Part Two: - The use of views. 1

Topics What is a View? Why Views are useful in Data Warehousing? Understand Materialised Views Understand View Maintenance policies 2

Views and Decision Support OLAP queries are typically aggregate queries. Precomputation is essential for interactive response times. The CUBE is in fact a collection of aggregate queries, and precomputation is especially important: lots of work on what is best to precompute given a limited amount of space to store precomputed results. Warehouses can be thought of as a collection of asynchronously replicated tables and periodically maintained views. 3

What is a VIEW A “virtual table” Does not exist as a base table in the database Automatically activated when referenced in an SQL statement. Views are stored SQL statements. Created with the Create View statement Can be dropped with Drop View 4

To create a simple view on the employee table Create view empdept30 As Select ename, sal, comm From Emp Where deptno = 30; The View can then be used and referenced as if it were a normal table:- Select ename, sal from empdept30; 5

Another example 6

View Modification (Evaluate On Demand) CREATE VIEW RegionalSales(category,sales,state) AS SELECT P.category, S.sales, L.state FROM Products P, Sales S, Locations L WHERE P.pid=S.pid AND S.locid=L.locid SELECT R.category, R.state, SUM (R.sales) FROM RegionalSales AS R GROUP BY R.category, R.state SELECT R.category, R.state, SUM (R.sales) FROM ( SELECT P.category, S.sales, L.state FROM Products P, Sales S, Locations L WHERE P.pid=S.pid AND S.locid=L.locid) AS R GROUP BY R.category, R.state View Query Modified Query 7

Materialized Views A view whose tuples are stored in the database is said to be materialized. Provides fast access, like a (very high-level) cache. Need to maintain the view as the underlying tables change. Ideally, we want incremental view maintenance algorithms. Views are closely related to data warehousing, and OLAP. 8

Extract, Transform and Load (ETL) Transforming data is typically accomplished by defining a relational View over the tables in the data sources. Loading data then consists of materializing such views and storing them in the warehouse. 9

Issues in View Materialization What views should we materialize, and what indexes should we build on the precomputed results? Given a query and a set of materialized views, can we use the materialized views to answer the query? How frequently should we refresh materialized views to make them consistent with the underlying tables? (And how can we do this incrementally?) 10

View Maintenance A View Maintenance policy is a decision about when a view is refreshed. Immediate Refresh: Can be refreshed as part of the transaction that modifies the underlying data tables. (+ Materialized view is always consistent; - updates are slowed) Deferred Refresh: Some time later, in a separate transaction. (- View becomes inconsistent; + can scale to maintain many views without slowing updates. Updates are captured in a log and applied subsequently to the materialised views.) 11

Deferred Maintenance Three flavors: Lazy: Delay refresh until next query on view; then refresh before answering the query. Periodic (Snapshot): Refresh periodically (say once per day). Queries will possibly be answered using outdated version of view tuples. Widely used for warehouse applications. Forced: E.g., Refresh after a fixed number of updates to underlying data tables. 12

Note: In periodic and forced view maintenance queries may see data that is not consistent with the underlying tables. A price to be paid for fast updates and queries. A snapshot (Oracle) is a local materialization of a view on data stored at a master site. 13