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// Unless explicitly stated otherwise all files in this repository are licensed under the Apache-2.0 License.
// This product includes software developed at Datadog (https://www.datadoghq.com/).
// Copyright 2019-Present Datadog, Inc.
use serde::de::{Error, MapAccess, Visitor};
use serde::{Deserialize, Deserializer, Serialize};
use serde_with::skip_serializing_none;
use std::fmt::{self, Formatter};
/// A group by rule
#[non_exhaustive]
#[skip_serializing_none]
#[derive(Clone, Debug, PartialEq, Serialize)]
pub struct LogsGroupBy {
/// The name of the facet to use (required)
#[serde(rename = "facet")]
pub facet: String,
/// Used to perform a histogram computation (only for measure facets).
/// Note: at most 100 buckets are allowed, the number of buckets is (max - min)/interval.
#[serde(rename = "histogram")]
pub histogram: Option<crate::datadogV2::model::LogsGroupByHistogram>,
/// The maximum buckets to return for this group by. Note: at most 10000 buckets are allowed.
/// If grouping by multiple facets, the product of limits must not exceed 10000.
#[serde(rename = "limit")]
pub limit: Option<i64>,
/// The value to use for logs that don't have the facet used to group by
#[serde(rename = "missing")]
pub missing: Option<crate::datadogV2::model::LogsGroupByMissing>,
/// A sort rule
#[serde(rename = "sort")]
pub sort: Option<crate::datadogV2::model::LogsAggregateSort>,
/// A resulting object to put the given computes in over all the matching records.
#[serde(rename = "total")]
pub total: Option<crate::datadogV2::model::LogsGroupByTotal>,
#[serde(flatten)]
pub additional_properties: std::collections::BTreeMap<String, serde_json::Value>,
#[serde(skip)]
#[serde(default)]
pub(crate) _unparsed: bool,
}
impl LogsGroupBy {
pub fn new(facet: String) -> LogsGroupBy {
LogsGroupBy {
facet,
histogram: None,
limit: None,
missing: None,
sort: None,
total: None,
additional_properties: std::collections::BTreeMap::new(),
_unparsed: false,
}
}
pub fn histogram(mut self, value: crate::datadogV2::model::LogsGroupByHistogram) -> Self {
self.histogram = Some(value);
self
}
pub fn limit(mut self, value: i64) -> Self {
self.limit = Some(value);
self
}
pub fn missing(mut self, value: crate::datadogV2::model::LogsGroupByMissing) -> Self {
self.missing = Some(value);
self
}
pub fn sort(mut self, value: crate::datadogV2::model::LogsAggregateSort) -> Self {
self.sort = Some(value);
self
}
pub fn total(mut self, value: crate::datadogV2::model::LogsGroupByTotal) -> Self {
self.total = Some(value);
self
}
pub fn additional_properties(
mut self,
value: std::collections::BTreeMap<String, serde_json::Value>,
) -> Self {
self.additional_properties = value;
self
}
}
impl<'de> Deserialize<'de> for LogsGroupBy {
fn deserialize<D>(deserializer: D) -> Result<Self, D::Error>
where
D: Deserializer<'de>,
{
struct LogsGroupByVisitor;
impl<'a> Visitor<'a> for LogsGroupByVisitor {
type Value = LogsGroupBy;
fn expecting(&self, f: &mut Formatter<'_>) -> fmt::Result {
f.write_str("a mapping")
}
fn visit_map<M>(self, mut map: M) -> Result<Self::Value, M::Error>
where
M: MapAccess<'a>,
{
let mut facet: Option<String> = None;
let mut histogram: Option<crate::datadogV2::model::LogsGroupByHistogram> = None;
let mut limit: Option<i64> = None;
let mut missing: Option<crate::datadogV2::model::LogsGroupByMissing> = None;
let mut sort: Option<crate::datadogV2::model::LogsAggregateSort> = None;
let mut total: Option<crate::datadogV2::model::LogsGroupByTotal> = None;
let mut additional_properties: std::collections::BTreeMap<
String,
serde_json::Value,
> = std::collections::BTreeMap::new();
let mut _unparsed = false;
while let Some((k, v)) = map.next_entry::<String, serde_json::Value>()? {
match k.as_str() {
"facet" => {
facet = Some(serde_json::from_value(v).map_err(M::Error::custom)?);
}
"histogram" => {
if v.is_null() {
continue;
}
histogram = Some(serde_json::from_value(v).map_err(M::Error::custom)?);
}
"limit" => {
if v.is_null() {
continue;
}
limit = Some(serde_json::from_value(v).map_err(M::Error::custom)?);
}
"missing" => {
if v.is_null() {
continue;
}
missing = Some(serde_json::from_value(v).map_err(M::Error::custom)?);
if let Some(ref _missing) = missing {
match _missing {
crate::datadogV2::model::LogsGroupByMissing::UnparsedObject(
_missing,
) => {
_unparsed = true;
}
_ => {}
}
}
}
"sort" => {
if v.is_null() {
continue;
}
sort = Some(serde_json::from_value(v).map_err(M::Error::custom)?);
}
"total" => {
if v.is_null() {
continue;
}
total = Some(serde_json::from_value(v).map_err(M::Error::custom)?);
if let Some(ref _total) = total {
match _total {
crate::datadogV2::model::LogsGroupByTotal::UnparsedObject(
_total,
) => {
_unparsed = true;
}
_ => {}
}
}
}
&_ => {
if let Ok(value) = serde_json::from_value(v.clone()) {
additional_properties.insert(k, value);
}
}
}
}
let facet = facet.ok_or_else(|| M::Error::missing_field("facet"))?;
let content = LogsGroupBy {
facet,
histogram,
limit,
missing,
sort,
total,
additional_properties,
_unparsed,
};
Ok(content)
}
}
deserializer.deserialize_any(LogsGroupByVisitor)
}
}