1. Abdullah Mueen 1

2. Architecture 2

3. Key Benefits Highly optimized performance and data throughput – Parallel execution of continuous queries over high-speed data. – Events are processed without costly data load or storage operations in the critical processing path..NET development environment – LINQ (Language Integrated Query) as an embedded query language. – Reduces development costs and the time. Flexible deployment capability – Needs only SQL Server 2008. Free for UCR Students. Manageability 3

4. Event Models 4 – Interval StartTime ::= DateTimeOffset EndTime ::= DateTimeOffset – Point StartTime ::= DateTimeOffset EndTime ::= StartTime + t – Edge Edge time ::= DateTimeOffset Edge type ::= START | END

5. Queries 5 – Projection var queryProject = from c in TestEventStream select new {i = c.i * 2, f = c.f * 2}; – Filtering var queryFilter = from c in someStream where c.i > 10 select c; – Joins var equiJoin = from e1 in stream1 join e2 in stream2 on e1.i equals e2.i select new{e1.i,e2.j}; – Aggregation var avgHourly = from win in inputStream.HoppingWindow (60, 5) select new { hourlyavg = win.Avg(e => e.f) }; – Union var unioned = stream1.Union(stream2);

6. Windows Event Windows – Count Windows Variable duration but fixed sized window of events – One parameter: Count – Hopping Windows Fixed duration but variable sized window of events – Two parameters: Duration and hop size – Snapshot Windows Variable duration window of a specific duration – No parameter: starts and ends at the starting or ending of an event 6

7. Windows – Count Windows – Hopping Windows – Snapshot Windows 7

8. Example: Lagged Correlation 8 var lags = sensorStream.ShiftEventTime(e => e.StartTime - TimeSpan.FromSeconds(30)); var joined = from e1 in sensorStream join e2 in lags select new{Value1 = e1.Value, Value2 = e2.Value}; var corr = from w in joined.HoppingWindow(60,1)select new { x = w.Corr(e => e.Value1, f => f.Value2) };