JDBC and Java Access to DBMS & Introduction to Data Warehouses

1. JDBC and Java Access to DBMS&Introduction to Data Warehouses University of California, Berkeley School of Information IS 257: Database Management

2. Review: Object-Relational DBMS OR features in Oracle OR features in PostgreSQL Extending OR databases (examples from PostgreSQL) Java and JDBC Introduction to Data Warehouses Lecture Outline

3. Object-Relational DBMS OR features in Oracle OR features in PostgreSQL Extending OR databases (examples from PostgreSQL) Java and JDBC Introduction to Data Warehouses Lecture Outline

4. Object Relational Data Model • Class, instance, attribute, method, and integrity constraints • OID per instance • Encapsulation • Multiple inheritance hierarchy of classes • Class references via OID object references • Set-Valued attributes • Abstract Data Types

5. Object Relational Extended SQL (Illustra) • CREATE TABLE tablename {OF TYPE Typename}|{OF NEW TYPE typename} (attr1 type1, attr2 type2,…,attrn typen) {UNDER parent_table_name}; • CREATE TYPE typename (attribute_name type_desc, attribute2 type2, …, attrn typen); • CREATE FUNCTION functionname (type_name, type_name) RETURNS type_name AS sql_statement

6. Object-Relational SQL in ORACLE • CREATE (OR REPLACE) TYPE typename AS OBJECT (attr_name, attr_type, …); • CREATE TABLE OF typename;

7. Example • CREATE TYPE ANIMAL_TY AS OBJECT (Breed VARCHAR2(25), Name VARCHAR2(25), Birthdate DATE); • Creates a new type • CREATE TABLE Animal of Animal_ty; • Creates “Object Table”

8. Constructor Functions • INSERT INTO Animal values (ANIMAL_TY(‘Mule’, ‘Frances’, TO_DATE(‘01-APR-1997’, ‘DD-MM-YYYY’))); • Insert a new ANIMAL_TY object into the table

9. PostgreSQL Classes • The fundamental notion in Postgres is that of a class, which is a named collection of object instances. Each instance has the same collection of named attributes, and each attribute is of a specific type. Furthermore, each instance has a permanent object identifier (OID) that is unique throughout the installation. Because SQL syntax refers to tables, we will use the terms table and class interchangeably. Likewise, an SQL row is an instance and SQL columns are attributes.

10. Creating a Class • You can create a new class by specifying the class name, along with all attribute names and their types: CREATE TABLE weather ( city varchar(80), temp_lo int, -- low temperature temp_hi int, -- high temperature prcp real, -- precipitation date date );

11. PostgreSQL • Postgres can be customized with an arbitrary number of user-defined data types. Consequently, type names are not syntactical keywords, except where required to support special cases in the SQL92 standard. • So far, the Postgres CREATE command looks exactly like the command used to create a table in a traditional relational system. However, we will presently see that classes have properties that are extensions of the relational model.

12. Inheritance CREATE TABLE cities ( name text, population float, altitude int -- (in ft) ); CREATE TABLE capitals ( state char(2) ) INHERITS (cities);

13. Inheritance • In Postgres, a class can inherit from zero or more other classes. • A query can reference either • all instances of a class • or all instances of a class plus all of its descendants

14. Non-Atomic Values - Arrays • The preceding SQL command will create a class named SAL_EMP with a text string (name), a one-dimensional array of int4 (pay_by_quarter), which represents the employee's salary by quarter and a two-dimensional array of text (schedule), which represents the employee's weekly schedule • Now we do some INSERTSs; note that when appending to an array, we enclose the values within braces and separate them by commas.

15. PostgreSQL Extensibility • Postgres is extensible because its operation is catalog-driven • RDBMS store information about databases, tables, columns, etc., in what are commonly known as system catalogs. (Some systems call this the data dictionary). • One key difference between Postgres and standard RDBMS is that Postgres stores much more information in its catalogs • not only information about tables and columns, but also information about its types, functions, access methods, etc. • These classes can be modified by the user, and since Postgres bases its internal operation on these classes, this means that Postgres can be extended by users • By comparison, conventional database systems can only be extended by changing hardcoded procedures within the DBMS or by loading modules specially-written by the DBMS vendor.

16. Rules System • CREATE RULE name AS ON event TO object [ WHERE condition ] DO [ INSTEAD ] [ action | NOTHING ] • Rules can be triggered by any event (select, update, delete, etc.)

