Influxdata
/
influxdb
mirror of https://github.com/influxdata/influxdb.git
1
0
Fork 0
Code Issues Projects Releases Wiki Activity

fix: Only use timestamps in first/last when there is a corresponding … (#2988) 

* fix: Only use timestamps in first/last when there is a corresponding value

* docs: Fix broken English in comment

* docs: clarify expectations in test
pull/24376/head
Andrew Lamb 2021-11-01 14:54:43 -04:00 committed by GitHub
parent 6473498cd5
commit 5e86989990
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
2 changed files with 105 additions and 1 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

38
query/src/func/selectors/internal.rs
View File

@ -147,6 +147,25 @@ macro_rules! make_first_selector {
// the input type arguments should be ensured by datafusion
.expect("Second argument was time");
// Only look for times where the array also has a non
// null value (the time array should have no nulls itself)
//
// For example, for the following input, the correct
// current min time is 200 (not 100)
//
// value | time
// --------------
// NULL | 100
// A | 200
// B | 300
//
// Note this could likely be faster if we used `ArrayData` APIs
let time_arr: TimestampNanosecondArray = time_arr
.iter()
.zip(value_arr.iter())
.map(|(ts, value)| if value.is_some() { ts } else { None })
.collect();
let cur_min_time = $MINFUNC(&time_arr);
let need_update = match (&self.time, &cur_min_time) {
@ -235,6 +254,25 @@ macro_rules! make_last_selector {
// the input type arguments should be ensured by datafusion
.expect("Second argument was time");
// Only look for times where the array also has a non
// null value (the time array should have no nulls itself)
//
// For example, for the following input, the correct
// current max time is 200 (not 300)
//
// value | time
// --------------
// A | 100
// B | 200
// NULL | 300
//
// Note this could likely be faster if we used `ArrayData` APIs
let time_arr: TimestampNanosecondArray = time_arr
.iter()
.zip(value_arr.iter())
.map(|(ts, value)| if value.is_some() { ts } else { None })
.collect();
let cur_max_time = $MAXFUNC(&time_arr);
let need_update = match (&self.time, &cur_max_time) {

68
query_tests/src/influxrpc/read_group.rs
View File

@ -3,7 +3,7 @@ use crate::{
influxrpc::util::run_series_set_plan,
scenarios::{
make_two_chunk_scenarios, util::all_scenarios_for_one_chunk, DbScenario, DbSetup, NoData,
TwoMeasurementsManyFieldsOneChunk,
TwoMeasurementsManyFields, TwoMeasurementsManyFieldsOneChunk,
},
};
@ -540,6 +540,39 @@ async fn test_grouped_series_set_plan_first() {
.await;
}
#[tokio::test]
async fn test_grouped_series_set_plan_first_with_nulls() {
let predicate = PredicateBuilder::default()
// return three rows, but one series
// "h2o,state=MA,city=Boston temp=70.4 50",
// "h2o,state=MA,city=Boston other_temp=70.4 250",
// "h2o,state=MA,city=Boston temp=70.4,moisture=43.0 100000"
.table("h2o")
.add_expr(col("state").eq(lit("MA")))
.add_expr(col("city").eq(lit("Boston")))
.build();
let agg = Aggregate::First;
let group_columns = vec!["state"];
// expect timestamps to be present for all three series
let expected_results = vec![
"Group tag_keys: _field, _measurement, city, state partition_key_vals: MA",
"Series tags={_field=moisture, _measurement=h2o, city=Boston, state=MA}\n FloatPoints timestamps: [100000], values: [43.0]",
"Series tags={_field=other_temp, _measurement=h2o, city=Boston, state=MA}\n FloatPoints timestamps: [250], values: [70.4]",
"Series tags={_field=temp, _measurement=h2o, city=Boston, state=MA}\n FloatPoints timestamps: [50], values: [70.4]",
];
run_read_group_test_case(
TwoMeasurementsManyFields {},
predicate,
agg,
group_columns,
expected_results,
)
.await;
}
#[tokio::test]
async fn test_grouped_series_set_plan_last() {
let predicate = PredicateBuilder::default()
@ -568,6 +601,39 @@ async fn test_grouped_series_set_plan_last() {
.await;
}
#[tokio::test]
async fn test_grouped_series_set_plan_last_with_nulls() {
let predicate = PredicateBuilder::default()
// return two three:
// "h2o,state=MA,city=Boston temp=70.4 50",
// "h2o,state=MA,city=Boston other_temp=70.4 250",
// "h2o,state=MA,city=Boston temp=70.4,moisture=43.0 100000"
.table("h2o")
.add_expr(col("state").eq(lit("MA")))
.add_expr(col("city").eq(lit("Boston")))
.build();
let agg = Aggregate::Last;
let group_columns = vec!["state"];
// expect timestamps to be present for all three series
let expected_results = vec![
"Group tag_keys: _field, _measurement, city, state partition_key_vals: MA",
"Series tags={_field=moisture, _measurement=h2o, city=Boston, state=MA}\n FloatPoints timestamps: [100000], values: [43.0]",
"Series tags={_field=other_temp, _measurement=h2o, city=Boston, state=MA}\n FloatPoints timestamps: [250], values: [70.4]",
"Series tags={_field=temp, _measurement=h2o, city=Boston, state=MA}\n FloatPoints timestamps: [100000], values: [70.4]",
];
run_read_group_test_case(
TwoMeasurementsManyFields {},
predicate,
agg,
group_columns,
expected_results,
)
.await;
}
struct MeasurementForMin {}
#[async_trait]
impl DbSetup for MeasurementForMin {