Files
lmxopcua/tests/Drivers/ZB.MOM.WW.OtOpcUa.Driver.Historian.Sql.Common.Tests/AggregateEvaluatorTests.cs
T
Joseph Doherty 1f88669304 feat(historian): Part 13 time-weighted aggregates on SqlServer + QuestDb (#671)
New AggregateFamily.TimeWeighted serving TimeAverage, TimeAverage2, Total,
Total2 and Interpolative, evaluated by the shared Sql.Common
TimeWeightedAggregator for both SQL backends (identical results by
construction). HistoryAggregateType gains TimeAverage2 + Total2 (appended);
OtOpcUaNodeManager.MapAggregate maps their NodeIds. Gateway's mapper already
refuses unknown defined members => BadAggregateNotSupported per node.

Semantics (server defaults, client AggregateConfiguration ignored):
TreatUncertainAsBad=false, PercentDataBad=PercentDataGood=100,
UseSlopedExtrapolation=false. Sloped for Double/Int64, stepped for Boolean;
a usable sample followed by a Bad one is held up to the outage (AtTime rule);
stepped Uncertain extrapolation past the last sample. TimeAverage/Total use
interpolated bounding (bridge outages); TimeAverage2/Total2 exclude Bad time.
Bounding values: latest usable + latest any before start, first any + first
usable at/after end (four TOP 1 / LIMIT 1 seeks).

CLIENT-VISIBLE: Total on SqlServer/QuestDb was SUM of samples; it is now the
time-weighted integral (TimeAverage x interval seconds), matching Gateway's
Integral. Release note in docs/Historian.md.

Trade-off (deviation from the preferred hybrid pushdown, allowed by the
design): the time-weighted family is NOT pushed down. Each read streams the
window's rows plus the four bounds (SQL Server: one five-result-set batch;
QuestDB: bounds UNION ALL + window select) into the C# evaluator. Network is
O(samples in window), memory O(buckets). Writing the per-segment
interpolation/edge splitting twice in two SQL dialects and keeping them
bit-identical was judged the bigger risk; this also makes the QuestDB
lag/lead spike moot.

Tests: 35 hand-computed TimeWeightedAggregator unit cases (each of 10
implementation mutations goes red); served-aggregate pin 13 -> 17;
conformance sparse fixture (intervals wider and narrower than sample gaps)
+ an outage straddling both window edges (each of the four SQL seeks
disabled in turn goes red); node-manager NodeId mapping test.
2026-10-11 08:44:44 -04:00

