name: raw and derived series alike are no longer selectable under those names. Dropping a name absent from input has no effect. Combined with WithSeriesDataset, which can expose a series under another name, this renames a series: dropSeries(withSeries(input, [newName = select(oldName)]), [oldName]).

input Dataset required: The base dataset to drop series from.
names array of StringConstant: Names of the series to drop.

DurationAdd#

The sum of two durations.

left compute.api.Duration required: First duration.
right compute.api.Duration required: Second duration.

DurationConstant#

A duration constant that can be a literal value or a named variable reference.

Set type to the name of one of the other fields, and set only that field.

literal run.api.Duration: Create from a literal duration value.
variable string: Create from a named reference name.

DurationDays#

Constructs a duration from a number of days.

days IntegerConstant required: The number of days.

DurationFilterRanges#

Filters a list of ranges down to only those satisfying a threshold condition on the range’s duration.

input RangeSeries required
threshold DurationConstant required
operator ThresholdOperator required
unboundedBehavior UnboundedBehavior

DurationFilterRangesV2#

Filters ranges by duration using an authored Duration expression.

input RangeSeries required
duration compute.api.Duration required: The duration each input range is compared against.
unboundedBehavior UnboundedBehavior: How a range with an open start or end is measured. Defaults to treating the missing bound as the edge of the compute request window.
comparison ThresholdOperator required

DurationHours#

Constructs a duration from a number of hours.

hours IntegerConstant required: The number of hours.

DurationMilliseconds#

Constructs a duration from a number of milliseconds.

milliseconds IntegerConstant required: The number of milliseconds.

DurationMinutes#

Constructs a duration from a number of minutes.

minutes IntegerConstant required: The number of minutes.

DurationNanoseconds#

Constructs a duration from a number of nanoseconds. Limited to values within the 32-bit integer range (~2.1 billion ns, or ~2.1 seconds). For larger durations, use DurationSeconds or DurationMilliseconds.

nanoseconds IntegerConstant required: The number of nanoseconds.

DurationNegate#

Negates a duration (reverses its sign).

input compute.api.Duration required: The duration to negate.

DurationSeconds#

Constructs a duration from a number of seconds.

seconds IntegerConstant required: The number of seconds.

DurationSubtract#

The difference of two durations (left minus right).

left compute.api.Duration required: Duration to subtract from.
right compute.api.Duration required: Duration to subtract.

EarliestAnchorReference#

Selects the earliest anchor resolved from the input.

An empty JSON object, {}.

Empty#

An empty JSON object, {}.

Enum1dArraySelectTagsSeries#

Subsets the tag dimensions of the input enum 1d array series to the given tag keys. Preserves the input series’ cardinality: points that share the selected keys but differ on dropped keys remain distinct.

input Enum1dArraySeries required
tagKeys array of StringConstant

Enum1dArraySeries#

Set type to the name of one of the other fields, and set only that field.

channel ChannelSeries
raw Reference
derived DerivedSeries
selectEnum1dArray SelectSeries
extractFromStruct ExtractEnum1dArrayFromStructSeries
toStartOfInterval Enum1dArrayToStartOfIntervalSeries
timeShift Enum1dArrayTimeShiftSeries
filterByTag Enum1dArrayTagFilterSeries
selectTags Enum1dArraySelectTagsSeries

Enum1dArrayTagFilterSeries#

Applies a tag predicate to the enum 1d array series produced by input.

input Enum1dArraySeries required
predicate TagPredicate required

Enum1dArrayTimeShiftSeries#

input Enum1dArraySeries required
duration DurationConstant required

Enum1dArrayToStartOfIntervalSeries#

Snaps each point’s timestamp to the start of its enclosing fixed-size time bucket. Buckets are epoch-aligned: a point at timestamp t (nanoseconds) is rewritten to floor(t / window) * window. Values and tag groupings are preserved; aggregation of points that collide on the snapped timestamp is the responsibility of downstream nodes.

input Enum1dArraySeries required
window compute.api.Duration required

EnumAggregation#

Aggregates an input series using an enum aggregation operator. Rolling aggregation builders are not supported; only the group-by shape is accepted at resolution time. Min and Max require a categorical input series. Udf also accepts a numeric input, which reaches the function as Vec<f64>; a categorical input reaches it as Vec<String>.

input AggregationBuilder required: The aggregation shape to apply the operator over. Only the group-by shape is supported; rolling builders are rejected at resolution time. The Python enum_aggregation(...) sugar form is categorical-only. Numeric builders expose the UDF-only enum_udf(...) and rust_enum_udf(...) terminals instead.
operator EnumAggregationOperator required: The enum reduction applied to each group (min, max, or a user-defined function).

EnumAggregationFunction#

Aggregates duplicate timestamps on a single enum series. For aggregating across tag groupings, use EnumSeries.enumAggregation with aggregation.AggregationBuilder.groupBy.

MIN
MAX

EnumAggregationOperator#

Set type to the name of one of the other fields, and set only that field.

min Empty
max Empty
udf EnumAggregationUdf

EnumAggregationUdf#

A user-defined enum aggregation. The supported ABI is a Rust function with one vector input and a String return value. Numeric input series use Vec<f64> and enum input series use Vec<String>.

source UdfSource required

EnumConstantResampleInterpolationConfiguration#

Fills all empty resample intervals with a single constant value.

If a resampled time interval (bucket) contains no data points from the input, it will be assigned the specified ‘constant’ as a default value. This applies to gaps at the start of the series, between data points, and at the end.

constant StringConstant required

EnumCountDuplicateSeries#

Counts the number of points along each timestamp in the input series.

inputs array of EnumSeries

EnumFilterOperator#

IS_IN: True when the value is contained in the set.
IS_NOT_IN: True when the value is not contained in the set.
MATCHES_ANY_REGEX: True when the value matches at least one pattern in the set. Values are RE2 regular expressions, anchored to the entire string.

EnumFilterRanges#

Produces a list of ranges for which the filter condition is satisfied.

input EnumSeries required
operator EnumFilterOperator required
values StringSetConstant required: The set of literal values (for IS_IN / IS_NOT_IN) or RE2 regex patterns (for MATCHES_ANY_REGEX) to match against.
persistenceWindowConfiguration PersistenceWindowConfiguration

EnumFilterTransformationSeries#

Outputs categorical input values that fall within the supplied ranges.

input EnumSeries required
filter RangeSeries required: Keeps only input points whose timestamp falls inside one of these ranges.

EnumNthPointDownsampleSeries#

Keeps every Nth row of the timestamp-ordered input, per series. No grid arithmetic, no interpolation, no boundary handling. Output count is ceil(input_count / n) per series. Caller is responsible for choosing n consistent with the input’s sample rate; output spacing is only uniform when the input is.

input EnumSeries required
n IntegerConstant required: Keep every Nth point starting from the earliest in each series. Must be >= 1.

EnumResampleConfiguration#

interval DurationConstant required: Interval between resampled points
interpolation EnumResampleInterpolationConfiguration: Interpolation strategy to use (defaults to forward fill).

EnumResampleInterpolationConfiguration#

Set type to the name of one of the other fields, and set only that field.

forwardFillResampleInterpolationConfiguration ForwardFillResampleInterpolationConfiguration
constantResampleInterpolationConfiguration EnumConstantResampleInterpolationConfiguration

EnumResampleSeries#

Resamples the input series to a new resolution using interpolation. Outputs data for timestamps corresponding to the defined frequency. Based on interpolation strategy, determines range of timestamps to output data for and interpolates values where necessary.

input EnumSeries required
resampleConfiguration EnumResampleConfiguration required: The interval at which to resample the series and interpolation strategy

EnumResampleSeriesV2#

Resamples categorical points at the authored interval using forward-fill interpolation.

input EnumSeries required
interval compute.api.Duration required: Interval at which to resample.

EnumSelectTagsSeries#

Subsets the tag dimensions of the input enum series to the given tag keys. Preserves the input series’ cardinality: points that share the selected keys but differ on dropped keys remain distinct.

input EnumSeries required
tagKeys array of StringConstant

EnumSeries#

Set type to the name of one of the other fields, and set only that field.

aggregate AggregateEnumSeries deprecated: Deprecated: AggregateEnumSeries is deprecated. Use enumAggregation with aggregation.GroupByAggregationBuilder instead.
raw Reference
channel ChannelSeries
derived DerivedSeries
resample EnumResampleSeries
resampleV2 EnumResampleSeriesV2
nthPointDownsample EnumNthPointDownsampleSeries
timeRangeFilter EnumTimeRangeFilterSeries
timeShift EnumTimeShiftSeries
timeShiftV2 EnumTimeShiftSeriesV2
union EnumUnionSeries
filterTransformation EnumFilterTransformationSeries
valueMap ValueMapSeries
select1dArrayIndex SelectIndexFrom1dEnumArraySeries
extractFromStruct ExtractEnumFromStructSeries
eventAggregation EventsEnumSeries
enumAggregation EnumAggregation
selectEnum SelectSeries
selectCategoricalProperty SelectProperty
filterByTag EnumTagFilterSeries
selectTags EnumSelectTagsSeries
scalarUdf ScalarUdfSeries
toStartOfInterval EnumToStartOfIntervalSeries

EnumSeriesEqualityRanges#

Produces a list of ranges for which provided enum series are all equal (or are not all equal).

input array of EnumSeries
equalityOperator EqualityOperator required
persistenceWindowConfiguration PersistenceWindowConfiguration
interpolationConfiguration InterpolationConfiguration deprecated: Defaults to forward fill interpolation with a 1s interpolation radius Deprecated: Setting interpolation on this node is deprecated.

EnumTagFilterSeries#

Applies a tag predicate to the enum series produced by input.

input EnumSeries required
predicate TagPredicate required

EnumTimeRangeFilterSeries#

Filters the series to points within the specified time range.

input EnumSeries required
startTime TimestampConstant: Represents the start time (inclusive) of the time range.
endTime TimestampConstant: Represents the end time (inclusive) of the time range.

EnumTimeShiftSeries#

input EnumSeries required
duration DurationConstant required

EnumTimeShiftSeriesV2#

Shifts the timestamps in the input series by the resolved duration.

input EnumSeries required
duration compute.api.Duration required: Duration to shift the input series by.

EnumToNumericSeries#

Maps an enumerated series to a numeric series by mapping each string value to a double.

input EnumSeries required
mapping map of string to DoubleConstant: The mapping from enum values to doubles.
defaultValue DoubleConstant: The value to use for enum values not present in the mapping. If not specified, points with unmapped enum values will be dropped.

