How to Improve Database Connectivity With the Data Tools Platform. John Graham (Sybase Data Tooling) Brian Payton (IBM Information Management)

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1 How to Improve Database Connectivity With the Data Tools Platform John Graham (Sybase Data Tooling) Brian Payton (IBM Information Management) 1

2 Agenda DTP Overview Creating a Driver Template Creating a Connection Profile Customizing a Database Definition Extending the SQL Query Parser Conclusion 2

3 DTP Structure Top level project at Eclipse Contains four subprojects Model Base Connectivity SQL Dev Tools Enablement 3

4 Model Base Domain models for data centric applications using EMF Currently SQL SQL Query SQL XML Query Database Definition 4

5 Connectivity Create and manage connections to data sources Frameworks Driver Management Connection Management ODA Data Source Explorer 5

6 SQL Dev Tools Developer centric SQL tools Frameworks Editor Results view SQL Query Parser Tools SQL Editor Script history Results 6

7 Enablement For specialization of DTP to specific data sources Examples Specific databases XML data source Other data sources? 7

8 Support for PostgreSQL 8.x Can define generic driver template Can connect using JDBC connection profile Can use SQL Dev with this connection profile 8

9 Demonstration: Connecting to PostgreSQL 9

10 Limitations Not intuitive for driver and connection profile definitions Not all data types correct Not all database objects appear in DSE We will address the first two today 10

11 Driver Template Specify reasonable defaults for PostgreSQL 8.x Reuse generic driver template Make the choice obvious in the driver template list 11

12 Demonstration: Creating a Driver Template 12

13 Connection Profile Simple reuse of the generic JDBC connection profile (for now) Responsibilities Manage connection on request Provide meta-data about connection 13

14 Demonstration: Creating a Connection Profile 14

15 Further (future) specializations Specialized class loading Specialized content for DSE Contribute to SQL Dev extension points 15

16 Data Type Problems Why is this happening? Specialize database definition Modify XMI vendor file Based on generic version Add new names for data types 16

17 Demonstration: Specialized DB Definition 17

18 Using the DB Customization Specialized types added (Future) Support all data types in a similar manner 18

19 Beyond Connecting Now that you have a (customized) connection to your database, what can you do with it? All kinds of things, but here are some important ones: Retrieve data Update data Retrieving and updating data typically requires creating SQL queries 19

20 SQL Facts of Life Each database type has its own flavor of SQL No database really implements the ISO SQL standard Each has missing features, added non-standard features, and some features present but just different This creates a problem for database tools! Need a way to create tools that can handle the differences 20

21 DTP SQL Query Parser DTP includes a SQL Query parser framework and example implementation Parses SQL DML statements: SELECT, INSERT, UPDATE, DELETE Based on IBM LALR Parser Generator (LPG) Output of parser is instance of SQL Query Model Both parser and model are designed to be customized and extended 21

22 Example: PostgreSQL PostgreSQL has lots of interesting features and differences from standard SQL. Here are two we will use for our example extension: Additional table join types Dollar-quoted string constants 22

23 PostgreSQL: Additional table join types PostgreSQL supports many table join types, including some unusual ones: CROSS JOIN NATURAL JOIN These are in ISO SQL but are not in many other DB s, and are not included in the base SQL Query model and parser Will illustrate how to extend the SQL Query model and parser 23

24 PostgreSQL: Dollar-quoted string literals PostgreSQL has an unusual alternative syntax for specifying string literals in SQL $$string literal here$$ Can include any characters inside the literal (avoids the need to double single quotes) Typically used to quote SQL code in procedure and function definitions Will illustrate how to extend the SQL lexer 24

25 Task Overview: Extending the Model 1. Create plugin for model extension 2. Define the model extension 3. Generate model code (EMF) 4. Extend the source formatter 25

26 Demonstration: Extending the SQL Query Model 26

27 Task Overview: Extending the Parser 1.Create plugin for parser extension 2.Copy and modify LPG templates 3.Define LPG command runner 4.Add and override parser rules 5.Generate parser code 27

28 Demonstration: Extending the SQL Query Parser 28

29 Task Overview: Extending the Lexer In LPG, the lexer is a specialized parser, so steps are similar to the parser steps 1. Copy LPG lexer template 2. Modify grammar rules in lexer 3. Generate lexer code 29

30 Demonstration: Extending the SQL Lexer 30

31 Putting it all together Now have a SQL parser and model that work together. Can be used for: Query analysis Query building Query syntax checking 31

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