CSE 326: Data Structures Lecture #22 Databases and Sorting Alon Halevy Spring Quarter 2001

Agenda Reminisce about Project 3. A bit on graphs. Get excited about Project 4 (short course on databases) Start talking about sorting.

Database Systems Enable you to manage large (huge) amounts of data: –Store the data efficiently –Pose complex queries on the data in a high-level language (e.g., SQL) –Enable concurrent access to the data by many users. –Embed database queries into application programs. The market: mostly relational databases.

Terminology Name Price Category Manufacturer gizmo $19.99 gadgets GizmoWorks Power gizmo $29.99 gadgets GizmoWorks SingleTouch $ photography Canon MultiTouch $ household Hitachi tuples Attribute names

More Terminology Every attribute has an atomic type. Relation Schema: relation name + attribute names + attribute types Relation instance: a set of tuples. Only one copy of any tuple! Database Schema: a set of relation schemas. Database instance: a relation instance for every relation in the schema.

Querying a Database The query language enables performing relational operators: –Selection (select a subset of the tuples from a table) –Projection (select a subset of the columns) –Join (match up two tables on certain attributes) –Union, negation, aggregation, etc., etc. Operations take table(s) as input and produce a table. SQL manual is a very effective doorstop.

Selection Produce a subset of the tuples in a relation which satisfy a given condition Unary operation… returns set with same attributes, but ‘selects’ rows Use and, or, not, >, <… to build condition Find all employees with salary more than $40,000:

Find all employees with salary more than $40,000.

Projection Unary operation, selects columns Eliminates duplicate tuples Example: project social-security number and names.

Join (Natural) Most important, expensive and exciting. Combines two relations, selecting only related tuples Resulting schema has all attributes of the two relations, but one copy of join condition attributes

Step 1 Read the schema (format given). Create the data structure to store tables. Read the data (each table is in a separate file, tuple per line).

Step 2 Read the query. The form is: Select attributes From Tables Where selection conditions, join conditions. Order By: attribute Note: no Cartesian products, may join two tables on more than one attribute. Dirty hack for self joins.

Step 3 Execute the query. Perform all joins (each join creates and intermediate table). Perform selections Perform projections Order the output (if necessary)

Notes on Mechanics Groups of 3-4 students. Send to Maya, Nic and Alon by Monday, the 21 st. Hash join (explained in section yesterday). Grading: demos (15 minutes per group) + 2-page writeup. Dates? You have a lot of freedom in this project. You’ll have to make a lot of choices on your own. Data (about you) Help: all of us + Peter Mork Homework 5 turn-in.

Sorting Given a set of N numbers, put them in order. We’ll see several algorithms for comparison sort: –Insertion sort –Merge sort –Quicksort –Heap sort. How well can we expect to do?? What is the minimum # of comparisons that any algorithm could do.

Decision tree to sort list A,B,C

Max depth of the decision tree How many permutations are there of N numbers? How many leaves does the tree have? What’s the shallowest tree with a given number of leaves? What is therefore the worst running time (number of comparisons) by the best possible sorting algorithm?

Stirling’s approximation