132 lines
6.2 KiB
C#

using Shouldly;
using Xunit;
using ZB.MOM.WW.OtOpcUa.Core.Abstractions;
using static ZB.MOM.WW.OtOpcUa.Driver.Historian.Sql.Common.Tests.Fixture;
namespace ZB.MOM.WW.OtOpcUa.Driver.Historian.Sql.Common.Tests;
/// <summary>
/// Direct tests of the aggregate evaluator over hand-built bucket rows for tag A, 20 s intervals from T0, window
/// [t0, t0+80s): B0 = {10, 20}; B1 = {Bad 30, 40}; B2 = {50}; B3 empty. Literals from the SqlServer
/// <c>ProcessedReadTests</c>.
/// </summary>
public sealed class AggregateEvaluatorTests
{
private static readonly DateTime Now = At(3600);
private static Dictionary<long, BucketRow> RowsA(bool maximum = false) => new()
{
[0] = new BucketRow
{
Bucket = 0, Total = 2, Usable = 2, Good = 2, Bad = 0, NonNumeric = 0, Avg = 15, Min = 10, Max = 20, Sum = 30,
First = HistorianValue.FromDouble(10), Last = HistorianValue.FromDouble(20),
Extreme = maximum ? 20 : 10, ExtremeTime = maximum ? At(10) : At(0),
},
[1] = new BucketRow
{
Bucket = 1, Total = 2, Usable = 1, Good = 1, Bad = 1, NonNumeric = 0, Avg = 40, Min = 40, Max = 40, Sum = 40,
First = HistorianValue.FromDouble(40), Last = HistorianValue.FromDouble(40), Extreme = 40, ExtremeTime = At(30),
},
[2] = new BucketRow
{
Bucket = 2, Total = 1, Usable = 1, Good = 1, Bad = 0, NonNumeric = 0, Avg = 50, Min = 50, Max = 50, Sum = 50,
First = HistorianValue.FromDouble(50), Last = HistorianValue.FromDouble(50), Extreme = 50, ExtremeTime = At(40),
},
};
private static IReadOnlyList<DataValueSnapshot> ReadA(HistoryAggregateType agg, bool maximum = false)
{
var plan = BucketPlan.Create(At(0), At(80), TimeSpan.FromSeconds(20));
var evaluated = RowsA(maximum).ToDictionary(kv => kv.Key,
kv => AggregateEvaluator.Evaluate(agg, kv.Value, plan.BucketStart(kv.Key), Now));
return plan.Assemble(evaluated, t => AggregateEvaluator.NoData(t, Now));
}
[Theory]
[InlineData(HistoryAggregateType.Average, 15d, 40d, 50d)]
[InlineData(HistoryAggregateType.Minimum, 10d, 40d, 50d)]
[InlineData(HistoryAggregateType.Maximum, 20d, 40d, 50d)]
[InlineData(HistoryAggregateType.Start, 10d, 40d, 50d)]
[InlineData(HistoryAggregateType.End, 20d, 40d, 50d)]
[InlineData(HistoryAggregateType.Delta, 10d, 0d, 0d)]
[InlineData(HistoryAggregateType.Range, 10d, 0d, 0d)]
public void Numeric_aggregates_over_hand_built_bucket_rows(HistoryAggregateType agg, double b0, double b1, double b2)
{
var s = ReadA(agg);
s.Count.ShouldBe(4);
s.Select(x => x.Value).ShouldBe([b0, b1, b2, null]);
s.Select(x => x.StatusCode).ShouldBe([GoodCalc, UncertainCalc, GoodCalc, NoDataCalc]);
s.Select(x => x.SourceTimestampUtc).ShouldBe([At(0), At(20), At(40), At(60)]);
}
[Fact]
public void Count_counts_usable_samples_as_int()
{
var s = ReadA(HistoryAggregateType.Count);
s.Select(x => x.Value).ShouldBe([(object?)2, 1, 1, null]);
s.Select(x => x.StatusCode).ShouldBe([GoodCalc, UncertainCalc, GoodCalc, NoDataCalc]);
}
[Theory]
[InlineData(HistoryAggregateType.PercentGood, 100d, 50d, 100d)]
[InlineData(HistoryAggregateType.PercentBad, 0d, 50d, 0d)]
public void Percent_aggregates_count_every_sample_and_stay_good(HistoryAggregateType agg, double b0, double b1, double b2)
{
var s = ReadA(agg);
s.Select(x => x.Value).ShouldBe([b0, b1, b2, null]);
s.Select(x => x.StatusCode).ShouldBe([GoodCalc, GoodCalc, GoodCalc, NoDataCalc]);
}
[Fact]
public void Actual_time_aggregates_stamp_the_sample_time()
{
var min = ReadA(HistoryAggregateType.MinimumActualTime);
min.Select(x => x.Value).ShouldBe([10d, 40d, 50d, null]);
min.Select(x => x.SourceTimestampUtc).ShouldBe([At(0), At(30), At(40), At(60)]);
min.Select(x => x.StatusCode).ShouldBe([GoodCalc, UncertainCalc, GoodCalc, NoDataCalc]);
var max = ReadA(HistoryAggregateType.MaximumActualTime, maximum: true);
max.Select(x => x.Value).ShouldBe([20d, 40d, 50d, null]);
max.Select(x => x.SourceTimestampUtc).ShouldBe([At(10), At(30), At(40), At(60)]);
}
[Fact]
public void A_usable_non_numeric_sample_makes_a_numeric_aggregate_invalid_inputs_but_not_count()
{
var row = new BucketRow { Total = 2, Usable = 2, Good = 2, NonNumeric = 1, Avg = 1, First = HistorianValue.FromString("x"),
Last = HistorianValue.FromDouble(1) };
var avg = AggregateEvaluator.Evaluate(HistoryAggregateType.Average, row, At(0), Now);
avg.Value.ShouldBeNull();
avg.StatusCode.ShouldBe(InvalidInputsCalc);
AggregateEvaluator.Evaluate(HistoryAggregateType.Count, row, At(0), Now).Value.ShouldBe(2);
AggregateEvaluator.Evaluate(HistoryAggregateType.Delta, row, At(0), Now).StatusCode.ShouldBe(InvalidInputsCalc);
}
[Fact]
public void A_bucket_with_only_bad_samples_is_no_data_except_for_the_percentages()
{
var row = new BucketRow { Total = 2, Usable = 0, Good = 0, Bad = 2 };
var avg = AggregateEvaluator.Evaluate(HistoryAggregateType.Average, row, At(0), Now);
avg.Value.ShouldBeNull();
avg.StatusCode.ShouldBe(NoDataCalc);
AggregateEvaluator.Evaluate(HistoryAggregateType.PercentBad, row, At(0), Now).Value.ShouldBe(100d);
}
[Fact]
public void An_unsupported_aggregate_throws_not_supported()
{
var ex = Should.Throw<HistoryAggregateNotSupportedException>(() =>
AggregateEvaluator.Evaluate(HistoryAggregateType.TimeAverage, RowsA()[0], At(0), Now));
ex.Aggregate.ShouldBe(HistoryAggregateType.TimeAverage);
}
[Fact]
public void An_uncertain_sample_in_a_bucket_degrades_the_aggregate_to_uncertain()
{
// Two usable samples, one Good and one Uncertain, no Bad: the value is computed, the status is Uncertain.
var row = new BucketRow { Total = 2, Usable = 2, Good = 1, Bad = 0, Avg = 15, Min = 10, Max = 20, Sum = 30 };
var avg = AggregateEvaluator.Evaluate(HistoryAggregateType.Average, row, At(0), Now);
avg.Value.ShouldBe(15d);
avg.StatusCode.ShouldBe(UncertainCalc);
}
}