1. CSE 190: Internet E-Commerce Lecture 10: Data Tier

2. Data Tier Rationale –All data will be stored in central location, the database, with no duplication of state. Careful attention will be paid to keeping data access atomic, consistent, isolated, and durable. (ACID) –Database will provide high level access to querying, filtering, and summarizing the data –Common commercial products: Oracle, IBM’s DB2, Microsoft SQL Server –Free products: mysql, PostgresSQL

3. Choosing data tier representation When might a data base be contra- indicated? –Very simple patterns of data access –Loss of data not catastrophic –Low latency an absolute requirement –Examples: Amazon, Yahoo, Hotmail, Google For most sites, a database backed web site is a good idea

4. Relational databases All data is described as relations between one set of facts (a table) and another set of facts Each relation is called a table. Each row (sometimes called a tuple) has a set of fields, such as name, date of birth Each field (column) has a value of some intrinsic DB type (string, integer, date)

5. Primary keys, foreign keys Primary key: A field of a table designated to provide a unique identifier for a specific row of the table Foreign key: A field of a table whose value matches the primary key of another table. From foreign keys, we see relationships between one table and another. Design: primary keys should not encode meaning in their representation

6. Joins A join is the cross product of all the rows of a set of tables. By selecting a subset of the rows of the join that match some criteria, we can answer simple questions about our data. This is the core of the relational model. Two tables Inner Join of two tables Left outer join

7. Schemas By creating several tables, with the appropriate Primary keys, foreign keys, we can model the data needs of our application Database especially suited for representing the relationship between our entities (objects) when the number of rows in our schemas very large compared to the number of schemas

8. SQL A standard mechanism for querying and manipulating relational databases Queries, Changes (DML: Data Manipulation Language) –SELECT id, firstname, lastname, networth from customers where networth > 1000000 –INSERT into customers values( 17, “Alice”, “Crypto”, 400 ) –UPDATE customers SET networth = networth + 1000 Note: Results from a SQL query (SELECT) are a table in their own right, a view of the data. This table may also be used to perform joins against other tables.

9. SQL Schema Manipulation (DDL: Data Definition Language) Example table creation: CREATE TABLE Customers ( CustNo NUMBER(3) NOT NULL, CustName VARCHAR2(30) NOT NULL, Street VARCHAR2(20) NOT NULL, City VARCHAR2(20) NOT NULL, State CHAR(2) NOT NULL, Zip VARCHAR2(10) NOT NULL, Phone VARCHAR2(12), PRIMARY KEY ( CustNo ) );