17. Views as Rules • Views in Postgres are implemented using the rule system. In fact there is absolutely no difference between a CREATE VIEW myview AS SELECT * FROM mytab; • compared against the two commands CREATE TABLE myview (same attribute list as for mytab); CREATE RULE "_RETmyview" AS ON SELECT TO myview DO INSTEAD SELECT * FROM mytab;

18. Extensions to Indexing • Access Method extensions in Postgres • GiST: A Generalized Search Trees • Joe Hellerstein, UC Berkeley

19. Indexing in OO/OR Systems • Quick access to user-defined objects • Support queries natural to the objects • Two previous approaches • Specialized Indices (“ABCDEFG-trees”) • redundant code: most trees are very similar • concurrency control, etc. tricky! • Extensible B-trees & R-trees (Postgres/Illustra) • B-tree or R-tree lookups only! • E.g. ‘WHERE movie.video < ‘Terminator 2’

20. GiST Approach • A generalized search tree. Must be: • Extensible in terms of queries • General (B+-tree, R-tree, etc.) • Easy to extend • Efficient (match specialized trees) • Highly concurrent, recoverable, etc.

21. GiST Applications • New indexes needed for new apps... • find all supersets of S • find all molecules that bind to M • your favorite query here (multimedia?) • ...and for new queries over old domains: • find all points in region from 12 to 2 o’clock • find all text elements estimated relevant to a query string

22. Review Object-Relational DBMS OR features in Oracle OR features in PostgreSQL Extending OR databases (examples from PostgreSQL) Java and JDBC Introduction to Data Warehouses Lecture Outline

23. Java and JDBC • Java is probably the high-level language used in instruction and development today one of the earliest “enterprise” additions to Java was JDBC • JDBC is an API that provides a mid-level access to DBMS from Java applications • Intended to be an open cross-platform standard for database access in Java • Similar in intent to Microsoft’s ODBC

24. JDBC Architecture • The goal of JDBC is to be a generic SQL database access framework that works for any database system with no changes to the interface code Java Applications JDBC API JDBC Driver Manager Driver Driver Driver Oracle MySQL Postgres

25. JDBC Resultset Resultset Resultset Statement PreparedStatement CallableStatement Connection Application DriverManager Oracle Driver ODBC Driver Postgres Driver Oracle DB ODBC DB Postgres DB • Provides a standard set of interfaces for any DBMS with a JDBC driver – using SQL to specify the databases operations.

26. JDBC Simple Java Implementation import java.sql.*; import oracle.jdbc.*; public class JDBCSample { public static void main(java.lang.String[] args) { try { // this is where the driver is loaded //Class.forName("jdbc.oracle.thin"); DriverManager.registerDriver(new OracleDriver()); } catch (SQLException e) { System.out.println("Unable to load driver Class"); return; }

27. JDBC Simple Java Impl. try { //All DB access is within the try/catch block... // make a connection to ORACLE on Dream Connection con = DriverManager.getConnection( "jdbc:oracle:thin:@dream.sims.berkeley.edu:1521:dev", “mylogin", “myoraclePW"); // Do an SQL statement... Statement stmt = con.createStatement(); ResultSet rs = stmt.executeQuery("SELECT NAME FROM DIVECUST");

28. JDBC Simple Java Impl. // show the Results... while(rs.next()) { System.out.println(rs.getString("NAME")); } // Release the database resources... rs.close(); stmt.close(); con.close(); } catch (SQLException se) { // inform user of errors... System.out.println("SQL Exception: " + se.getMessage()); se.printStackTrace(System.out); } } }

29. JDBC • Once a connection has been made you can create three different types of statement objects • Statement • The basic SQL statement as in the example • PreparedStatement • A pre-compiled SQL statement • CallableStatement • Permits access to stored procedures in the Database

30. JDBC Resultset methods • Next() to loop through rows in the resultset • To access the attributes of each row you need to know its type, or you can use the generic “getObject()” which wraps the attribute as an object

31. JDBC “GetXXX()” methods

32. JDBC GetXXX() Methods

33. JDBC GetXXX() Methods

34. Large Object Handling • Large binary databytes can be read from a resultset as streams using: • getAsciiStream() • getBinaryStream() • getUnicodeStream() ResultSet rs = stmt.executeQuery(“SELECT IMAGE FROM PICTURES WHERE PID = 1223”)); if (rs.next()) { BufferedInputStream gifData = new BufferedInputSteam( rs.getBinaryStream(“IMAGE”)); byte[] buf = new byte[4*1024]; // 4K buffer int len; while ((len = gifData.read(buf,0,buf.length)) != -1) { out.write(buf, 0, len); } }

