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
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
// This Source Code Form is subject to the terms of the Mozilla Public
// License, v. 2.0. If a copy of the MPL was not distributed with this
// file, You can obtain one at https://mozilla.org/MPL/2.0/.
use std::collections::HashMap;
use serde::Serialize;
use crate::error_recording::{record_error, ErrorType};
use crate::histogram::{Bucketing, Histogram, HistogramType};
use crate::metrics::Metric;
use crate::metrics::MetricType;
use crate::storage::StorageManager;
use crate::CommonMetricData;
use crate::Glean;
/// A custom distribution metric.
///
/// Memory distributions are used to accumulate and store memory sizes.
#[derive(Debug)]
pub struct CustomDistributionMetric {
meta: CommonMetricData,
range_min: u64,
range_max: u64,
bucket_count: u64,
histogram_type: HistogramType,
}
/// A serializable representation of a snapshotted histogram.
#[derive(Debug, Serialize)]
pub struct Snapshot {
values: HashMap<u64, u64>,
sum: u64,
}
/// Create a snapshot of the histogram.
///
/// The snapshot can be serialized into the payload format.
pub(crate) fn snapshot<B: Bucketing>(hist: &Histogram<B>) -> Snapshot {
Snapshot {
values: hist.snapshot_values(),
sum: hist.sum(),
}
}
impl MetricType for CustomDistributionMetric {
fn meta(&self) -> &CommonMetricData {
&self.meta
}
fn meta_mut(&mut self) -> &mut CommonMetricData {
&mut self.meta
}
}
impl CustomDistributionMetric {
/// Create a new memory distribution metric.
pub fn new(
meta: CommonMetricData,
range_min: u64,
range_max: u64,
bucket_count: u64,
histogram_type: HistogramType,
) -> Self {
Self {
meta,
range_min,
range_max,
bucket_count,
histogram_type,
}
}
/// Accumulates the provided signed samples in the metric.
///
/// This is required so that the platform-specific code can provide us with
/// 64 bit signed integers if no `u64` comparable type is available. This
/// will take care of filtering and reporting errors for any provided negative
/// sample.
///
/// ## Arguments
///
/// - `samples` - The vector holding the samples to be recorded by the metric.
///
/// ## Notes
///
/// Discards any negative value in `samples` and report an `ErrorType::InvalidValue`
/// for each of them.
pub fn accumulate_samples_signed(&self, glean: &Glean, samples: Vec<i64>) {
let mut num_negative_samples = 0;
// Generic accumulation function to handle the different histogram types and count negative
// samples.
fn accumulate<B: Bucketing, F>(
samples: &[i64],
mut hist: Histogram<B>,
metric: F,
) -> (i32, Metric)
where
F: Fn(Histogram<B>) -> Metric,
{
let mut num_negative_samples = 0;
for &sample in samples.iter() {
if sample < 0 {
num_negative_samples += 1;
} else {
let sample = sample as u64;
hist.accumulate(sample);
}
}
(num_negative_samples, metric(hist))
}
glean.storage().record_with(glean, &self.meta, |old_value| {
let (num_negative, hist) = match self.histogram_type {
HistogramType::Linear => {
let hist = if let Some(Metric::CustomDistributionLinear(hist)) = old_value {
hist
} else {
Histogram::linear(
self.range_min,
self.range_max,
self.bucket_count as usize,
)
};
accumulate(&samples, hist, Metric::CustomDistributionLinear)
}
HistogramType::Exponential => {
let hist = if let Some(Metric::CustomDistributionExponential(hist)) = old_value
{
hist
} else {
Histogram::exponential(
self.range_min,
self.range_max,
self.bucket_count as usize,
)
};
accumulate(&samples, hist, Metric::CustomDistributionExponential)
}
};
num_negative_samples = num_negative;
hist
});
if num_negative_samples > 0 {
let msg = format!("Accumulated {} negative samples", num_negative_samples);
record_error(
glean,
&self.meta,
ErrorType::InvalidValue,
msg,
num_negative_samples,
);
}
}
/// **Test-only API (exported for FFI purposes).**
///
/// Get the currently stored histogram.
///
/// This doesn't clear the stored value.
pub fn test_get_value(
&self,
glean: &Glean,
storage_name: &str,
) -> Option<Histogram<Box<dyn Bucketing>>> {
match StorageManager.snapshot_metric(
glean.storage(),
storage_name,
&self.meta.identifier(glean),
) {
// Boxing the value, in order to return either of the possible buckets
Some(Metric::CustomDistributionExponential(hist)) => Some(hist.boxed()),
Some(Metric::CustomDistributionLinear(hist)) => Some(hist.boxed()),
_ => None,
}
}
/// **Test-only API (exported for FFI purposes).**
///
/// Get the currently stored histogram as a JSON String of the serialized value.
///
/// This doesn't clear the stored value.
pub fn test_get_value_as_json_string(
&self,
glean: &Glean,
storage_name: &str,
) -> Option<String> {
self.test_get_value(glean, storage_name)
.map(|hist| serde_json::to_string(&snapshot(&hist)).unwrap())
}
}