1. The Top 10 Reasons Why Federated Can’t Succeed And Why it Will Anyway

2. But First…  What is our purpose as a community? Produce (wonderful) new ideas Structure the field Educate the workforce

3. A Brief History of Federation  Multibase @1980  Many attempts since Functional Relational Object-oriented Logic-based XML  Still not solved (think of last night)  And never will be?

4. Number 10: Robustness  Systems fail  Sources slow or unavailable  In a distributed system, more pieces => more failures  Users don’t like failures

5. Number 9: Security  Different systems have different security mechanisms Hard to create a single coherent view of permissions  Distributed systems are more vulnerable More points of failure Hard to make security guarantees  Data is often the corporate jewels It must be protected

6. Number 8: Updates  Recording change isn’t always an UPDATE Application semantics must be accounted for Application APIs must be reckoned with  ACIDity isn’t always achievable Not all data sources display ACID properties  Varying degrees of support Strong transaction semantics not always possible or appropriate  And always painful Changes to multiple sources must be coordinated  Requirements for consistency vary

7. Number 7: Configurability  Many architectures possible Even with pre-existing sources, many choices Little or no guidance on tradeoffs  Lots of code to install Federation engine, data source clients Often choices here  Lots of connections to define Need tooling to support

8. Number 6: Administration  Monitoring is hard Not all sources have facilities to track events Variety of mechanisms for different events, and different sources Not always APIs  Tuning is difficult Need to understand what must change Need to take appropriate actions  Repairing is painful Distributed debugging Different vendors to deal with for fixes

9. Number 5: Semantic heterogeneity  Hard to identify commonalities Same terms, different meanings Different terms, same meaning Different structures representing different interpretations  Can’t integrate data effectively without them Can’t make sensible queries

10. Number 4: Insufficient Metadata  Need metadata to integrate, configure, administer and query  Every data source has different metadata No uniform standard Not always collected  Tools to examine and exploit missing

11. Number 3: Performance (Data Movement)  Distributed queries involve moving data  Geographic distribution is common WAN is slow  Large data volumes common Large numbers of objects Large objects  Caching isn’t a complete answer Changes can be frequent and hard to track Storage is not unlimited

12. Number 2: Performance (Complexity)  Decision-support appls do complex queries Many choices for how to execute Big differences in performance among choices  Need data from diverse sources May not have enough power in source Performance at sources may vary  Need expensive functions of data Function may not be implemented everywhere Flowing the data to the function expensive

13. Number 1: Performance (Pathlength)  Simple queries (OLTP-like) incur huge overheads Processing and networking costs  Simple queries are common Easier to write Automatically produced Workflows

14. So Why Will Federated Succeed?  It has to Integration one of the top IT issues  And it’s not going away Alternatives are expensive and/or painful  Write it by hand  EAI/Workflow  Consolidation (warehouse, data marts…)

15. So Why Will Federated Succeed? (2)  Simple scenarios exist Don’t need OLTP, high security, great robustness, … for all applications Customers know their data, or must learn anyway Needs are so great, compromise is possible

16. So Why Will Federated Succeed? (3)  Progress on technology being made 20 years of distributed query processing Plumbing in place  Commit protocols  Reliable messaging  Connectivity infrastructure XML (basic community agreement)  XML data format  XML schema  Web services We’re getting closer

17. What would we do if it ever did work?  Retire  Integrate the web? Data grids Data Google  P2P database?

18. For Discussion  Is research in this area warranted?  What are the most important research topics? Did we miss any?