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test: int test

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Signed-off-by: discord9 <discord9@163.com>
This commit is contained in:
discord9
2026-03-20 18:03:56 +08:00
parent 53aa78c55f
commit 4265f44700
1 changed files with 237 additions and 1 deletions
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238
tests-integration/src/tests/promql_test.rs
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@@ -15,7 +15,9 @@
use std::sync::Arc;
use std::time::{Duration, SystemTime, UNIX_EPOCH};
use common_query::Output;
use common_query::{Output, OutputData};
use common_recordbatch::util::collect_batches;
use datatypes::arrow::array::{Float64Array, Int64Array};
use frontend::instance::Instance;
use query::parser::{PromQuery, QueryLanguageParser, QueryStatement};
use rstest::rstest;
@@ -151,6 +153,103 @@ async fn create_insert_tql_assert(
check_unordered_output_stream(query_output, expected).await;
}
async fn execute_all(instance: &Arc<Instance>, sql: &str, query_ctx: Arc<QueryContext>) {
instance
.do_query(sql, query_ctx)
.await
.into_iter()
.for_each(|v| {
let _ = v.unwrap();
});
}
#[allow(clippy::too_many_arguments)]
async fn promql_query_as_batches(
ins: Arc<Instance>,
promql: &str,
alias: Option<String>,
query_ctx: Arc<QueryContext>,
start: SystemTime,
end: SystemTime,
interval: Duration,
lookback: Duration,
) -> common_recordbatch::RecordBatches {
let output = promql_query(
ins, promql, alias, query_ctx, start, end, interval, lookback,
)
.await
.unwrap();
match output.data {
OutputData::Stream(stream) => collect_batches(stream).await.unwrap(),
OutputData::RecordBatches(recordbatches) => recordbatches,
_ => unreachable!(),
}
}
const ANON_PROMQL_RATIO_REPRO_DB: &str = "repro_db";
const ANON_PROMQL_RATIO_REPRO_CREATE: &str = r#"
CREATE TABLE phy (
t TIMESTAMP TIME INDEX,
v DOUBLE
) ENGINE=metric WITH ("physical_metric_table" = "");
CREATE TABLE metric_a (
l1 STRING NULL,
l2 STRING NULL,
l3 STRING NULL,
l4 STRING NULL,
l5 STRING NULL,
t TIMESTAMP NOT NULL,
v DOUBLE NULL,
TIME INDEX (t),
PRIMARY KEY (l1, l2, l3, l4, l5)
) ENGINE=metric WITH (on_physical_table = 'phy');
CREATE TABLE metric_b (
l6 STRING NULL,
l1 STRING NULL,
l2 STRING NULL,
l3 STRING NULL,
l4 STRING NULL,
t TIMESTAMP NOT NULL,
v DOUBLE NULL,
TIME INDEX (t),
PRIMARY KEY (l6, l1, l2, l3, l4)
) ENGINE=metric WITH (on_physical_table = 'phy');
"#;
const ANON_PROMQL_RATIO_REPRO_INSERT: &str = r#"
INSERT INTO metric_a (l1, l2, l3, l4, l5, t, v) VALUES
('v1', 'v2', 'v3', 'v4a', 'v5a', 1, 0),
('v1', 'v2', 'v3', 'v4a', 'v5a', 180000, 120),
('v1', 'v2', 'v3', 'v4a', 'v5a', 360000, 240),
('v1', 'v2', 'v3', 'v4a', 'v5b', 1, 0),
('v1', 'v2', 'v3', 'v4a', 'v5b', 180000, 30),
('v1', 'v2', 'v3', 'v4a', 'v5b', 360000, 60),
('v1', 'v2', 'v3-b', 'v4b', 'v5c', 1, 0),
('v1', 'v2', 'v3-b', 'v4b', 'v5c', 180000, 60),
('v1', 'v2', 'v3-b', 'v4b', 'v5c', 360000, 120);
INSERT INTO metric_b (l6, l1, l2, l3, l4, t, v) VALUES
('v6', 'v1', 'v2', 'v3', 'v4a', 1, 1),
('v6', 'v1', 'v2', 'v3', 'v4a', 180000, 1),
('v6', 'v1', 'v2', 'v3', 'v4a', 360000, 1),
('v6', 'v1', 'v2', 'v3-b', 'v4b', 1, 2),
('v6', 'v1', 'v2', 'v3-b', 'v4b', 180000, 2),
('v6', 'v1', 'v2', 'v3-b', 'v4b', 360000, 2);
"#;
const ANON_PROMQL_RATIO_REPRO_NUMERATOR: &str = r#"count(((rate(metric_a{l1="v1",l2="v2",l3=~"v3(|-a|-b)",__schema__="repro_db"}[3m]) / on(l3,l4) group_left metric_b{l6="v6",l1="v1",l2="v2",l3=~"v3(|-a|-b)",__schema__="repro_db"}) > 0.50))"#;
const ANON_PROMQL_RATIO_REPRO_DENOMINATOR: &str =
r#"count(rate(metric_a{l1="v1",l2="v2",l3=~"v3(|-a|-b)",__schema__="repro_db"}[3m]))"#;
