Struct google_api_proto::google::cloud::timeseriesinsights::v1::QueryDataSetRequest
source · pub struct QueryDataSetRequest {
pub name: String,
pub detection_time: Option<Timestamp>,
pub num_returned_slices: Option<i32>,
pub slicing_params: Option<SlicingParams>,
pub timeseries_params: Option<TimeseriesParams>,
pub forecast_params: Option<ForecastParams>,
pub return_timeseries: bool,
}
Expand description
Request for performing a query against a loaded DataSet.
Fields§
§name: String
Required. Loaded DataSet to be queried in the format of “projects/{project}/datasets/{dataset}”
detection_time: Option<Timestamp>
Required. This is the point in time that we want to probe for anomalies.
The corresponding [TimeseriesPoint][google.cloud.timeseriesinsights.v1.TimeseriesPoint] is referred to as the detection point.
NOTE: As with any other time series point, the value is given by aggregating all events in the slice that are in the [detectionTime, detectionTime + granularity) time interval, where the granularity is specified in the [timeseriesParams.granularity][google.cloud.timeseriesinsights.v1.TimeseriesParams.granularity] field.
num_returned_slices: Option<i32>
How many slices are returned in [QueryDataSetResponse.slices][google.cloud.timeseriesinsights.v1.QueryDataSetResponse.slices].
The returned slices are tentatively the ones with the highest [anomaly scores][google.cloud.timeseriesinsights.v1.EvaluatedSlice.anomaly_score] in the dataset that match the query, but it is not guaranteed.
Reducing this number will improve query performance, both in terms of latency and resource usage.
Defaults to 50.
slicing_params: Option<SlicingParams>
Parameters controlling how we will split the dataset into the slices that we will analyze.
timeseries_params: Option<TimeseriesParams>
Parameters controlling how we will build the time series used to predict the [detectionTime][google.cloud.timeseriesinsights.v1.QueryDataSetRequest.detection_time] value for each slice.
forecast_params: Option<ForecastParams>
Parameters that control the time series forecasting models, such as the sensitivity of the anomaly detection.
return_timeseries: bool
If specified, we will return the actual and forecasted time for all returned slices.
The time series are returned in the [EvaluatedSlice.history][google.cloud.timeseriesinsights.v1.EvaluatedSlice.history] and [EvaluatedSlice.forecast][google.cloud.timeseriesinsights.v1.EvaluatedSlice.forecast] fields.
Implementations§
source§impl QueryDataSetRequest
impl QueryDataSetRequest
sourcepub fn num_returned_slices(&self) -> i32
pub fn num_returned_slices(&self) -> i32
Returns the value of num_returned_slices
, or the default value if num_returned_slices
is unset.
Trait Implementations§
source§impl Clone for QueryDataSetRequest
impl Clone for QueryDataSetRequest
source§fn clone(&self) -> QueryDataSetRequest
fn clone(&self) -> QueryDataSetRequest
1.0.0 · source§fn clone_from(&mut self, source: &Self)
fn clone_from(&mut self, source: &Self)
source
. Read moresource§impl Debug for QueryDataSetRequest
impl Debug for QueryDataSetRequest
source§impl Default for QueryDataSetRequest
impl Default for QueryDataSetRequest
source§impl Message for QueryDataSetRequest
impl Message for QueryDataSetRequest
source§fn encoded_len(&self) -> usize
fn encoded_len(&self) -> usize
source§fn encode(&self, buf: &mut impl BufMut) -> Result<(), EncodeError>where
Self: Sized,
fn encode(&self, buf: &mut impl BufMut) -> Result<(), EncodeError>where
Self: Sized,
source§fn encode_to_vec(&self) -> Vec<u8>where
Self: Sized,
fn encode_to_vec(&self) -> Vec<u8>where
Self: Sized,
source§fn encode_length_delimited(
&self,
buf: &mut impl BufMut,
) -> Result<(), EncodeError>where
Self: Sized,
fn encode_length_delimited(
&self,
buf: &mut impl BufMut,
) -> Result<(), EncodeError>where
Self: Sized,
source§fn encode_length_delimited_to_vec(&self) -> Vec<u8>where
Self: Sized,
fn encode_length_delimited_to_vec(&self) -> Vec<u8>where
Self: Sized,
source§fn decode(buf: impl Buf) -> Result<Self, DecodeError>where
Self: Default,
fn decode(buf: impl Buf) -> Result<Self, DecodeError>where
Self: Default,
source§fn decode_length_delimited(buf: impl Buf) -> Result<Self, DecodeError>where
Self: Default,
fn decode_length_delimited(buf: impl Buf) -> Result<Self, DecodeError>where
Self: Default,
source§fn merge(&mut self, buf: impl Buf) -> Result<(), DecodeError>where
Self: Sized,
fn merge(&mut self, buf: impl Buf) -> Result<(), DecodeError>where
Self: Sized,
self
. Read moresource§fn merge_length_delimited(&mut self, buf: impl Buf) -> Result<(), DecodeError>where
Self: Sized,
fn merge_length_delimited(&mut self, buf: impl Buf) -> Result<(), DecodeError>where
Self: Sized,
self
.source§impl PartialEq for QueryDataSetRequest
impl PartialEq for QueryDataSetRequest
source§fn eq(&self, other: &QueryDataSetRequest) -> bool
fn eq(&self, other: &QueryDataSetRequest) -> bool
self
and other
values to be equal, and is used
by ==
.impl StructuralPartialEq for QueryDataSetRequest
Auto Trait Implementations§
impl Freeze for QueryDataSetRequest
impl RefUnwindSafe for QueryDataSetRequest
impl Send for QueryDataSetRequest
impl Sync for QueryDataSetRequest
impl Unpin for QueryDataSetRequest
impl UnwindSafe for QueryDataSetRequest
Blanket Implementations§
source§impl<T> BorrowMut<T> for Twhere
T: ?Sized,
impl<T> BorrowMut<T> for Twhere
T: ?Sized,
source§fn borrow_mut(&mut self) -> &mut T
fn borrow_mut(&mut self) -> &mut T
§impl<T> Instrument for T
impl<T> Instrument for T
§fn instrument(self, span: Span) -> Instrumented<Self>
fn instrument(self, span: Span) -> Instrumented<Self>
§fn in_current_span(self) -> Instrumented<Self>
fn in_current_span(self) -> Instrumented<Self>
source§impl<T> IntoRequest<T> for T
impl<T> IntoRequest<T> for T
source§fn into_request(self) -> Request<T>
fn into_request(self) -> Request<T>
T
in a tonic::Request