EnumToStartOfIntervalSeries#

input EnumSeries required
window compute.api.Duration required

EnumUnionOperation#

THROW: Throws an exception if two series contain points with a duplicate timestamp.
MAX: Aggregates duplicates by String MAX.
MIN: Aggregates duplicates by String MIN.

EnumUnionSeries#

Combines multiple enum series together and outputs a single series. The strategy to merge input values with the same timestamp together is specified in the operation field.

input array of EnumSeries
operation EnumUnionOperation required: The strategy to merge points with duplicate timestamps.

EqualityOperator#

ALL_EQUAL
NOT_ALL_EQUAL

EqualToSeries#

Compares two numeric series point-wise, producing true where left == right and false otherwise.

left NumericSeries required
right NumericSeries required

EventAnchor#

Uses the start timestamp of the event at the configured zero-based index from this query whose event time lies in the anchor window [start, end), or [start, +infinity) when the end is absent. The window is the run bounds for a run anchor. Shares the wire shape of numeric.EventTimeShift, which tagByIntervals time shifts use; a separate type so dataset anchors evolve independently.

query ComputeEventQuery required
index IntegerConstant: Zero-based event index after sorting. Defaults to zero and must be non-negative.
sortOrder EventSortOrder: Ordering by event start timestamp before selecting the index. Defaults to ASC.

EventDispositionStatus#

PENDING_REVIEW
CLOSED_IGNORED
CLOSED_REQUIRES_FURTHER_ACTION
NO_DISPOSITION

EventIntervalSource#

Intervals come from an event query. Each event defines [timestamp, timestamp+duration).

query ComputeEventQuery required
tagBy array of EventTagSource: Non-empty ordered list of tag sources. Each contributes a tag key-value pair per event interval.

EventLabelTag#

label StringConstant required

EventLevelTag#

An empty JSON object, {}.

EventPropertyTag#

propertyName StringConstant required

EventsEnumSeries#

Queries events and emits an enum series where each data point corresponds to an event and the enum value is derived from a single event field (property, label, etc).

query ComputeEventQuery required
valueSource EventsEnumValueSource required

EventsEnumValueSource#

Set type to the name of one of the other fields, and set only that field.

property StringConstant: Name of the event property whose value should be used as the enum value.
level Empty: The event level (INFO, FLAG, VIOLATION, SUCCESS). This field corresponds to the event type.

EventSortOrder#

ASC
DESC

EventsSearchRanges#

Produces a range series with a range for each event matching the query. Throws if there are more than 1,000 results.

query ComputeEventQuery required

EventTagSource#

A dimension contributing a tag key-value pair per event interval.

Set type to the name of one of the other fields, and set only that field.

intervalIndex IntervalIndexTag
level EventLevelTag
property EventPropertyTag
label EventLabelTag
rangeStartTimestamp IntervalStartTimestampTag

EventTimeFilter#

timestamp TimestampConstant required
timestampCondition EventTimeFilterCondition required

EventTimeFilterCondition#

START_TIME_BEFORE_INCLUSIVE
START_TIME_BEFORE_EXCLUSIVE
START_TIME_AFTER_INCLUSIVE
START_TIME_AFTER_EXCLUSIVE
END_TIME_BEFORE_INCLUSIVE
END_TIME_BEFORE_EXCLUSIVE
END_TIME_AFTER_INCLUSIVE
END_TIME_AFTER_EXCLUSIVE

EventTimeShift#

Shift by the start timestamp of the event at the configured zero-based index from this query whose event time lies in the anchor window [start, end), or [start, +infinity) when the end is absent. The window is the tagging interval for tagByIntervals and the run bounds for a run anchor. The query may differ from the query that produced a tagging interval.

query ComputeEventQuery required
index IntegerConstant: Zero-based event index after sorting. Defaults to zero and must be non-negative.
sortOrder EventSortOrder: Ordering by event start timestamp before selecting the index. Defaults to ASC.

EventType#

INFO
FLAG
ERROR
SUCCESS

EveryNthPerSeriesSampling#

Returns every Nth timestamp-ordered point from each distinct series.

n IntegerConstant required: Keep every Nth point starting from the earliest in each series. Must be > 1.

ExcludeNegativeValues#

An empty JSON object, {}.

ExponentialCurve#

An empty JSON object, {}.

ExtractEnum1dArrayFromStructSeries#

input StructSeries required
fieldPath array of StringConstant

ExtractEnumFromStructSeries#

input StructSeries required
fieldPath array of StringConstant: Path segments that are joined to locate a nested enum field. Use dots to traverse objects (e.g. a.b.c) and 0-based brackets to index into arrays (e.g. items[0].value). A bare numeric name like 0 refers to an object key named “0”; use [0] to index into an array. Rows where the path is invalid or resolves to a nested object rather than a scalar are filtered out.

ExtractNumeric1dArrayFromStructSeries#

input StructSeries required
fieldPath array of StringConstant

ExtractNumericFromStructSeries#

input StructSeries required
fieldPath array of StringConstant: Path segments that are joined to locate a nested numeric field. Use dots to traverse objects (e.g. a.b.c) and 0-based brackets to index into arrays (e.g. items[0].value). A bare numeric name like 0 refers to an object key named “0”; use [0] to index into an array. Rows where the path is invalid or the value cannot be converted to the specified type are filtered out.
dataType NumericDataType: The type the numeric data will be cast to, defaults to FLOAT64

ExtractStructFromStructSeries#

input StructSeries required
fieldPath array of StringConstant: Path segments that are joined to locate a nested struct field. Use dots to traverse objects (e.g. a.b.c) and 0-based brackets to index into arrays (e.g. items[0].value). A bare numeric name like 0 refers to an object key named “0”; use [0] to index into an array. Returns an empty struct when the path does not resolve to a valid JSON object.

ExtremaRangesV2#

Produces ranges for the selected extrema type.

input NumericSeries required
minimumProminence DoubleConstant: The minimum topographic prominence for an extrema to be returned.
selection PeakType required

FillLimit#

How far forward in time a sample’s value may be carried.

Set type to the name of one of the other fields, and set only that field.

duration DurationConstant

FillStrategy#

Default strategy for filling gaps when aligning multi-input series.

Set type to the name of one of the other fields, and set only that field.

forwardFill ForwardFill

FilterByExpressionSeries#

Keeps points from the base series where the boolean expression evaluates to true. Only outputs timestamps where all input series have an entry for that timestamp, or a value can be filled using the interpolation configuration.

base string required: The variable name for the series that will be returned by this filter. The expression can filter points conditional on multiple series. The base defines which series’ points will be returned after applying all the filters.
inputs map of LocalVariableName to NumericSeries: A map containing all the numeric series present in the expression.
expression string required: An expression that evaluates to a boolean. For example - a > 5.
interpolationConfiguration InterpolationConfiguration deprecated: Defaults to forward fill interpolation with a 1s interpolation radius Deprecated: Setting interpolation on this node is deprecated.

FilteredDataset#

Applies a conjunctive tag predicate to the series produced by the inner dataset. Resolved by threading tag filters into channel specs and folding against known tag assignments; does not add a resolved numeric node.

input Dataset required: The underlying dataset to filter.
predicate TagPredicate required: Conjunctive tag predicate used to keep matching series.

FirstPointMatchingCondition#

The first point in the output range will be the first point where the condition evaluates to true.

An empty JSON object, {}.

FloorDivide#

Divides left by right pointwise and rounds down to the nearest integer.

left NumericSeries required: Numerator.
right NumericSeries required: Denominator.

ForwardFill#

At each grid point, carries the most recent prior sample value forward. The value is held only up to the configured limit; grid points with no prior sample within that window are left empty.

limit FillLimit required

ForwardFillInterpolation#

interpolationRadius DurationConstant required

ForwardFillResampleInterpolationConfiguration#

Forward fill interpolation for resampling. Rounds the earliest and latest timestamp up to the nearest interval multiple and generates timestamps at the given interval between the new earliest and latest timestamps. For every timestamp in the resampled timestamps, takes the last known value before the timestamp as the value.

An empty JSON object, {}.

FunctionDerivedSeries#

A reference to a derived series resulting from applying a function to a set of arguments.

moduleName StringConstant required
functionName StringConstant required
versionReference ModuleVersionReference required
functionArgs map of FunctionParameterName to FunctionParameterValue: Map of function input names to their values. The function inputs must match the function’s parameter names and types. An input must be specified for each of the referenced function’s parameters.

FunctionParameterValue#

Set type to the name of one of the other fields, and set only that field.

variable string
value VariableValue

FunctionVariables#

variables map of VariableName to VariableValue
subFunctionVariables map of FunctionReference to FunctionVariables

GetDatasetMetadataRequest#

Dataset metadata request.

dataset Dataset required
context Context required

GreaterThanOrEqualToSeries#

Compares two numeric series point-wise, producing true where left >= right and false otherwise.

left NumericSeries required
right NumericSeries required

GreaterThanSeries#

Compares two numeric series point-wise, producing true where left > right and false otherwise.

left NumericSeries required
right NumericSeries required

GroupByAggregationBuilder#

Groups points by a tag selection and a timestamp policy and applies the operator.

input Series required: The series to group and aggregate.
tags GroupByTags required: Selects which tag keys form the grouping key: GroupByTags.Current() keeps the input series’ currently selected tags, or GroupByTags.Subset([...]) restricts the grouping to a subset of them.
timestamp GroupByTimestamp required: Selects how timestamps participate in the grouping key: GroupByTimestamp.Current() groups on existing timestamps, and GroupByTimestamp.Every(duration) buckets points into fixed-size, epoch-aligned tumbling windows.
alignment GroupByAlignment: Optionally aligns source tag groups that map to the same output tag group before aggregation. Alignment is currently supported only with GroupByTimestamp.Current() and built-in numeric aggregation operators.

GroupByAlignment#

Selects how source tag groups are aligned before aggregation.

Set type to the name of one of the other fields, and set only that field.

contextDefaults Empty: Use the compute context’s defaultAlignmentStrategy and defaultFillStrategy.

GroupBySubsetTags#

tags array of StringConstant: Tag keys to group by.

GroupByTags#

Selects which tag keys form the grouping key.

