ADVANCED TOPICS IN RELATIONAL DATABASES Spring 2011 Instructor: Hassan Khosravi

4.2 AUTHORIZATION

4.3 Database Authorization Make sure users see only the data they are supposed to see. Guard the database against modifications by malicious users. Users have privileges Can only operate on data for which they are authorized Select on R Insert on R Update on R Delete on R

4.4 Example Apply(dec), Select(Sid) Student select(SID,GPA)

4.5

4.6 How can we give the following privilege Select students info for Stanford applications only Delete Berkeley applications only

4.7 Obtaining Privileges Relation creator is owner Owner has all privileges and may grant privileges Grant privs on R to users  [with grant option]

4.8 Revoking Privileges Cascade: also revoke privileges granted from privileges being revoked transitively, unless also granted from another source Restrict: disallow if cascade would revoke any other privileges

4.9 ON-LINE ANALYTICAL PROCESSING (OLAP)

4.10 Two broad types of database activities OLTP: Online Transaction Processing  Short transactions  Simple queries  Touch small portion of data  Frequent updates OLAP: Online Analytical Processing  Long transactions  Complex queries  Touch large portions of data  Infrequent updates

4.11 Data warehousing Bring data from operational OLPT sources into a single warehouse for OLAP analysis Decision Support System Data warehouse tuned for OLAP

4.12 Star Schema Fact table (relationships) Updated frequently, very large  Sales transaction, course enrollment Dimension tables (entities, objects) Stores, items, customers Students, courses

4.13 Example

4.14 Performance Inherently very slow:  Special indexes  Extensive use of materialized views

4.15 DATA CUBES

4.16 Multi-dimensional OLAP Data Cube Dimension data form axes of Cube Fact data in cells Item Stores Customers

4.17 Assuming one quantity for that Item Stores Customers Qty and price for I32, C4, s17

4.18 Usually have defined aggregate functions that are meaningful Sum(qty * price) Item Stores Customers Aggregate over all items for C5, s11

4.19 Usually have defined aggregate functions that are meaningful Sum(qty * price) Item Stores Customers Aggregate over all stores for I 61, C5, C21

4.20 Usually have defined aggregate functions that are meaningful Sum(qty * price) Item Stores Customers Aggregate over all customers for I 5, s13

4.21 Usually have defined aggregate functions that are meaningful Sum(qty * price) Item Stores Customers Aggregate over all customers and Items for s2 Aggregate over all stores and Items for c63 Aggregate over all stores and customers for I 52

4.22 Usually have defined aggregate functions that are meaningful Sum(qty * price) Item Stores Customers Full aggregation

4.23 Example

4.24

4.25 Drill Down Add for category to the group by and selection

4.26 Roll Up