const ANON_PROMQL_RATIO_REPRO_WHOLE: &str = r#"(count(((rate(metric_a{l1="v1",l2="v2",l3=~"v3(|-a|-b)",__schema__="repro_db"}[3m]) / on(l3,l4) group_left metric_b{l6="v6",l1="v1",l2="v2",l3=~"v3(|-a|-b)",__schema__="repro_db"}) > 0.50)) / count(rate(metric_a{l1="v1",l2="v2",l3=~"v3(|-a|-b)",__schema__="repro_db"}[3m]))) * 100"#;
const ANON_PROMQL_RATIO_REPRO_SCALAR_DIV: &str =
r#"count(rate(metric_a{l1="v1",l2="v2",l3=~"v3(|-a|-b)",__schema__="repro_db"}[3m])) / 2"#;
#[apply(both_instances_cases)]
async fn sql_insert_tql_query_ceil(instance: Arc<dyn MockInstance>) {
let instance = instance.frontend();
@@ -709,3 +808,140 @@ async fn cross_schema_query(instance: Arc<dyn MockInstance>) {
check_unordered_output_stream(query_output, expected).await;
}
#[apply(both_instances_cases)]
async fn anon_promql_ratio_repro(instance: Arc<dyn MockInstance>) {
let ins = instance.frontend();
execute_all(
&ins,
&format!("CREATE DATABASE {ANON_PROMQL_RATIO_REPRO_DB}"),
QueryContext::arc(),
)
.await;
let repro_ctx: Arc<QueryContext> =
QueryContext::with_db_name(Some(ANON_PROMQL_RATIO_REPRO_DB)).into();
execute_all(&ins, ANON_PROMQL_RATIO_REPRO_CREATE, repro_ctx.clone()).await;
execute_all(&ins, ANON_PROMQL_RATIO_REPRO_INSERT, repro_ctx).await;
let start = UNIX_EPOCH.checked_add(Duration::from_secs(180)).unwrap();
let end = UNIX_EPOCH.checked_add(Duration::from_secs(360)).unwrap();
let interval = Duration::from_secs(180);
let lookback = Duration::from_secs(1);
let numerator = promql_query_as_batches(
ins.clone(),
ANON_PROMQL_RATIO_REPRO_NUMERATOR,
Some("num".to_string()),
QueryContext::arc(),
start,
end,
interval,
lookback,
)
.await;
let denominator = promql_query_as_batches(
ins.clone(),
ANON_PROMQL_RATIO_REPRO_DENOMINATOR,
Some("den".to_string()),
QueryContext::arc(),
start,
end,
interval,
lookback,
)
.await;
let whole = promql_query_as_batches(
ins.clone(),
ANON_PROMQL_RATIO_REPRO_WHOLE,
Some("pct".to_string()),
QueryContext::arc(),
start,
end,
interval,
lookback,
)
.await;
let scalar_div = promql_query_as_batches(
ins,
ANON_PROMQL_RATIO_REPRO_SCALAR_DIV,
Some("half_den".to_string()),
QueryContext::arc(),
start,
end,
interval,
lookback,
)
.await;
let numerator = numerator.iter().collect::<Vec<_>>();
let denominator = denominator.iter().collect::<Vec<_>>();
let whole = whole.iter().collect::<Vec<_>>();
let scalar_div = scalar_div.iter().collect::<Vec<_>>();
let numerator_values = numerator[0]
.column_by_name("num")
.unwrap()
.as_any()
.downcast_ref::<Int64Array>()
.unwrap();
let denominator_values = denominator[0]
.column_by_name("den")
.unwrap()
.as_any()
.downcast_ref::<Int64Array>()
.unwrap();
let percentage_values = whole[0]
.column_by_name("pct")
.unwrap()
.as_any()
.downcast_ref::<Float64Array>()
.unwrap();
let scalar_div_values = scalar_div[0]
.column_by_name("half_den")
.unwrap()
.as_any()
.downcast_ref::<Float64Array>()
.unwrap();
assert_eq!(numerator_values.len(), 1, "{}", numerator[0].pretty_print());
assert_eq!(
denominator_values.len(),
1,
"{}",
denominator[0].pretty_print()
);
assert_eq!(percentage_values.len(), 1, "{}", whole[0].pretty_print());
assert_eq!(
scalar_div_values.len(),
1,
"{}",
scalar_div[0].pretty_print()
);
assert_eq!(
numerator_values.value(0),
1,
"{}",
numerator[0].pretty_print()
);
assert_eq!(
denominator_values.value(0),
3,
"{}",
denominator[0].pretty_print()
);
assert!(
(scalar_div_values.value(0) - 1.5).abs() < 1e-9,
"{}",
scalar_div[0].pretty_print()
);
let expected = 100.0 / 3.0;
assert!(
(percentage_values.value(0) - expected).abs() < 1e-9,
"{}",
whole[0].pretty_print()
);
}