Set type to the name of one of the other fields, and set only that field.

current Empty: Group by the tags currently selected on the input series.
subset GroupBySubsetTags: Group by exactly the listed tag keys. Must be a (non-strict) subset of the input series’s currently selected tags.

GroupByTimestamp#

Selects how timestamps participate in the grouping key.

Set type to the name of one of the other fields, and set only that field.

current Empty: Use the current timestamps.
every compute.api.Duration: Bucket timestamps into a tumbling fixed-size, epoch-aligned window. A point at timestamp t (nanoseconds) falls into the bucket [floor(t / window) * window, +window), and one aggregated point is emitted per bucket per tag grouping at the bucket start timestamp.

GroupWithinRangesSeriesV2#

Aggregates the input series within each supplied range and emits one point at the range start. Empty ranges emit no point, and ranges without a start use the compute request start.

input NumericSeries required
ranges RangeSeries required: One output point is emitted per range, at the range’s start.
aggregation NumericAggregationOperator required

HashSubsampleSampling#

Keeps approximately 1/N of raw points via a stateless hash of each point’s timestamp.

n IntegerConstant required: Keep approximately one out of every N points. Must be > 1.

HighPassConfiguration#

cutoffFrequency DoubleConstant required

IdentityDimension#

Injects the value of a type’s primary key, under a tag key equal to the primary key’s property name by default. The primary key is read when the query runs, so it follows changes to the type. Only asset branches of an asset with the type have a value; every other branch, including run branches, gets the reserved value NOMINAL_ABSENT.

typeRid StringConstant required: Resource identifier of the type whose primary key identifies the asset.

IntegerConstant#

An integer constant that can be a literal value or a named variable reference.

Set type to the name of one of the other fields, and set only that field.

literal integer: Create from a literal integer value.
variable string: Create from a named reference name.

IntegralSeries#

Calculates the running sum of the area underneath a series using the trapezoidal rule.

input NumericSeries required
startTimestamp TimestampConstant required
timeUnit TimeUnit: Time unit used to calculate the integral. Defaults to seconds if not specified.

InterpolationConfiguration#

Set type to the name of one of the other fields, and set only that field.

forwardFillInterpolation ForwardFillInterpolation

IntersectRanges#

Produces the intersection of the input ranges: the ranges of time covered by every input. For best performance, pass inputs in the order in which they should be evaluated, listing the ranges that are cheapest to compute first.

inputs array of RangeSeries

IntervalAnchor#

Selects which boundary of an interval to use as its anchor.

Set type to the name of one of the other fields, and set only that field.

intervalStart IntervalStartTimeShift: Uses the interval’s start timestamp.
intervalEnd IntervalEndTimeShift: Uses the interval’s end timestamp.
eventInInterval EventAnchor
rangeInInterval RangesAnchor

IntervalEndTimeShift#

Shift by each tagging interval’s resolved end; resolution throws if end is missing.

An empty JSON object, {}.

IntervalIndexTag#

An empty JSON object, {}.

IntervalSource#

Where the intervals come from and how each is labeled.

Set type to the name of one of the other fields, and set only that field.

events EventIntervalSource
ranges RangeIntervalSource

IntervalStartTimeShift#

Shift by each tagging interval’s resolved start; resolution throws if start is missing.

An empty JSON object, {}.

IntervalStartTimestampTag#

An empty JSON object, {}.

LabelsFilter#

operator SetOperator required
labels array of string

LessThanOrEqualToSeries#

Compares two numeric series point-wise, producing true where left <= right and false otherwise.

left NumericSeries required
right NumericSeries required

LessThanSeries#

Compares two numeric series point-wise, producing true where left < right and false otherwise.

left NumericSeries required
right NumericSeries required

LiteralRange#

A literal range of values.

startTimestamp TimestampConstant
endTimestamp TimestampConstant
tags map of string to string

LiteralRanges#

A list of literal ranges.

literalRanges array of LiteralRange

Ln#

Computes the natural logarithm (base e) of each value.

x NumericSeries required: Input numeric series (positive values).

Log10#

Computes the base-10 logarithm of each value.

x NumericSeries required: Input numeric series (positive values).

LogArgFilterOperator#

Matches against a single log arg.

key StringConstant required
operator LogRegexFilterOperator required

LogarithmicCurve#

An empty JSON object, {}.

LogExactMatchCaseInsensitiveFilter#

Filters points such that the log message in each point contains an exact case-insensitive match of the provided token.

token string required

LogFilterOperator#

Set type to the name of one of the other fields, and set only that field.

regexFilter LogRegexFilterOperator
exactMatchCaseInsensitiveFilter LogExactMatchCaseInsensitiveFilter
arg LogArgFilterOperator
and array of LogFilterOperator
or array of LogFilterOperator
not LogFilterOperator

LogFilterSeries#

Outputs only values of the log plot that satisfy the filter.

input LogSeries required
operator LogFilterOperator required

LogRegexFilterOperator#

Matches a text value against the given re2 regular expression. Regular expression syntax: https://github.com/google/re2/wiki/Syntax.

regex string required

LogSelectTagsSeries#

Subsets the tag dimensions of the input log series to the given tag keys. Preserves the input series’ cardinality: points that share the selected keys but differ on dropped keys remain distinct.

input LogSeries required
tagKeys array of StringConstant

LogSeries#

Set type to the name of one of the other fields, and set only that field.

raw Reference
channel ChannelSeries
derived DerivedSeries
selectLogs SelectSeries
union LogUnionSeries
filter LogFilterSeries
timeShift LogTimeShiftSeries
toStartOfInterval LogToStartOfIntervalSeries
filterByTag LogTagFilterSeries
selectTags LogSelectTagsSeries

LogTagFilterSeries#

Applies a tag predicate to the log series produced by input.

input LogSeries required
predicate TagPredicate required

LogTimeShiftSeries#

input LogSeries required
duration DurationConstant required

LogToStartOfIntervalSeries#

input LogSeries required
window compute.api.Duration required

LogUnionOperation#

KEEP_ALL: Keeps all points if multiple series contain points with a duplicate timestamp.

LogUnionSeries#

Combines multiple log series together and outputs a single series. The strategy to merge input values with the same timestamp together is specified in the operation field.

input array of LogSeries
operation LogUnionOperation required: The strategy to merge points with duplicate timestamps.

LowPassConfiguration#

cutoffFrequency DoubleConstant required

MathConstant#

Math constants referenceable by name.

PI: The circle constant π (dimensionless).
TAU: The circle constant τ = 2π (dimensionless).
E: Euler’s number e (dimensionless).

Maximum#

The maximum value of points inside the time window.

An empty JSON object, {}.

MaxSeries#

For every timestamp specified in the input series, outputs a value that is the maximum for that timestamp across all input series. Only outputs timestamps where all input series have an entry for that timestamp, subject to interpolation.

inputs array of NumericSeries: Input series across which to take the pointwise maximum
interpolationConfiguration InterpolationConfiguration deprecated: Defaults to forward fill interpolation with a 1s interpolation radius Deprecated: Setting interpolation on this node is deprecated.

MeanSeries#

For every timestamp specified in the input series, outputs a value that is the mean for that timestamp across all input series. Only outputs timestamps where all input series have an entry for that timestamp, subject to interpolation.

inputs array of NumericSeries: Input series across which to take the pointwise mean
interpolationConfiguration InterpolationConfiguration deprecated: Defaults to forward fill interpolation with a 1s interpolation radius Deprecated: Setting interpolation on this node is deprecated.

Minimum#

The minimum value of points inside the time window.

An empty JSON object, {}.

MinMaxThresholdOperator#

OUTSIDE_BOUNDS
OUTSIDE_OR_EQUAL_TO_BOUNDS
INSIDE_BOUNDS
INSIDE_OR_EQUAL_TO_BOUNDS

MinMaxThresholdRanges#

Produces a list of ranges for which the threshold condition is satisfied.

input NumericSeries required
lowerBound DoubleConstant required
upperBound DoubleConstant required
operator MinMaxThresholdOperator required
persistenceWindowConfiguration PersistenceWindowConfiguration

MinSeries#

For every timestamp specified in the input series, outputs a value that is the minimum for that timestamp across all input series. Only outputs timestamps where all input series have an entry for that timestamp, subject to interpolation.

inputs array of NumericSeries: Input series across which to take the pointwise minimum
interpolationConfiguration InterpolationConfiguration deprecated: Defaults to forward fill interpolation with a 1s interpolation radius Deprecated: Setting interpolation on this node is deprecated.

ModuleVersionReference#

Set type to the name of one of the other fields, and set only that field.

pinned PinnedModuleVersionReference

Modulo#

Computes the remainder of left divided by right pointwise.

left NumericSeries required: Dividend.
right NumericSeries required: Divisor.

Multiply#

Multiplies two numeric series pointwise.

left NumericSeries required: Left-hand operand.
right NumericSeries required: Right-hand operand.

NamedSeries#

name StringConstant required: Name of the new derived series.
definition Series required: Compute expression defining the series values.

Negate#

Negates each value in the series pointwise (multiplies by -1).

x NumericSeries required: Input numeric series.

NegativeValueConfiguration#

Set type to the name of one of the other fields, and set only that field.

allowNegativeValues AllowNegativeValues: Include negative output values
setNegativeValuesToZero SetNegativeValuesToZero: Set negative output values to zero
excludeNegativeValues ExcludeNegativeValues: Exclude points with negative output values

NotEqualToSeries#

Compares two numeric series point-wise, producing true where left != right and false otherwise.

left NumericSeries required
right NumericSeries required

NotRanges#

The not ranges node will invert the ranges, filling the negative space in time.

input RangeSeries required

Numeric1dArraySelectTagsSeries#

Subsets the tag dimensions of the input numeric 1d array series to the given tag keys. Preserves the input series’ cardinality: points that share the selected keys but differ on dropped keys remain distinct.

input Numeric1dArraySeries required
tagKeys array of StringConstant

Numeric1dArraySeries#

Set type to the name of one of the other fields, and set only that field.

channel ChannelSeries
raw Reference
derived DerivedSeries
selectNumeric1dArray SelectSeries
extractFromStruct ExtractNumeric1dArrayFromStructSeries
toStartOfInterval Numeric1dArrayToStartOfIntervalSeries
timeShift Numeric1dArrayTimeShiftSeries
filterByTag Numeric1dArrayTagFilterSeries
selectTags Numeric1dArraySelectTagsSeries

Numeric1dArrayTagFilterSeries#

Applies a tag predicate to the numeric 1d array series produced by input.

input Numeric1dArraySeries required
predicate TagPredicate required

Numeric1dArrayTimeShiftSeries#

input Numeric1dArraySeries required
duration DurationConstant required

Numeric1dArrayToStartOfIntervalSeries#

input Numeric1dArraySeries required
window compute.api.Duration required

NumericAggregation#

Aggregates an input series using the given operator. The shape of the aggregation (rolling time window, rolling point-count window, or group by) is selected by the aggregation builder passed as input. The operator must be compatible with that builder’s series, producing a numeric output: count reduces a series of any type, whereas SUM requires a numeric series.

input AggregationBuilder required: The aggregation shape to apply the operator over: a rolling time window, a rolling point-count window, or a group-by.
operator NumericAggregationOperator required: The reduction applied to each window or group (e.g. sum, mean, percentile). Must be compatible with the input series, producing a numeric output: Count works on any input series, whereas reductions like Sum require a numeric series.

