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DATA WAREHOUSING
Physical Design
2
   Logical database design
     What are the facts and dimensions?
     Goals: Simplicity, Expressiveness
     Make the database easy to understand
     Make queries easy to ask
   Physical database design
     How should the data be arranged on disk?
     Goal: Performance
      ▪ Manageability is an important secondary concern
     Make queries run fast
   Trade-off between query performance and
    load performance
   To make queries run fast:
     Precompute as much as possible
     Build lots of data structures
      ▪ Partitions
      ▪ Materialized views
      ▪ Indexes
   But…
     Data structures require disk space to store
     Building/updating data structures takes
      time
     More data structures → longer load time
   Base data
     Fact tables and dimension tables
     Fact table space >> Dimension table space
   Indexes
     100%-200% of base data
   Aggregates / Materialized Views
     100% of base data
   Extra data structures 2-3 times size of base data
   The Data Warehouse Toolkit.Second Edition.The
    Complete Guide to Dimensional Modeling.Ralph
    Kimball.Margy Ross

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Diseño fisico 1

  • 2. 2
  • 3. Logical database design  What are the facts and dimensions?  Goals: Simplicity, Expressiveness  Make the database easy to understand  Make queries easy to ask
  • 4. Physical database design  How should the data be arranged on disk?  Goal: Performance ▪ Manageability is an important secondary concern  Make queries run fast
  • 5. Trade-off between query performance and load performance
  • 6. To make queries run fast:  Precompute as much as possible  Build lots of data structures ▪ Partitions ▪ Materialized views ▪ Indexes
  • 7. But…  Data structures require disk space to store  Building/updating data structures takes time  More data structures → longer load time
  • 8. Base data  Fact tables and dimension tables  Fact table space >> Dimension table space  Indexes  100%-200% of base data  Aggregates / Materialized Views  100% of base data  Extra data structures 2-3 times size of base data
  • 9. The Data Warehouse Toolkit.Second Edition.The Complete Guide to Dimensional Modeling.Ralph Kimball.Margy Ross