35. JDBC Metadata • There are also methods to access the metadata associated with a resultSet • ResultSetMetaData rsmd = rs.getMetaData(); • Metadata methods include… • getColumnCount(); • getColumnLabel(col); • getColumnTypeName(col)

36. JDBC access to MySQL • The basic JDBC interface is the same, the only differences are in how the drivers are loaded public class JDBCTestMysql { public static void main(java.lang.String[] args) { try { // this is where the driver is loaded Class.forName("com.mysql.jdbc.Driver").newInstance(); } catch (InstantiationException i) { System.out.println("Unable to load driver Class"); return; } catch (ClassNotFoundException e) { System.out.println("Unable to load driver Class"); …

37. JDBC for MySQL try { //All DB access is within the try/catch block... // make a connection to MySQL on Dream Connection con = DriverManager.getConnection( "jdbc:mysql://localhost/ (this is really one line) MyDatabase?user=MyLogin&password=MySQLPW"); // Do an SQL statement... Statement stmt = con.createStatement(); ResultSet rs = stmt.executeQuery("SELECT NAME FROM DIVECUST"); • Otherwise everything is the same as in the Oracle example • For connecting to the machine you are running the program on, you can use “localhost” instead of the machine name

38. Demo – JDBC for MySQL • Demo of JDBC code on Harbinger • Code will be made available on class web site

39. Review Object-Relational DBMS OR features in Oracle OR features in PostgreSQL Extending OR databases (examples from PostgreSQL) Java and JDBC Introduction to Data Warehouses Lecture Outline

40. Overview • Data Warehouses and Merging Information Resources • What is a Data Warehouse? • History of Data Warehousing • Types of Data and Their Uses

41. Problem: Heterogeneous Information Sources “Heterogeneities are everywhere” Personal Databases World Wide Web Scientific Databases Digital Libraries • Different interfaces • Different data representations • Duplicate and inconsistent information Slide credit: J. Hammer

42. Problem: Data Management in Large Enterprises • Vertical fragmentation of informational systems (vertical stove pipes) • Result of application (user)-driven development of operational systems Sales Planning Suppliers Num. Control Stock Mngmt Debt Mngmt Inventory ... ... ... Sales Administration Finance Manufacturing ... Slide credit: J. Hammer

43. Goal: Unified Access to Data Integration System World Wide Web Personal Databases Digital Libraries Scientific Databases • Collects and combines information • Provides integrated view, uniform user interface • Supports sharing Slide credit: J. Hammer

44. The Traditional Research Approach • Query-driven (lazy, on-demand) Clients Metadata Integration System . . . Wrapper Wrapper Wrapper . . . Source Source Source Slide credit: J. Hammer

45. Disadvantages of Query-Driven Approach • Delay in query processing • Slow or unavailable information sources • Complex filtering and integration • Inefficient and potentially expensive for frequent queries • Competes with local processing at sources • Hasn’t caught on in industry Slide credit: J. Hammer

46. The Warehousing Approach Clients Data Warehouse Metadata Integration System . . . Extractor/ Monitor Extractor/ Monitor Extractor/ Monitor . . . Source Source Source • Information integrated in advance • Stored in WH for direct querying and analysis Slide credit: J. Hammer

47. Advantages of Warehousing Approach • High query performance • But not necessarily most current information • Doesn’t interfere with local processing at sources • Complex queries at warehouse • OLTP at information sources • Information copied at warehouse • Can modify, annotate, summarize, restructure, etc. • Can store historical information • Security, no auditing • Has caught on in industry Slide credit: J. Hammer

48. Not Either-Or Decision • Query-driven approach still better for • Rapidly changing information • Rapidly changing information sources • Truly vast amounts of data from large numbers of sources • Clients with unpredictable needs Slide credit: J. Hammer

49. Data Warehouse Evolution “Building the DW” Inmon (1992) Data Replication Tools Relational Databases Company DWs 1960 1975 1980 1985 1990 1995 2000 Information- Based Management Data Revolution “Prehistoric Times” “Middle Ages” TIME PC’s and Spreadsheets End-user Interfaces 1st DW Article DW Confs. Vendor DW Frameworks Slide credit: J. Hammer

50. “A Data Warehouse is a subject-oriented, integrated, time-variant, non-volatile collection of data used in support of management decision making processes.” -- Inmon & Hackathorn, 1994: viz. Hoffer, Chap 11 What is a Data Warehouse?