NumericAggregationFunction#

DEPRECATED. Use NumericAggregationOperator instead.

SUM
MEAN
MIN
MAX
COUNT
STANDARD_DEVIATION
ROOT_MEAN_SQUARE

NumericAggregationOperator#

Unified numeric aggregation used across rolling windows, plain aggregates, range aggregates, union merges, and per-bucket summarization.

Set type to the name of one of the other fields, and set only that field.

sum Summation
average Average
min Minimum
max Maximum
count Count
standardDeviation StandardDeviation
rootMeanSquare RootMeanSquare
percentile Percentile
udf NumericAggregationUdf

NumericAggregationUdf#

A user-defined numeric aggregation. The aggregation builder controls grouping/windowing. Supported Rust entrypoints accept grouped value vectors, optionally with leading sample timestamps, and return either one numeric value or timestamped numeric point(s), e.g. fn rms(values: Vec<f64>) -> f64, fn energy(timestamp_ns: Vec<i64>, values: Vec<f64>) -> f64, fn first(timestamp_ns: Vec<i64>, values: Vec<f64>) -> (i64, f64), or fn passthrough(timestamp_ns: Vec<i64>, values: Vec<f64>) -> Vec<(i64, f64)>. The value vector’s element type follows the aggregated series: Vec<f64> for a numeric series, and Vec<String> for a categorical or struct series, where each struct row arrives as a JSON object. A UDF over a combined struct series may instead take one vector per named struct field it needs, e.g. fn mean_product(channel0: Vec<f64>, channel1: Vec<f64>) -> f64. Parameter names select the fields, so a subset of the struct’s fields in any order is accepted.

source UdfSource required

NumericApproximateFilterSeries#

Outputs the values of the numeric plot value that are approximately equal to the threshold value.

input NumericSeries required
threshold DoubleConstant required
tolerance DoubleConstant required
operator ApproximateThresholdOperator required

NumericConstantResampleInterpolationConfiguration#

Fills all empty resample intervals with a single constant value.

constant DoubleConstant required

NumericDataType#

Supported numeric data types for value casting.

INT64
FLOAT64
UINT64

NumericEqualityRangesV2#

Produces ranges where all numeric inputs are equal or are not all equal.

inputs array of NumericSeries: The series compared against each other. At least two are required.
tolerance DoubleConstant: Maximum spread between the inputs still counted as equal. Defaults to zero, i.e. exact equality.
minPoints IntegerConstant: Minimum number of matching points. Defaults to 1.
minDuration compute.api.Duration: Minimum matching duration. Defaults to one nanosecond.
rangeStart RangeStart: Selects whether the output begins at the first match or after persistence is satisfied.
equalityOperator EqualityOperator required

NumericFilterTransformationSeries#

Outputs the input points whose timestamps fall within the supplied ranges.

input NumericSeries required
filter RangeSeries required: Keeps input points whose timestamps fall inside any of these ranges.

NumericFilterWhereSeries#

Outputs numeric input values where the provided Boolean expression evaluates to true.

input NumericSeries required
condition BooleanSeries required: Condition evaluated point-wise at each input timestamp. A point is only kept where the condition is true.

NumericIfElseSeries#

Selects between two numeric series point-wise based on a boolean condition series. For every aligned timestamp, emits the value from trueValue where condition is true, and the value from falseValue otherwise.

condition BooleanSeries required: Boolean series evaluated at each point to choose between the trueValue and falseValue branches.
trueValue NumericSeries required: Value emitted at points where condition is true.
falseValue NumericSeries required: Value emitted at points where condition is false.

NumericLargestTriangleThreeBucketsSeries#

Applies Largest-Triangle-Three-Buckets to a numeric time series for visualization-oriented downsampling. The algorithm preserves the first and last points, partitions the remaining input points based on the requested output count, and selects points that preserve the visual shape of the series. Results are selected input timestamp/value points, not fixed-width bucket aggregate rows.

input NumericSeries required
maxPointsToReturn IntegerConstant required: Maximum number of selected points to return. Must be positive and no greater than 10,000.

NumericNanFilter#

Removes points where the value is NaN from the input series.

input NumericSeries required: Input numeric series.

NumericNthPointDownsampleSeries#

input NumericSeries required
n IntegerConstant required: Keep every Nth point starting from the earliest in each series. Must be >= 1.

NumericPropertyPredicate#

Matches resources that have a numeric value for the named property and whose value satisfies the operator. NEQ excludes resources that lack the property or store a string value under the same name.

name string required
value number required
operator PropertyComparisonOperator required

NumericPropertyRangeOperator#

BETWEEN
NOT_BETWEEN

NumericPropertyRangePredicate#

Inclusive range on a numeric property. At least one bound is required. BETWEEN: min <= x <= max. An absent bound is unbounded on that side. NOT_BETWEEN: x < min OR x > max. An absent bound drops that side. Both operators require a numeric value for name. Missing properties and string values never match. Bounds are closed [min, max] to match the number chip (is between / is not between), not half-open.

name string required
min number
max number
operator NumericPropertyRangeOperator required

NumericResampleConfiguration#

interval DurationConstant required: Interval between resampled points
interpolation NumericResampleInterpolationConfiguration: Interpolation strategy to use (defaults to forward fill).

NumericResampleInterpolationConfiguration#

Set type to the name of one of the other fields, and set only that field.

forwardFillResampleInterpolationConfiguration ForwardFillResampleInterpolationConfiguration
constantResampleInterpolationConfiguration NumericConstantResampleInterpolationConfiguration

NumericResampleSeries#

input NumericSeries required
resampleConfiguration NumericResampleConfiguration required: The interpolation strategy and interval at which to resample the series

NumericResampleSeriesV2#

Resamples the input series at the authored interval using forward-fill.

input NumericSeries required
interval compute.api.Duration required: Interval at which to resample.

NumericSelectTagsSeries#

Subsets the tag dimensions of the input numeric series to the given tag keys. Preserves the input series’ cardinality: points that share the selected keys but differ on dropped keys remain distinct.

input NumericSeries required
tagKeys array of StringConstant

NumericSeries#

Set type to the name of one of the other fields, and set only that field.

abs Abs
negate Negate
cos Cos
sin Sin
tan Tan
acos Acos
asin Asin
ln Ln
log10 Log10
sqrt Sqrt
add Add
subtract Subtract
multiply Multiply
divide Divide
floorDivide FloorDivide
power Power
modulo Modulo
atan2 Atan2
max MaxSeries
mean MeanSeries
min MinSeries
sum SumSeries
union NumericUnionSeries
product ProductSeries
constant ConstantNumericSeries
selectNewestPoints SelectNewestPointsSeries
selectNumeric SelectSeries
selectNumericProperty SelectProperty
selectOldestPoints SelectOldestPointsSeries
bitAnd BitAnd
bitOr BitOr
bitXor BitXor
bitShiftRight BitShiftRight
bitShiftLeft BitShiftLeft
bitTest BitTest
ifElse NumericIfElseSeries
numericAggregation NumericAggregation
countDuplicate EnumCountDuplicateSeries
cumulativeSum CumulativeSumSeries
derivative DerivativeSeries
integral IntegralSeries
zScore ZscoreSeries
raw Reference
derived DerivedSeries
resample NumericResampleSeries
resampleV2 NumericResampleSeriesV2
nthPointDownsample NumericNthPointDownsampleSeries
largestTriangleThreeBuckets NumericLargestTriangleThreeBucketsSeries
signalFilter SignalFilterSeries
timeDifference TimeDifferenceSeries
absoluteTimestamp AbsoluteTimestampSeries
timeRangeFilter NumericTimeRangeFilterSeries
timeShift NumericTimeShiftSeries
timeShiftV2 NumericTimeShiftSeriesV2
unitConversion UnitConversionSeries
unitOverride UnitOverrideSeries
valueDifference ValueDifferenceSeries
filterTransformation NumericFilterTransformationSeries
filterWhere NumericFilterWhereSeries
thresholdFilter NumericThresholdFilterSeries
approximateFilter NumericApproximateFilterSeries
dropNan NumericNanFilter
select1dArrayIndex SelectIndexFrom1dNumericArraySeries
aggregateUnderRanges AggregateUnderRangesSeries
rangeDuration RangeDurationSeries
groupWithinRangesV2 GroupWithinRangesSeriesV2
filterByExpression FilterByExpressionSeries
scalarUdf ScalarUdfSeries
enumToNumeric EnumToNumericSeries
contains ContainsSeries
refprop RefpropSeries
refpropV2 RefpropSeriesV2
extractFromStruct ExtractNumericFromStructSeries
tagByIntervals TagByIntervalsSeries
filterByTag NumericTagFilterSeries
selectTags NumericSelectTagsSeries
toStartOfInterval NumericToStartOfIntervalSeries
phaseUnwrap PhaseUnwrapSeries
aggregate AggregateNumericSeries deprecated: Deprecated: AggregateNumericSeries is deprecated. Use numericAggregation with aggregation.GroupByAggregationBuilder instead.
rollingOperation RollingOperationSeries deprecated: Deprecated: RollingOperationSeries is deprecated. Use numericAggregation with aggregation.RollingTimeAggregationBuilder instead.
bitOperation BitOperationSeries deprecated: Deprecated: BitOperationSeries is deprecated in favor of individual nodes for each operation.
channel ChannelSeries deprecated: Deprecated: Deprecated in favor of the SelectSeries node
offset OffsetSeries deprecated: Deprecated: OffsetSeries is deprecated in favor of add with a constant.
scale ScaleSeries deprecated: Deprecated: ScaleSeries is deprecated in favor of multiply with a constant.
arithmetic ArithmeticSeries deprecated: Deprecated: ArithmeticSeries is deprecated in favor of individual nodes for each operation.
unaryArithmetic UnaryArithmeticSeries deprecated: Deprecated: UnaryArithmeticSeries is deprecated in favor of individual nodes for each operation.
binaryArithmetic BinaryArithmeticSeries deprecated: Deprecated: BinaryArithmeticSeries is deprecated in favor of individual nodes for each operation.

