TimeSeriesQueryLanguage 1.0.3

TimeSeries Query Language

This is a library to aggregate values on user defined time series datasets.

Quick Start

public class YOUREvalImplementationOnEFInMemory : ITimeSeriesQueryLanguageContext
{
    readonly YOURDbContext Db;
    public EvalImplementationOnEFInMemory(YOURDbContext db)
    {
        Db = db;
    }
    public async Task<decimal> Eval(string fn)
    {
        var tsqlp = new TimeSeriesQueryLanguageParser().Set(fn)?.Parse();
        return tsqlp == null ? 0.0m : await tsqlp.Eval(this);
    }
    public async Task<decimal> Eval(AggFn aggFn, AggCl aggCl = AggCl.Cl0, AggTs aggTsSlideTo = AggTs.M0, AggTs aggTsFrame = AggTs.D7, int i = 0)
    {
        var tsSlideTo = (await Db.Tickers.FirstAsync()).ts - AggTsToTimeSpanMapping.Map(aggTsSlideTo);
        var tsFrameMin = tsSlideTo - AggTsToTimeSpanMapping.Map(aggTsFrame);
        var tickers = Db.Tickers.Where(_ => _.ts <= tsSlideTo && _.ts >= tsFrameMin);

        switch (aggFn)
        {
            case AggFn.Cnt: return await tickers.CountAsync();
        }
        return 0.0m;
    }
}

// Count all rows in data
var c1 = await evalImplementationOnEFInMemory.Eval(AggFn.Cnt));

// Count rows in data for the last 5 mins
var c2 = await evalImplementationOnEFInMemory.Eval("ag(Cnt,Cl0,To.M0,Fr.M5)");										

// Count rows in data for the last 5 mins, starting 1 hour ago 
var c2 = await evalImplementationOnEFInMemory.Eval("ag(Cnt,Cl0,To.H1,Fr.M5)");										

Open the Samples project to see it in action with many more examples.

The Eval function: This function lives within your class implementation, that also holds a context to your data. You can query your data with aggregates, algebraic and logical operators. As the engine doesnt have knowledge of your dataset column names, a mapping will be needed.

Usage

The engine will interpret the function syntax, validate it and recall the Eval function on you implementation class, recursing all calls.

Aggregate Operators: ag Algebraic Operators: +, *, /, sc Logical Operators: &, |, <, >, in

Task<decimal> Eval(AggFn aggFn, AggCl aggCl = AggCl.Cl0, AggTs aggTsSlideTo = AggTs.M0, AggTs aggTsFrame = AggTs.M0, int i = 0) AggFn : Cnt, TxS, TxM, TxH, Fst, Snd, Pen, Lst, Min, Max, Avg, Sum, Dlt, MMP, FId, StD Used for aggregation data on your data implementation class

AggCl : Cl0, Cl1, Cl2, Cl3, Cl4, Cl5, Cl6, Cl7, Cl8, Cl9, Used for mapping to you data column fields

AggTs : M0 = 0, M1, M2, M5, M10, M15, M30, M45, H1, H2, H3, H5, H8, H17, H23, D1, D2, D3, D4, D5, D6, D7 Used for windowing the time series. aggTsSlideTo argument says how far back you want to go on your data. aggTsFrame argument defines the window time size.

Support

For support, email sidegence@gmail.com

Optimizations

Mappings are still needed for translating AggCl internal columns to your own dataset.