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I would like someone to work on…. Jeff Naughton UW-Madison. Consider the following scenario…. A network of 100,000 sensors. Resulting stream of sensor data requires sophisticated processing: “standing” or continuous queries
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I would like someone to work on… Jeff Naughton UW-Madison
Consider the following scenario… • A network of 100,000 sensors. • Resulting stream of sensor data requires sophisticated processing: • “standing” or continuous queries • Ad-hoc queries over current and 10s – 100s of terabytes of archived data • This processing is mission critical and essential for timely reaction to changing environment as perceived by the sensors.
But this is Wal-Mart today! • Obviously I am not the first to make this observation. • This is more “where Wal-Mart would like to be” than “where it is.” • My point: much of stream processing is not new – it is an old unsolved problem. • There remain important and hard issues in these old unsolved problems – and they should not be relegated to “delta X work on classic problems” status.
Is all of stream processing old? • No – some new interesting problems: • Extreme resource constrained scenarios (tiny batteries, wimpy processors, anemic networks) • Streams too fast to look at more than once • But these are not the only or perhaps even the most important challenging stream problems.
Digression • In my youth I worked a little on object-oriented DBMS. • The “grand old men” (they were men) of the field said “objects are nice, but don’t be stupid, why throw away RDBMS – add objects to them instead of starting from scratch!” • They were right!
So what do I wish someone would work on? • Investigate the following: • Stream processing is important, and not just in the realm of extremely limited resources. • But don’t be stupid, in addition to investigating the “start from scratch” approach, answer the following: • Can existing RDBMS technology be extended or modified to be better at stream processing? • If yes, how? • If no, why not? What is the fundamental limitation?