NumericStaleRangesV2#

Produces ranges where a numeric input has no data for at least a duration.

input NumericSeries required
threshold compute.api.Duration required: Minimum gap without data that produces an output range.

NumericTagFilterSeries#

Applies a tag predicate to the numeric series produced by input.

input NumericSeries required
predicate TagPredicate required

NumericThresholdFilterSeries#

Outputs only the values of the numeric plot value that satisfy the threshold condition.

input NumericSeries required
threshold DoubleConstant required
operator ThresholdOperator required

NumericTimeRangeFilterSeries#

Filters the series to points within the specified time range.

input NumericSeries required
startTime TimestampConstant: Represents the start time (inclusive) of the time range.
endTime TimestampConstant: Represents the end time (inclusive) of the time range.

NumericTimeShiftSeries#

input NumericSeries required
duration DurationConstant required

NumericTimeShiftSeriesV2#

Shifts the timestamps in the input series by the resolved duration.

input NumericSeries required
duration compute.api.Duration required: Duration to shift the input series by.

NumericToStartOfIntervalSeries#

input NumericSeries required
window compute.api.Duration required

NumericUnionOperation#

DEPRECATED: apply aggregations as a separate step over the unioned output.

MIN: Combines multiple points by taking the minimum value
MAX: Combines multiple points by taking the maximum value
MEAN: Combines multiple points by taking the mean of the values
SUM: Combines multiple points by taking the sum of the values
COUNT: Combines multiple points by taking the count of the values
STANDARD_DEVIATION: Combines multiple points by taking the standard deviation of the values
ROOT_MEAN_SQUARE: Combines multiple points by taking the root mean square of the values
THROW: Throws a DuplicateTimestamp error if two series contain points with a duplicate timestamp.

NumericUnionSeries#

Combines multiple numeric series together and outputs a single series. By default, points from the inputs are concatenated (SQL {@code UNION ALL}) and duplicate timestamps across inputs are preserved. To aggregate values that share a timestamp, do a separate aggregation step next.

input array of NumericSeries: Input series to union
operation NumericUnionOperation deprecated: The strategy to merge points with duplicate timestamps. Deprecated: Apply aggregations as a separate step over the unioned output.

OffsetSeries#

For every timestamp specified in the input series, offset it by a constant factor.

input NumericSeries required
scalar DoubleConstant required: The constant to add to each point

OnChangeRanges#

Produces a list of ranges for each point that has a different value to the previous point. A range will have identical start and end times.

input Series required

OrSeries#

Combines two boolean series point-wise using logical OR, producing true where either input is true and false otherwise.

left BooleanSeries required
right BooleanSeries required

OutputRangeStart#

Set type to the name of one of the other fields, and set only that field.

firstPointMatchingCondition FirstPointMatchingCondition: The first point in the output range will be the first point where the condition evaluates to true.
afterPersistenceWindow AfterPersistenceWindow: The output range will contain points where the condition has been true for at least the min duration and min points.

PaddedRanges#

Expands ranges durations by adding temporal padding to the start, end, or both sides. Note that if the input ranges contain a RangeValue, it will be dropped.

input RangeSeries required
padding DurationConstant required
paddingConfiguration RangePaddingConfiguration: Configuration for how to apply padding to the ranges. Defaults to PAD_START_AND_END if not specified.

PaddedRangesV2#

Expands ranges using an authored Duration expression and a selected padding direction.

input RangeSeries required
duration compute.api.Duration required: How far to extend each range on every padded side.
paddingConfiguration RangePaddingConfiguration required

PeakRanges#

Produces a list of ranges for each point that is greater than its neighbors. Peaks at edges are discarded, and continuous, multivalue, flat peaks will return all values.

input NumericSeries required
returnsPeaks boolean deprecated: True if returning peaks, else troughs. Deprecated: No longer used, use returnType instead
returnType PeakType: Optional for backcompatibility.
minimumProminence DoubleConstant: The minimum topographic prominence for an extrema to be returned. Prominence is the minimum vertical distance needed to travel from an extrema to one of greater magnitude.

PeakType#

PEAK
TROUGH
BOTH

PercentageThreshold#

Threshold defined as the percentage of a given value.

value DoubleConstant required: Allowed spread, as a percentage of the window’s mean value.

Percentile#

The value at the specified percentile.

percentile DoubleConstant required: Percentile to compute, in range [0, 1]. E.g. 0.5 for median, 0.95 for p95.

PersistenceWindowConfiguration#

Configures how long a condition has to be true for to output a time range, and what to use as the start of the output range. For a point to be included in the output time range, both the minPoints and minDuration conditions must be satisfied.

minPoints IntegerConstant: The minimum number of points for which this condition be must satisfied to include the time range in the output. Must be non-negative. If not present, will default to 1.
minDuration DurationConstant: The minimum number of points for which this condition must be satisfied to include the time range in the output. Must be non-negative. If not present, will default to 1 nanosecond.
outputRangeStart OutputRangeStart required: Which point to use as the start of the output range. Defaults to firstPointMatchingCondition if not specified.

PhaseUnwrapSeries#

Removes discontinuities from a wrapping signal (e.g. phase or heading) by adding whole multiples of period whenever the step between consecutive samples exceeds half the period. Output length equals input length.

input NumericSeries required
period DoubleConstant required: The wrapping period of the signal (e.g. 2*pi for radians, 360 for degrees). A jump between consecutive samples greater than period/2 in magnitude is corrected by adding/subtracting a whole multiple of period.

PhysicalConstant#

Physical constants referenceable by name. The server resolves the symbol to its numeric value in SI units.

SPEED_OF_LIGHT: Speed of light in vacuum, 299792458 m/s (exact).
AVOGADRO: Avogadro constant, 6.02214076e23 mol^-1 (exact).
BOLTZMANN: Boltzmann constant, 1.380649e-23 J/K (exact).
PLANCK: Planck constant, 6.62607015e-34 J*s (exact).
ELEMENTARY_CHARGE: Elementary charge, 1.602176634e-19 C (exact).
GAS_CONSTANT: Molar gas constant, 8.31446261815324 J/(mol*K) (exact, Avogadro times Boltzmann).
STANDARD_GRAVITY: Standard acceleration of gravity, 9.80665 m/s^2 (exact by convention).
STANDARD_ATMOSPHERE: Standard atmosphere, 101325 Pa (exact by convention).
ABSOLUTE_ZERO_CELSIUS: Absolute zero expressed in degrees Celsius, -273.15 (exact).
GRAVITATIONAL_CONSTANT: Newtonian constant of gravitation, 6.67430e-11 m^3/(kg*s^2) (CODATA 2022, measured).
STEFAN_BOLTZMANN: Stefan-Boltzmann constant, 5.670374419e-8 W/(m^2*K^4) (exact derived).

PinnedModuleVersionReference#

version StringConstant required

PolynomialCurve#

degree IntegerConstant required: The highest allowable degree of the fit polynomial.
intercept DoubleConstant: The y-value at the point x (or t) = 0. If omitted, the y-intercept will also be fit to the data.

PolynomialCurveFit#

A polynomial fit of the enclosing target (y) against the chosen independent variable (x).

independentVariable CurveFitVariable required: The x axis the target is fit against — either relative sample time or another series.
degree IntegerConstant required: The highest allowable degree of the fit polynomial.
intercept DoubleConstant: The y-value at the point x (or t) = 0. If omitted, the y-intercept will also be fit to the data.

Power#

Raises base to the power of exponent pointwise.

base NumericSeries required: Base values.
exponent NumericSeries required: Exponent values.

PowerCurve#

An empty JSON object, {}.

ProductSeries#

For every timestamp specified in the input series, outputs a value that is the product for that timestamp across all input series. Only outputs timestamps where all input series have an entry for that timestamp, subject to interpolation.

inputs array of NumericSeries: Input series across which to take the pointwise product
interpolationConfiguration InterpolationConfiguration deprecated: Defaults to forward fill interpolation with a 1s interpolation radius Deprecated: Setting interpolation on this node is deprecated.

PropertiesFilter#

name string required
values array of string

Property#

name StringConstant required
value StringConstant required

PropertyComparisonOperator#

EQ
NEQ
GT
GTE
LT
LTE

RangeAggregationOperation#

Set type to the name of one of the other fields, and set only that field.

sum Summation
rootMeanSquare RootMeanSquare
average Average
min Minimum
max Maximum
standardDeviation StandardDeviation
count Count
all Empty

RangeDurationSeries#

Outputs a numeric series with one point per range: timestamp = range start, value = range duration.

input RangeSeries required
unboundedRangeBehavior UnboundedRangeBehavior required: How to handle ranges with a missing start or end.
timeUnit TimeUnit: The time unit of the duration. Defaults to seconds if not specified.

RangeIntervalSource#

Intervals come from a range series. Must resolve to literal ranges.

ranges RangeSeries required
tagBy array of RangeTagSource: Non-empty ordered list of tag sources. Each contributes a tag key-value pair per range interval.

RangeMap#

start DoubleConstant: Inclusive start value. If not specified, the start is the prior range’s end value, or negative infinity.
end DoubleConstant: Exclusive end value. If not specified, the end value is the next range’s start value, or positive infinity.
output StringConstant required: The value to map to if the input value is within the range.

RangePaddingConfiguration#

PAD_START
PAD_END
PAD_START_AND_END

RangesAnchor#

Uses the start timestamp of the range at the configured zero-based index from ranges evaluated over each interval, considering only ranges whose start lies in the anchor window [start, end), or [start, +infinity) when the end is absent. The window is the run bounds for a run anchor. A range already in progress when the window opens anchors at the window start. Series in ranges that select no explicit dataset resolve against the aligned input dataset, and the computed range groups must carry the aligned runs’ runRid grouping tags.

ranges RangeSeries required: The range series evaluated per interval to locate the anchor range.
index IntegerConstant: Zero-based range index after sorting. Defaults to zero and must be non-negative.
sortOrder RangeSortOrder: Ordering by range start timestamp before selecting the index. Defaults to ASC.

