Worldspan The travel challenge October 20, 2006
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Worldspan The travel challenge October 20, 2006
description
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. - PowerPoint PPT Presentation
Transcript of Worldspan The travel challenge October 20, 2006
Worldspan The travel challengeOctober 20, 2006
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Worldspan, Is not a household name and we mean it!
Think travel
• ShoppingExpedia, Orbitz, PriceLine, and many more including
your local travel agent
• Passenger HandlingBooking, seat assignment, baggage handling, meals,
etc.
• Airport SystemsCrew operation, equipment operation, inventory
management, billing, etc..
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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?
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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
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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
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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!
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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!
Q/A?
