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
|
// SPDX-License-Identifier: GPL-3.0-or-later
#include "value.h"
inline NETDATA_DOUBLE rrdr2value(RRDR *r, long i, RRDR_OPTIONS options, int *all_values_are_null, NETDATA_DOUBLE *anomaly_rate) {
QUERY_TARGET *qt = r->internal.qt;
long c;
const long used = qt->query.used;
NETDATA_DOUBLE *cn = &r->v[ i * r->d ];
RRDR_VALUE_FLAGS *co = &r->o[ i * r->d ];
NETDATA_DOUBLE *ar = &r->ar[ i * r->d ];
NETDATA_DOUBLE sum = 0, min = 0, max = 0, v;
int all_null = 1, init = 1;
NETDATA_DOUBLE total = 1;
NETDATA_DOUBLE total_anomaly_rate = 0;
int set_min_max = 0;
if(unlikely(options & RRDR_OPTION_PERCENTAGE)) {
total = 0;
for (c = 0; c < used; c++) {
if(unlikely(!(r->od[c] & RRDR_DIMENSION_QUERIED))) continue;
NETDATA_DOUBLE n = cn[c];
if(likely((options & RRDR_OPTION_ABSOLUTE) && n < 0))
n = -n;
total += n;
}
// prevent a division by zero
if(total == 0) total = 1;
set_min_max = 1;
}
// for each dimension
for (c = 0; c < used; c++) {
if(unlikely(r->od[c] & RRDR_DIMENSION_HIDDEN)) continue;
if(unlikely(!(r->od[c] & RRDR_DIMENSION_QUERIED))) continue;
if(unlikely((options & RRDR_OPTION_NONZERO) && !(r->od[c] & RRDR_DIMENSION_NONZERO))) continue;
NETDATA_DOUBLE n = cn[c];
if(likely((options & RRDR_OPTION_ABSOLUTE) && n < 0))
n = -n;
if(unlikely(options & RRDR_OPTION_PERCENTAGE)) {
n = n * 100 / total;
if(unlikely(set_min_max)) {
r->min = r->max = n;
set_min_max = 0;
}
if(n < r->min) r->min = n;
if(n > r->max) r->max = n;
}
if(unlikely(init)) {
if(n > 0) {
min = 0;
max = n;
}
else {
min = n;
max = 0;
}
init = 0;
}
if(likely(!(co[c] & RRDR_VALUE_EMPTY))) {
all_null = 0;
sum += n;
}
if(n < min) min = n;
if(n > max) max = n;
total_anomaly_rate += ar[c];
}
if(anomaly_rate) {
if(!r->d) *anomaly_rate = 0;
else *anomaly_rate = total_anomaly_rate / (NETDATA_DOUBLE)r->d;
}
if(unlikely(all_null)) {
if(likely(all_values_are_null))
*all_values_are_null = 1;
return 0;
}
else {
if(likely(all_values_are_null))
*all_values_are_null = 0;
}
if(options & RRDR_OPTION_MIN2MAX)
v = max - min;
else
v = sum;
return v;
}
QUERY_VALUE rrdmetric2value(RRDHOST *host,
struct rrdcontext_acquired *rca, struct rrdinstance_acquired *ria, struct rrdmetric_acquired *rma,
time_t after, time_t before,
RRDR_OPTIONS options, RRDR_GROUPING group_method, const char *group_options,
size_t tier, time_t timeout, QUERY_SOURCE query_source, STORAGE_PRIORITY priority
) {
QUERY_TARGET_REQUEST qtr = {
.host = host,
.rca = rca,
.ria = ria,
.rma = rma,
.after = after,
.before = before,
.points = 1,
.options = options,
.group_method = group_method,
.group_options = group_options,
.tier = tier,
.timeout = timeout,
.query_source = query_source,
.priority = priority,
};
ONEWAYALLOC *owa = onewayalloc_create(16 * 1024);
RRDR *r = rrd2rrdr(owa, query_target_create(&qtr));
QUERY_VALUE qv;
if(!r || rrdr_rows(r) == 0) {
qv = (QUERY_VALUE) {
.value = NAN,
.anomaly_rate = NAN,
};
}
else {
qv = (QUERY_VALUE) {
.after = r->after,
.before = r->before,
.points_read = r->internal.db_points_read,
.result_points = r->internal.result_points_generated,
};
for(size_t t = 0; t < storage_tiers ;t++)
qv.storage_points_per_tier[t] = r->internal.tier_points_read[t];
long i = (!(options & RRDR_OPTION_REVERSED))?(long)rrdr_rows(r) - 1:0;
int all_values_are_null = 0;
qv.value = rrdr2value(r, i, options, &all_values_are_null, &qv.anomaly_rate);
if(all_values_are_null) {
qv.value = NAN;
qv.anomaly_rate = NAN;
}
}
rrdr_free(owa, r);
onewayalloc_destroy(owa);
return qv;
}
|