RangeSeries#

Set type to the name of one of the other fields, and set only that field.

approximateThreshold ApproximateThresholdRanges
booleanRanges BooleanRanges
thresholdRangesV2 ThresholdRangesV2
durationFilter DurationFilterRanges
durationFilterV2 DurationFilterRangesV2
enumFilter EnumFilterRanges
categoryFilterRangesV2 CategoryFilterRangesV2
categoricalOnChangeRangesV2 CategoricalOnChangeRangesV2
categoricalStaleRangesV2 CategoricalStaleRangesV2
categoricalEqualityRangesV2 CategoricalEqualityRangesV2
enumSeriesEqualityRangesNode EnumSeriesEqualityRanges
eventsSearch EventsSearchRanges
intersectRange IntersectRanges
literalRanges LiteralRanges
minMaxThreshold MinMaxThresholdRanges: Computes ranges where the input time series matches a filter defined by lower and upper bounds, and an operator.
not NotRanges
onChange OnChangeRanges
peak PeakRanges
extremaRangesV2 ExtremaRangesV2
rangeNumericAggregation RangesNumericAggregation
raw Reference
derived DerivedSeries
seriesCrossoverRangesNode SeriesCrossoverRanges
seriesEqualityRangesNode SeriesEqualityRanges
numericEqualityRangesV2 NumericEqualityRangesV2
stabilityDetection StabilityDetectionRanges
stabilityDetectionV2 StabilityDetectionRangesV2
staleRange StaleRanges
numericStaleRangesV2 NumericStaleRangesV2
threshold ThresholdingRanges: Computes ranges where the input time series matches a filter defined by a single threshold and an operator.
unionRange UnionRanges
paddedRanges PaddedRanges
paddedRangesV2 PaddedRangesV2

RangesNumericAggregation#

Aggregates the values of a numeric series at each range specified by the input ranges.

ranges RangeSeries required
input NumericSeries required
operation RangeAggregationOperation required

RangeSortOrder#

Sort order for selecting ranges. ASC selects from earliest to latest, DESC selects from latest to earliest.

ASC
DESC

RangeStart#

Selects which point of a satisfied condition begins the output range.

CONDITION_START
PERSISTENCE_START

RangeTagSource#

A dimension contributing a tag key-value pair per range interval.

Set type to the name of one of the other fields, and set only that field.

intervalIndex IntervalIndexTag
rangeStartTimestamp IntervalStartTimestampTag

Reference#

name string required: A reference to a value not defined in the current compute scope.

RefpropProperty#

Supported properties for REFPROP calculations.

TEMPERATURE
PRESSURE
MASS_DENSITY
MASS_SPECIFIC_ENTHALPY
MASS_SPECIFIC_INTERNAL_ENERGY
MASS_SPECIFIC_ENTROPY
VISCOSITY

RefpropSeries#

Computes the output property given input properties for the substance using REFPROP. Initial implementation only expects two input properties.

inputs map of string to NumericSeries: A map that maps a REFPROP property to its numeric series.
outputProperty RefpropProperty required: The desired output property. This should not be one of the input properties.
substance RefpropSubstance required: The substance for REFPROP calculations.
interpolationConfiguration InterpolationConfiguration deprecated: Deprecated: Setting interpolation on this node is deprecated.

RefpropSeriesV2#

Computes a REFPROP output property from the supplied substance and output property.

inputs map of string to NumericSeries: Map of REFPROP property to its numeric series.
substance RefpropSubstance required: The substance for REFPROP calculations.
outputProperty RefpropProperty required: The desired output property. This must not be one of the input properties.

RefpropSubstance#

Supported substances for REFPROP calculations

NITROGEN
OXYGEN
HELIUM
HYDROGEN
METHANE
PROPANE
BUTANE
WATER
XENON
AIR
CARBON_DIOXIDE
ARGON
CARBON_MONOXIDE
JET_A_4658
JET_A_3638

ResolvedDatasetInterval#

A catalog dataset’s recorded bounds transformed into the resolved dataset’s output time domain.

datasetRid string (RID) required: The caller-facing dataset this interval belongs to. For a derived dataset this is the derived dataset itself, so its inputs’ intervals all report the derived rid.
startTime Timestamp required
endTime Timestamp required

ResolvedRunInterval#

A run interval transformed into the dataset’s output time domain.

runRid string (RID) required
startTime Timestamp required
endTime Timestamp

ResourceSearchQuery#

Predicate tree for filtering.

Set type to the name of one of the other fields, and set only that field.

properties PropertiesFilter
numericProperty NumericPropertyPredicate
numericPropertyRange NumericPropertyRangePredicate: Matches resources using an inclusive numeric property range.
labels LabelsFilter
workspace StringConstant
and array of ResourceSearchQuery
or array of ResourceSearchQuery
not ResourceSearchQuery

RollingOperationSeries#

DEPRECATED. Use numericAggregation with aggregation.RollingTimeAggregationBuilder instead.

input NumericSeries required
window Window required
operator NumericAggregationOperator required

RollingPointsAggregationBuilder#

Rolling point-count aggregation: for each point in the input, aggregate the current point and the preceding N - 1 points within the same tag grouping.

input Series required
points IntegerConstant required

RollingTimeAggregationBuilder#

Rolling time-window aggregation: for each point in the input, aggregate the values within the preceding time window.

input Series required
window compute.api.Duration required

RootMeanSquare#

The root mean square of points inside the time window.

An empty JSON object, {}.

Run#

Run reference for Dataset.run. The rid field accepts either a literal run RID or a StringConstant reference resolved from Context.

rid StringConstant required: Resource identifier of a run

run.api.Duration#

seconds integer (int64) required
nanos integer (int64) required

RunChannel#

runRid StringConstant required
assetRid StringConstant: Used to disambiguate when multiple assets within this run contain data scopes with the same name. If not specified for a run with multiple assets, an error will be thrown.
dataScopeName StringConstant required: Used to disambiguate when multiple data scopes within this run contain channels with the same name.
channel StringConstant required
additionalTags map of string to StringConstant deprecated: Deprecated: Use additionalTagFilters
additionalTagFilters TagFilters: Tags to filter the channel by, in addition to tag filters defined for a given Run data scope. Throws on collisions with tag keys already defined for the given Run data scope. Only returns points that match both sets of tag filters. For log series, include arg filters here in addition to tag filters.
tagsToGroupBy array of string deprecated: Deprecated: Use groupByTags instead. Throws if both tagsToGroupBy and groupByTags are specified.
groupByTags array of StringConstant: Tags that the channel should be grouped by. If this is non-empty a grouped result will be returned with an entry for each grouping. Only one of tagsToGroupBy and groupByTags should be specified.

RunsSearchTarget#

Search runs. Each matched run expands to one grouping per data source attached to the run: asset-typed data sources contribute one grouping per data scope on the asset; dataset-typed data sources contribute one grouping per dataset. Every grouping is tagged by runRid and dataScope (the asset’s data scope name for asset-typed sources, or the run-local data source ref name for dataset-typed sources); asset-typed groupings additionally carry assetRid.

query ResourceSearchQuery required: Predicate tree used to filter matching runs.

RustUdfSource#

Rust source code defining the UDF entrypoint and any helper functions.

sourceCode string required: Rust source code to transpile into WASM. The operation consuming this source defines the entrypoint signature: scalar UDFs receive one scalar per input series, while aggregation UDFs receive grouped value vectors. If several functions appear at the top level, annotate the entrypoint with #[main].

Sampling#

Options for returning a sampled subset of raw series points.

Set type to the name of one of the other fields, and set only that field.

everyNthPerSeries EveryNthPerSeriesSampling
hashSubsample HashSubsampleSampling

SavedDataset#

A persisted source of data, named by its RID. Can be a catalog dataset, pipeline, connection, etc.

rid StringConstant required: A data source RID, given as a literal or as a variable resolved from Context. A pipeline’s logic only accepts catalog datasets/pipelines, since it is persisted without context.

ScalarUdfSeries#

Executes user-provided scalar UDF code over aligned inputs. The function must return one output for each aligned input row, with the return type matching the series type that contains this node.

inputs array of Series: Input series passed to the UDF in argument order.
source UdfSource required: Language-specific source definition for the UDF.

ScaleSeries#

For every timestamp specified in the input series, multiply it by a constant factor.

input NumericSeries required
scalar DoubleConstant required: The constant to multiply each point by
scalarUnit string: The units of the scalar to multiply by. If empty, the scalar is considered unit-less.

Scatter#

A scatter plot comprised of the values from one input series on the x-axis and values from another input series on the y-axis, for all points within a requested time range.

x NumericSeries required
y NumericSeries required

ScatterCurveFit#

Fits a curve to the scatter between two series.

scatter Scatter required: The x and y series to fit to.
options ScatterFitOptions required

ScatterFitOptions#

minX DoubleConstant: Inclusive lower bound on the x values to fit to. If omitted, does not set a bound (equivalent to setting this to the minimum x value among all points in the time range).
maxX DoubleConstant: Inclusive upper bound on the x values to fit to. If omitted, does not set a bound (equivalent to setting this to the maximum x value among all points in the time range).
minY DoubleConstant: Inclusive lower bound on the y values to fit to. If omitted, does not set a bound (equivalent to setting this to the minimum y value among all points in the time range).
maxY DoubleConstant: Inclusive upper bound on the y values to fit to. If omitted, does not set a bound (equivalent to setting this to the maximum y value among all points in the time range).

SearchDataset#

Resolves matching assets or runs from search, creating a combined dataset tagged by source rid and data scope.

target SearchTarget required: Whether to search assets or runs and with which query.
maxResults integer: Maximum number of assets or runs returned from search. Defaults to 10000 when omitted.

SearchEventOriginType#

WORKBOOK
TEMPLATE
API
DATA_REVIEW
PROCEDURE

SearchTarget#

Set type to the name of one of the other fields, and set only that field.

assets AssetsSearchTarget
runs RunsSearchTarget

SelectIndexFrom1dEnumArraySeries#

For each timestamp, selects a single enum value from the 1D enum array at the specified index. If the index is out of bounds for an array at a given timestamp, it is omitted.

input Enum1dArraySeries required
index IntegerConstant required

SelectIndexFrom1dNumericArraySeries#

For each timestamp, selects a single numeric value from the 1D numeric array at the specified index. If the index is out of bounds for an array at a given timestamp, it is omitted.

input Numeric1dArraySeries required
index IntegerConstant required

SelectNewestPointsSeries#

Select the most recent N points from the input series by timestamp.

input NumericSeries required: The input series to select the newest points from.
numPoints IntegerConstant required: The number of points to select.

