1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
// 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 single column of a DDSQL tabular query result.
#[non_exhaustive]
#[skip_serializing_none]
#[derive(Clone, Debug, PartialEq, Serialize)]
pub struct DdsqlTabularQueryColumn {
/// Name of the column as projected by the SQL statement.
#[serde(rename = "name")]
pub name: String,
/// DDSQL data type of the column's values, for example `VARCHAR`, `BIGINT`,
/// `DECIMAL`, `BOOLEAN`, `TIMESTAMP`, `JSON`, or an array variant such as
/// `VARCHAR[]`. See the
/// [DDSQL data-types reference](<https://docs.datadoghq.com/ddsql_reference/#data-types>)
/// for the full, up-to-date list.
#[serde(rename = "type")]
pub type_: String,
/// Column values in row order, one entry per result row. The element type
/// follows the column's `type`. The following serialization rules should be
/// taken into account:
///
/// - `BIGINT` values are encoded as JSON numbers in the signed 64-bit integer range.
/// - `DECIMAL` values are encoded as JSON numbers with 64-bit double precision.
/// - `TIMESTAMP` and `DATE` values are encoded as Unix-millisecond integers; a
/// `DATE` resolves to midnight UTC.
/// - `JSON` values are returned as a JSON-encoded string.
///
/// `null` is allowed for any column type where a value is missing.
#[serde(rename = "values")]
pub values: Vec<serde_json::Value>,
#[serde(flatten)]
pub additional_properties: std::collections::BTreeMap<String, serde_json::Value>,
#[serde(skip)]
#[serde(default)]
pub(crate) _unparsed: bool,
}
impl DdsqlTabularQueryColumn {
pub fn new(
name: String,
type_: String,
values: Vec<serde_json::Value>,
) -> DdsqlTabularQueryColumn {
DdsqlTabularQueryColumn {
name,
type_,
values,
additional_properties: std::collections::BTreeMap::new(),
_unparsed: false,
}
}
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 DdsqlTabularQueryColumn {
fn deserialize<D>(deserializer: D) -> Result<Self, D::Error>
where
D: Deserializer<'de>,
{
struct DdsqlTabularQueryColumnVisitor;
impl<'a> Visitor<'a> for DdsqlTabularQueryColumnVisitor {
type Value = DdsqlTabularQueryColumn;
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 name: Option<String> = None;
let mut type_: Option<String> = None;
let mut values: Option<Vec<serde_json::Value>> = 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() {
"name" => {
name = Some(serde_json::from_value(v).map_err(M::Error::custom)?);
}
"type" => {
type_ = Some(serde_json::from_value(v).map_err(M::Error::custom)?);
}
"values" => {
values = Some(serde_json::from_value(v).map_err(M::Error::custom)?);
}
&_ => {
if let Ok(value) = serde_json::from_value(v.clone()) {
additional_properties.insert(k, value);
}
}
}
}
let name = name.ok_or_else(|| M::Error::missing_field("name"))?;
let type_ = type_.ok_or_else(|| M::Error::missing_field("type_"))?;
let values = values.ok_or_else(|| M::Error::missing_field("values"))?;
let content = DdsqlTabularQueryColumn {
name,
type_,
values,
additional_properties,
_unparsed,
};
Ok(content)
}
}
deserializer.deserialize_any(DdsqlTabularQueryColumnVisitor)
}
}