1. Physical Storage Indexes Partitions Materialized views March 2004
Ron McFadyen

2. All DBMSs provide variations of b-trees for indexing B-tree index
Indexes
All DBMSs provide variations of b-trees for indexing
B-tree index
Bitmapped index
Bitmapped join index
A data warehousing DBMS will likely provide these, or variations, on these
March 2004
Ron McFadyen

3. Most used access structure in database systems.
B-tree structures
Most used access structure in database systems.
There are b-trees, b+-trees, b*-trees, etc.
B-trees and their variations are:
balanced
very good in environments with mixed reading and writing operations, concurrency, exact searches and range searches
provide excellent performance when used to find a few rows in big tables
are studied in
March 2004
Ron McFadyen

4. Consider the following Customer table
Bitmapped index
Consider the following Customer table
Cust_id
gender
province
phone 22 M Ab
(403) 44 M Mb
(204) 77 F Sk
(306) 88 F Sk
(306) 99 M Mb
(204)
Note that Mb appears in rows 2, 5
Note that Sk appears in rows 3, 4; Ab in row 1
Note that M appears in rows 1, 2, 5; F in rows 3, 4
March 2004
Ron McFadyen

5. A bitmapped index comprises a collection of bit arrays.
There is one bit array for each distinct value of the indexed attribute.
Useful for low-cardinality attributes
Since gender has two values there are two bit arrays. Each bit array has the same number of bits as there are rows in the table.
If we construct a bitmapped index for gender we would have two bit arrays of 5 bits each: M F
March 2004
Ron McFadyen

6. Bitmapped index
If we construct a bitmapped index for Province we would have three bit arrays of 5 bits each: Ab Mb Sk
March 2004
Ron McFadyen

7. Select Sum(s.amount) From Sales s Inner Join Customer c On ( … )
Bitmapped index
Consider a query
Select Sum(s.amount) From Sales s Inner Join Customer c On ( … )
where c.gender =M
and c.province = Mb
The database query processor could choose to AND the arrays for gender=M and province=Mb
The result indicates that rows 2 and 5 of Customer satisfy the query; only these two rows need to be joined to Sales M Mb
Result
March 2004
Ron McFadyen

8. Bitmapped Join Index
In general, a join index is a structure containing index entries (attribute value, row pointers), where the attribute values are in one table, and the row pointers are to related rows in another table
Consider
Customer
Sales
Date
March 2004
Ron McFadyen

9. Cust_id Cust_id Store_id Date_id
Join Index
Customer
Cust_id
gender
province
phone 22 M Ab
(403) 44 M Mb
(204) 77 F Sk
(306) 88 F Sk
(306) 99 M Mb
(204)
Sales
Cust_id
Store_id
Date_id
Amount
row 1 22 1 90
100 2 44 2 7
150 3 22 2 33 50 4 44 3 55 50 5 99 3 55 25
March 2004
Ron McFadyen

10. Bitmapped Join Index
In some database systems, a bitmapped join index can be created which indexes Sales by an attribute of customer: home province. Here is SQL for the index: CREATE BITMAP INDEX cust_sales_bji ON Sales(Customer.province) FROM Sales, Customer WHERE Sales.cust_id = Customer.cust_id;
March 2004
Ron McFadyen

11. Bitmapped Join Index
There are three province values in Customer. The join index will have three entries where each has a province value and a bitmap: Mb Ab Sk
The bitmap index shows that rows 2, 4, 5 of the Sales fact table are rows for customers with province = Mb
The bitmap index shows that rows 1, 3 of the Sales fact table are rows for customers with province = Ab
The bitmap index shows that no rows of the Sales fact table are rows for customers with province = Sk
March 2004
Ron McFadyen

12. Bitmapped Join Index
The bitmap join index could be used to evaluate the following query. In this query, the CUSTOMER table will not even be accessed; the query is executed using only the bitmap join index and the sales table SELECT SUM(Sales.dollar_amount) FROM Sales, Customer WHERE Sales.cust_id = Customer.cust_id AND Customer.province = Mb;
The bitmap index will show that rows 2, 4, 5 of the Sales fact table are rows for customers with province = M
March 2004
Ron McFadyen

13. Often the attribute is a date.
Partitions
Physical storage can be organized in partitions where the value of an attribute is used to determine where a row is placed.
Often the attribute is a date.
In warehousing, dates are often used to restrict a query.
Archiving older data is facilitated since one only has to drop the oldest partition.
March 2004
Ron McFadyen

14. Materialized Views
An MV is a view where the result set is pre-computed and stored in the database
Periodically an MV must be re-computed to account for updates to its source tables
MVs represent a performance enhancement to a DBMS as the result set is immediately available when the view is referenced in a SQL statement
MVs are used in some cases to provide summary or aggregates for data warehousing transparently to the end-user
Query optimization is a DBMS feature that may re-write an SQL statement supplied by a user.
March 2004
Ron McFadyen