SelectOldestPointsSeries#

Select the earliest N points from the input series by timestamp.

input NumericSeries required: The input series to select the oldest points from.
numPoints IntegerConstant required: The number of points to select.

SelectProperty#

Selects a typed property value from every asset or run branch resolved from dataset. Inside a WithSeriesDataset definition, dataset may be omitted to use that node’s wrapping input; it is required everywhere else. Asset branches read properties directly from their asset. Run branches read properties directly from their run, never from a backing asset or dataset. Direct saved-dataset branches are unsupported.

propertyName string required
dataset Dataset

SelectSeries#

Selects series from a dataset (might contain multiple tag groupings). When name is provided, selects that single channel. When name is omitted, selection starts from all channels in the dataset scope; callers narrow the selection with a filterByTag predicate on the reserved NOMINAL_CHANNEL tag key and preserve per-channel identity in the response with selectTags. Providing both name and a NOMINAL_CHANNEL filter is rejected as an invalid request. Raw and derived channels can both be selected through the reserved tag filter.

name StringConstant: The identifying series name to query
dataset Dataset: The dataset providing the data to query. May be omitted inside a WithSeriesDataset series definition, in which case it defaults to that node’s wrapping input; required everywhere else.
sampling Sampling: Raw-series sampling options. Supported for numeric and enum raw series.

Series#

Set type to the name of one of the other fields, and set only that field.

raw Reference deprecated: Deprecated: use typed value of series instead.
enum EnumSeries
numeric NumericSeries
log LogSeries
array ArraySeries
struct StructSeries
video Reference

SeriesCrossoverRanges#

Produces a list of zero-duration ranges at the first point where two series cross over one another

inputA NumericSeries required
inputB NumericSeries required: The series inputA is compared against.

SeriesEqualityRanges#

Produces a list of ranges for which provided series are all equal (or are not all equal).

input array of NumericSeries
equalityOperator EqualityOperator required
tolerance DoubleConstant
persistenceWindowConfiguration PersistenceWindowConfiguration
interpolationConfiguration InterpolationConfiguration deprecated: Defaults to forward fill interpolation with a 1s interpolation radius Deprecated: Setting interpolation on this node is deprecated.

SeriesVariable#

A series selected from a dataset, bound to a variable. The series type (numeric, enum, …) is decided lazily by the node consuming the variable, matching the behaviour of channel variables.

select SelectSeries required
groupByTags array of StringConstant: Tags that the series should be grouped by. If this is non-empty a grouped result will be returned with an entry for each grouping; otherwise all matching series are merged.

SetNegativeValuesToZero#

An empty JSON object, {}.

SetOperator#

AND
OR

SignalFilterConfiguration#

Set type to the name of one of the other fields, and set only that field.

lowPass LowPassConfiguration
highPass HighPassConfiguration
bandPass BandPassConfiguration
bandStop BandStopConfiguration

SignalFilterSeries#

Applies IIR-based signal filtering to input series. Includes low-pass, high-pass, band-pass, and band-stop filters. Currently supports variable-order bidirectional Butterworth filters, with fixed-size padding based on SciPy output.

input NumericSeries required
signalFilterConfiguration SignalFilterConfiguration required: Filter type and cutoff frequencies.
order IntegerConstant required: Order of filter. Must be a positive integer, and is effectively doubled for bidirectional filters.
samplingFrequency DoubleConstant: The sampling frequency of the input series. Used to calculate normalized frequency for cutoff frequencies.

Sin#

Computes the trigonometric sine of each value (input in radians).

x NumericSeries required: Input numeric series (radians).

Sqrt#

Computes the square root of each value.

x NumericSeries required: Input numeric series (non-negative values).

StabilityDetectionRanges#

Outputs a set of ranges where the input series is stable. For each point, the min and max are calculated over the specified lookback window, including the current point. A point is considered stable if its value does not deviate from the calculated min and the max by more than the threshold and the total number of points within the window is at least the specified amount. The threshold can be either fixed values or percentages of the value. The lookback window must be strictly positive. The minimum points threshold defaults to 2.

input NumericSeries required
windowConfiguration StabilityWindowConfiguration required
threshold Threshold required

StabilityDetectionRangesV2#

Produces ranges where a numeric input is stable within a modern duration window.

input NumericSeries required
window compute.api.Duration required: Lookback window over which the input’s spread is measured.
minPoints IntegerConstant: Minimum number of points in the window. Defaults to 2.
threshold Threshold required

StabilityWindowConfiguration#

minPoints IntegerConstant: The minimum number of points within the window to create a stable range. Must be non-negative. If not present, will default to 2.
duration DurationConstant required

StaleRanges#

Produces a list of ranges for which data does not exist for the specified duration or longer. Increases window size by the specified staleness threshold on both ends to capture edge cases of data not currently in view.

input Series required
threshold DurationConstant required
startTimestamp TimestampConstant: The start timestamp of the range. If not specified, staleness will automatically use view range start.
endTimestamp TimestampConstant deprecated: Deprecated: No longer used and will be removed

StandardDeviation#

The standard deviation of points inside the time window.

An empty JSON object, {}.

StreamingNotSupportedReason#

Why a particular data source within the dataset does not support streaming.

DATASET_DOES_NOT_ALLOW_STREAMING
CONNECTION_TYPE_NOT_NOMINAL
CONNECTION_TIMESTAMP_TYPE_NOT_ABSOLUTE

StreamingSupport#

Whether the dataset supports live streaming, plus unsupported data source diagnostics.

supportsStreaming boolean required: True iff unsupportedDataSources is empty.
unsupportedDataSources array of DataSourceStreamingSupport: Diagnostic entries for data sources reachable from the dataset that do not support live streaming. A data source may appear multiple times if multiple checks fail.

StringConstant#

A string constant that can be a literal value or a named variable reference.

Set type to the name of one of the other fields, and set only that field.

literal string: Create from a literal string value.
variable string: Create from a named reference.

StringPropertyDimension#

Injects the value of a string property, under a tag key equal to the property name by default. Only supported on asset and run branches: asset branches read the asset’s properties, and run branches, including run branches backed by an asset, read the run’s properties, matching SelectProperty. Values are injected as is. A branch without the property, or whose property holds a numeric value, gets the reserved value NOMINAL_ABSENT.

propertyName StringConstant required: Name of the property whose value to inject. Also the default tag key.

StringSetConstant#

Set type to the name of one of the other fields, and set only that field.

literal array of string
variable string

StringSetConstantV2#

A set of string constants that can be a literal set or a named variable reference.

Set type to the name of one of the other fields, and set only that field.

literal array of StringConstant: Create from a literal set of string constants.
variable string: Create from a named reference.

StructSelectTagsSeries#

Subsets the tag dimensions of the input struct series to the given tag keys. Preserves the input series’ cardinality: points that share the selected keys but differ on dropped keys remain distinct.

input StructSeries required
tagKeys array of StringConstant

StructSeries#

Set type to the name of one of the other fields, and set only that field.

channel ChannelSeries
raw Reference
derived DerivedSeries
combine CombineStructSeries
selectStruct SelectSeries
extractFromStruct ExtractStructFromStructSeries
toStartOfInterval StructToStartOfIntervalSeries
timeShift StructTimeShiftSeries
filterByTag StructTagFilterSeries
selectTags StructSelectTagsSeries

StructTagFilterSeries#

Applies a tag predicate to the struct series produced by input.

input StructSeries required
predicate TagPredicate required

StructTimeShiftSeries#

input StructSeries required
duration DurationConstant required

StructToStartOfIntervalSeries#

input StructSeries required
window compute.api.Duration required

Subtract#

Subtracts right from left pointwise.

left NumericSeries required: Left-hand operand (minuend).
right NumericSeries required: Right-hand operand (subtrahend).

Summation#

The sum of points inside the time window.

An empty JSON object, {}.

SumSeries#

For every timestamp specified in the input series, outputs a value that is the sum for that timestamp across all input series. Only outputs timestamps where all input series have an entry for that timestamp, subject to interpolation.

inputs array of NumericSeries: Input series across which to take the pointwise sum
interpolationConfiguration InterpolationConfiguration deprecated: Defaults to forward fill interpolation with a 1s interpolation radius Deprecated: Setting interpolation on this node is deprecated.

TagAnd#

Conjunction of two tag predicates (both must hold).

left TagPredicate required
right TagPredicate required

TagByIntervalsSeries#

Injects tags derived from interval boundaries onto a numeric series. Points within an interval get tagged; points outside all intervals are dropped. Intervals come from either events or ranges. If intervals with different tag map overlap, a data point falling in multiple intervals is duplicated into each matching output group. Overlapping intervals with equal tag maps are not allowed. Optional time shift subtracts a per-interval anchor from timestamps after matching.

input NumericSeries required
intervals IntervalSource required
timeShift TagByIntervalsTimeShift: When set, shift each matched point’s timestamp by the chosen anchor for that interval.

TagByIntervalsTimeShift#

How to shift timestamps after tagging (subtract anchor from each point in the interval slice).

Set type to the name of one of the other fields, and set only that field.

intervalStart IntervalStartTimeShift
intervalEnd IntervalEndTimeShift
eventTimeShift EventTimeShift

TagFilter#

A filter on a single tag key and set of values. For an IN operator, the tag key must match at least one of the values in the set. For a NOT_IN operator, it must not match any of the values in the set.

key StringConstant required
values array of StringConstant
operator TagFilterOperator required

TagFilterOperator#

IN
NOT_IN

TagFilters#

A set of tag filters to apply to a channel. Allows for combining filters on multiple tag keys, but throws if any one tag key is specified in more than one filter.

Set type to the name of one of the other fields, and set only that field.

single TagFilter
and array of TagFilters

TaggedDataset#

Injects one ephemeral tag (key and value) onto the underlying dataset.

input Dataset required: The underlying dataset to tag.
key StringConstant required: Tag key to inject onto each series in the dataset.
value StringConstant required: Tag value to assign to the injected key.

