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Worldspan The travel challenge October 20, 2006

Worldspan The travel challenge October 20, 2006. Worldspan, Is not a household name and we mean it!. Think travel Shopping Expedia, Orbitz, PriceLine, and many more including your local travel agent Passenger Handling Booking, seat assignment, baggage handling, meals, etc.

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Worldspan The travel challenge October 20, 2006

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  1. Worldspan The travel challengeOctober 20, 2006

  2. Worldspan, Is not a household name and we mean it! Think travel • Shopping Expedia, Orbitz, PriceLine, and many more including your local travel agent • Passenger Handling Booking, seat assignment, baggage handling, meals, etc. • Airport Systems Crew operation, equipment operation, inventory management, billing, etc.. 2

  3. Travel Shopping A Case Study • DL alone has about 4 Million Fares at any point of time • Each Fare has dozens of rules • A total 540 airlines in the Worldspan system including both International and domestic carriers • Worldwide currencies and taxes • Fares are updated 8 times a day • Inventory changes continuously Do you see the problem? 3

  4. The problem! • Thirty years worth of code mainly assembler on Mainframe • Hyper application, shopping is multiple applications in one • 10% of the entries represent 80% of the MIPS (system resources) • Internet, the equalizer and explosion of cost 4

  5. The solution – Installment 1 To move the application from Mainframe to server we had to find a solution that adhere to the following constraints:1) Use commodity servers 2) Achieve response time comparable to Mainframe response time 3) 24/7 availability 4) Accept and process all updates within SLAs How we did it? 1) All data is preprocessed into a relational flat files,16 GB for Fares alone and at least another 3 GB of auxiliary data 2) Transfer all the data to all the servers (1,200 of them) Challenges: 1) Preprocessing time 2) New data impact 3) Cold server phenomena 5

  6. The solution – Installment 2 Using a real database on the cheap! • Response time is a major concern • Low cost is essential • Solution: working with GT, 98% of the right data has to be local all the time • Understanding relationships: traffic, geography, data utilization • Understanding and proactively handling capacity needs • Transferring only updated required data • Do you know what will be installment three? Reverse engineering! 6

  7. Thoughts and conclusions! • Cost, cost and then cost! • Constraints is a part of any problem solving process! • There is no one big bang, it comes in pieces! • There is always a place for Academia but we need to learn to work together! 7

  8. Q/A?

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