VictoriaMetrics/app/vmctl/influx/influx_test.go

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package influx
import "testing"
func TestFetchQuery(t *testing.T) {
f := func(s *Series, timeFilter, resultExpected string) {
t.Helper()
result := s.fetchQuery(timeFilter)
if result != resultExpected {
t.Fatalf("unexpected result\ngot\n%s\nwant\n%s", result, resultExpected)
}
}
f(&Series{
Measurement: "cpu",
Field: "value",
LabelPairs: []LabelPair{
{
Name: "foo",
Value: "bar",
},
},
}, "", `select "value" from "cpu" where "foo"::tag='bar'`)
f(&Series{
Measurement: "cpu",
Field: "value",
LabelPairs: []LabelPair{
{
Name: "foo",
Value: "bar",
},
{
Name: "baz",
Value: "qux",
},
},
}, "", `select "value" from "cpu" where "foo"::tag='bar' and "baz"::tag='qux'`)
f(&Series{
Measurement: "cpu",
Field: "value",
LabelPairs: []LabelPair{
{
Name: "foo",
Value: "b'ar",
},
},
}, "time >= now()", `select "value" from "cpu" where "foo"::tag='b\'ar' and time >= now()`)
f(&Series{
Measurement: "cpu",
Field: "value",
LabelPairs: []LabelPair{
{
Name: "name",
Value: `dev-mapper-centos\x2dswap.swap`,
},
{
Name: "state",
Value: "dev-mapp'er-c'en'tos",
},
},
}, "time >= now()", `select "value" from "cpu" where "name"::tag='dev-mapper-centos\\x2dswap.swap' and "state"::tag='dev-mapp\'er-c\'en\'tos' and time >= now()`)
f(&Series{
Measurement: "cpu",
Field: "value",
}, "time >= now()", `select "value" from "cpu" where time >= now()`)
f(&Series{
Measurement: "cpu",
Field: "value",
}, "", `select "value" from "cpu"`)
vmctl: fixed import duplicate data when query result contains multiple series (#7330) ### Describe Your Changes Fix https://github.com/VictoriaMetrics/VictoriaMetrics/issues/7301 When querying with condition like `WHERE a=1` (looking for series A), InfluxDB can return data with the tag `a=1` (series A) and data with the tag `a=1,b=1` (series B). However, series B is will be queried later and it's data should not be combined into series A's data. This PR filter those series that are not identical to the original query condition. For table `example`: ``` // time host region value // ---- ---- ------ ----- // 2024-10-25T02:12:13.469720983Z serverA us_west 0.64 // 2024-10-25T02:12:21.832755213Z serverA us_west 0.75 // 2024-10-25T02:12:32.351876479Z serverA 0.88 // 2024-10-25T02:12:37.766320484Z serverA 0.95 ``` The query for series A (`example_value{host="serverA"}`) and result will be: ```SQL SELECT * FROM example WHERE host = "serverA" ``` ```json { "results": [{ "statement_id": 0, "series": [{ "name": "cpu", "columns": ["time", "host", "region", "value"], "values": [ ["2024-10-25T02:12:13.469720983Z", "serverA", "us_west", 0.64], ["2024-10-25T02:12:21.832755213Z", "serverA", "us_west", 0.75], ["2024-10-25T02:12:32.351876479Z", "serverA", null, 0.88], ["2024-10-25T02:12:37.766320484Z", "serverA", null, 0.95] ] }] }] } ``` We need to abandon `values[0]` and `values[1]` because the value of **unwanted** column `region` is not null. As for series B (`example_value{host="serverA", region="us_west"}`), no change needed since the query filter out unwanted rows already. ### Note This is a draft PR for verifying the fix. ### Checklist The following checks are **mandatory**: - [x] My change adheres [VictoriaMetrics contributing guidelines](https://docs.victoriametrics.com/contributing/). --------- Signed-off-by: hagen1778 <roman@victoriametrics.com> Co-authored-by: hagen1778 <roman@victoriametrics.com> (cherry picked from commit f16a58f14c43663ca35093b6583539934bdc6544)
2024-11-06 12:53:49 +00:00
f(&Series{
Measurement: "cpu",
Field: "value1",
EmptyTags: []string{"e1", "e2", "e3"},
}, "", `select "value1" from "cpu" where "e1"::tag='' and "e2"::tag='' and "e3"::tag=''`)
}
func TestTimeFilter(t *testing.T) {
f := func(start, end, resultExpected string) {
t.Helper()
result := timeFilter(start, end)
if result != resultExpected {
t.Fatalf("unexpected result\ngot\n%v\nwant\n%s", result, resultExpected)
}
}
// no start and end filters
f("", "", "")
// missing end filter
f("2020-01-01T20:07:00Z", "", "time >= '2020-01-01T20:07:00Z'")
// missing start filter
f("", "2020-01-01T21:07:00Z", "time <= '2020-01-01T21:07:00Z'")
// both start and end filters
f("2020-01-01T20:07:00Z", "2020-01-01T21:07:00Z", "time >= '2020-01-01T20:07:00Z' and time <= '2020-01-01T21:07:00Z'")
}