TagIn#

Constrains a tag key to be in the given set of values.

key StringConstant required
values StringSetConstantV2 required

TagNotIn#

Constrains a tag key to not be in the given set of values.

key StringConstant required
values StringSetConstantV2 required

TagPredicate#

Conjunctive tag predicate for dataset filtering. Compiles to resolved TagFilters for storage and resolution-time folding against known tag assignments (e.g. TaggedDataset, search branches).

Set type to the name of one of the other fields, and set only that field.

in TagIn
notIn TagNotIn
and TagAnd

Tan#

Computes the trigonometric tangent of each value (input in radians).

x NumericSeries required: Input numeric series (radians).

Threshold#

Set type to the name of one of the other fields, and set only that field.

absolute AbsoluteThreshold
percentage PercentageThreshold

ThresholdingRanges#

Produces a list of ranges for which the threshold condition is satisfied.

input NumericSeries required
threshold DoubleConstant required
operator ThresholdOperator required
persistenceWindowConfiguration PersistenceWindowConfiguration

ThresholdOperator#

GREATER_THAN
GREATER_THAN_OR_EQUAL_TO
LESS_THAN
LESS_THAN_OR_EQUAL_TO
EQUAL_TO
NOT_EQUAL_TO

ThresholdRangesComparison#

Selects the comparison applied to a numeric threshold.

Set type to the name of one of the other fields, and set only that field.

gt ThresholdRangesOrderedComparison
ge ThresholdRangesOrderedComparison
lt ThresholdRangesOrderedComparison
le ThresholdRangesOrderedComparison
eq ThresholdRangesEqualityComparison
ne ThresholdRangesEqualityComparison

ThresholdRangesEqualityComparison#

An equality comparison against a numeric threshold, within an optional tolerance.

threshold DoubleConstant required: The value each input point is compared against.
tolerance DoubleConstant: Maximum absolute difference from the threshold still counted as equal. Defaults to zero, i.e. exact equality.

ThresholdRangesOrderedComparison#

An ordering comparison against a single numeric threshold.

threshold DoubleConstant required: The value each input point is compared against.

ThresholdRangesV2#

Produces ranges where a numeric input satisfies a threshold comparison.

input NumericSeries required
minPoints IntegerConstant: Minimum number of matching points. Defaults to 1.
minDuration compute.api.Duration: Minimum matching duration. Defaults to one nanosecond.
rangeStart RangeStart: Selects whether the output begins at the first match or after persistence is satisfied.
comparison ThresholdRangesComparison required

TimeDifferenceSeries#

Outputs a new series where each value is the difference between the time of the current and previous points.

input Series required
timeUnit TimeUnit: The time unit used to define the output values. Defaults to seconds if not specified.

TimeSeriesCurveFit#

Fits a curve to a series vs its timestamps.

series NumericSeries required: The series to fit. Timestamps will be used as x values and data as y values. The leftmost (earliest) timestamp will be used as the value of 0, and all other timestamps will be relative to that.
options TimeSeriesFitOptions required

TimeSeriesFitOptions#

timeUnit TimeUnit: Time unit used for the timestamps to fit against. Defaults to seconds if not specified.

TimeShiftedDataset#

Transforms a dataset by adding a time offset to all its data.

input Dataset required: The underlying dataset to time-shift.
offset compute.api.Duration required: The time shift to apply. Positive values shift data forward in time, negative values shift backward.

Timestamp#

Deprecated for new APIs. Use google.protobuf.Timestamp for absolute instants in proto APIs.

This legacy nanosecond precision timestamp type is represented by an epoch time in seconds and a nanosecond offset. The nanosecond offset is from the start of the epoch second, so must be less than 1 billion.

seconds integer (int64) required
nanos integer (int64) required

TimestampConstant#

A timestamp constant that can be a literal value or a named variable reference.

Set type to the name of one of the other fields, and set only that field.

literal Timestamp: Create from a literal timestamp value.
variable string: Create from a named reference.

TimeUnit#

DAYS
HOURS
MINUTES
SECONDS
MILLISECONDS
MICROSECONDS
NANOSECONDS

UdfSource#

Source provider for a user-defined function.

Set type to the name of one of the other fields, and set only that field.

rust RustUdfSource

UnaryArithmeticOperation#

COS: Calculates the trigonometric cosine (input in radians)
SIN: Calculates the trigonometric sine (input in radians)
TAN: Calculates the trigonometric tangent (input in radians)
ABS: Calculates the absolute value
ASIN: Calculates the arcsine, returning radians
ACOS: Calculates the arccosine, returning radians
LOG: Calculates the base 10 logarithm
LN: Calculates the natural logarithm (base e)
SQRT: Calculates the square root

UnaryArithmeticSeries#

Applies a point-wise transformation to a series. The transformation function is applied to every individual data point.

input NumericSeries required
operation UnaryArithmeticOperation required

UnboundedBehavior#

Dictates how empty range bounds should be handled by the compute node. Defaults to INFINITY.

INFINITY
WINDOW_BOUND

UnboundedRangeBehavior#

How to handle ranges with a missing start or end.

Set type to the name of one of the other fields, and set only that field.

clampToWindow Empty: Clamp a missing range start to the compute request window start and a missing range end to the compute request window end.
drop Empty: Drop the range if it has a missing start or end.

Union#

Uses the union of all input timestamps as the alignment grid.

An empty JSON object, {}.

UnionRanges#

inputs array of RangeSeries: The ranges to union.

UnitConversionSeries#

Convert the given series to a different unit.

input NumericSeries required
outputUnit string required

UnitOverrideSeries#

Override the unit of the given series without changing its values. Unlike unit conversion, no compatibility with the input’s current unit is required.

input NumericSeries required
unit string: The unit to report for the input series. If absent, the input’s unit is cleared.

ValueDifferenceSeries#

Calculates the first discrete difference of the input series. For each point, computes the difference between the current value and the previous value (current - previous). The first point in the input series is omitted from the output since it has no previous point to compare against.

This is equivalent to pandas DataFrame.diff() with period=1. Useful for analyzing changes between consecutive data points in time series data, such as detecting value increases or decreases.

Example: For input values [1.0, 1.0, 2.0, 2.5, 1.8], the output would be [0.0, 1.0, 0.5, -0.7] at the corresponding timestamps (the first timestamp is omitted).

input NumericSeries required
negativeValuesConfiguration NegativeValueConfiguration: Defines the strategy for handling negative output values. Defaults to allowNegativeValues if not specified.

ValueMapSeries#

Maps a continuous numeric series to a discrete enum series using the specified value ranges.

input NumericSeries required: The input series to map to an enumerated series
mapping array of RangeMap: The output of the first capturing range will be used. Ranges are start inclusive, end exclusive, must not overlap, and increasing from lowest to highest. Ranges can be open ended to the edge of the next or prior range. The first range can be open ended to negative infinity, and the last range can be open ended to positive infinity.
default StringConstant: The default value if not captured by any range. If not specified, points will be filtered.

VariableValue#

Set type to the name of one of the other fields, and set only that field.

double number
computeNode ComputeNodeWithContext
duration run.api.Duration
integer integer
channel ChannelSeries deprecated: Deprecated: use series instead.
derived DerivedSeries
series SeriesVariable
string string
stringSet array of string
timestamp Timestamp

Window#

Set type to the name of one of the other fields, and set only that field.

duration DurationConstant

WithSeriesDataset#

Adds one or more derived series to the base dataset. Each entry’s definition must reference only the wrapping input. Series names must be unique within the request; a derived name replaces a same-named series from input.

input Dataset required: The base dataset to which the new series will be added.
series array of NamedSeries: The named derived series to add.

ZscoreSeries#

Computes the z-score for each series within a group-by family. For each group at each timestamp, the output is (value - mean) / stddev, where mean and stddev are computed across all groups in the family at that timestamp, using the interpolation configuration to align values across groups. When stddev is zero at a timestamp (e.g., all groups have the same value), that data point is excluded from the output. If groupByTags is empty, all groups in the input series will be considered as a single family. This node only produces meaningful results when the input has a group by.

input NumericSeries required
groupByTags array of StringConstant: Tags to group by for the normalization. If left empty, all groups in the input will be considered as a single family. Otherwise, inputs will be normalized separately across the groups specified by the tags.
interpolationConfiguration InterpolationConfiguration deprecated: Configuration for aligning values across groups at each timestamp. Defaults to forward fill interpolation with a 1s interpolation radius. Deprecated: Setting interpolation on this node is deprecated.

Page design based on Scalar, MIT License.

Dataset metadata service#

Endpoints#

Get dataset metadata#

Batch get dataset metadata#

Types#

Abs#

AbsoluteThreshold#

AbsoluteTimestampSeries#

Acos#

Add#

AfterPersistenceWindow#

AggregateEnumSeries#

AggregateNumericSeries#

AggregateUnderRangesSeries#

AggregationBuilder#

Alignment#

AllowNegativeValues#

AnchorAlignedDataset#

AnchorReference#

AndSeries#

ApproximateThresholdOperator#

ApproximateThresholdRanges#

ArithmeticSeries#

ArraySeries#

Asin#

Asset#

AssetChannel#

AssetsSearchTarget#

Atan2#

Average#

BandPassConfiguration#

BandStopConfiguration#

BatchDataSourceStreamingSupport#

BatchStreamingSupport#

BinaryArithmeticOperation#

BinaryArithmeticSeries#

BitAnd#

BitAndFunction#

BitOperationFunction#

BitOperationSeries#

BitOr#

BitOrFunction#

BitShiftLeft#

BitShiftLeftFunction#

BitShiftRight#

BitShiftRightFunction#

BitTest#

BitTestFunction#

BitXor#

BitXorFunction#

BooleanRanges#

BooleanSeries#

BuiltinConstant#

BuiltInCurveFit#

CategoricalEqualityRangesV2#

CategoricalOnChangeRangesV2#

CategoricalStaleRangesV2#

CategoryFilterRangesV2#

ChannelSeries#

CombinedDataset#

CombineStructSeries#

compute.api.Duration#

ComputeEventQuery#

ComputeNode#

ComputeNodeWithContext#

ConstantNumericSeries#

ContainsSeries#

Context#

Cos#

Count#

CumulativeSumSeries#

CurveFit#

CurveFitBoundsConfiguration#

CurveFitDetails#

CurveFitOptions#

CurveFitPlotType#

CurveFitRange#

CurveFitSeriesVariable#

CurveFitTarget#

CurveFitTimeVariable#