So 1.44PB is a billion diskettes. If you stack them eight to the inch, that's about 2,000 miles of diskettes. A tornado may as well have picked all of us up from a world in which a high-density floppy disk stored a fair amount of data, dropping us moments later into a world where some companies have more data than you can store on all the floppy disks you can stack between Denver and my office in Waltham. I find myself thinking back to fundamentals. I believe this will be helpful in grasping today's data volumes and getting a sense of what they mean for query processing in the data warehouse.
Joins are fundamental to relational database management.
The simplest algorithm for performing this query is shown in Listing 1 . This approach is correct and works fine if the database is small. In a large business providing retail products or services, it would not be unusual to have data on 10 million customers and a billion transactions in the data warehouse. Suppose further that customer rows are 2,500 bytes long and transaction rows are 100 bytes long. The customer table contains 25GB of data and the transaction table contains 100GB of data.