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Optimization step by step First, enable the Hibernate SQL log You should also be prepared to read, understand, and evaluate SQL queries and their performance characteristics for your specific database schema: Will a single outer-join operation be faster than two selects Are all the indexes used properly, and what is the cache hit-ratio inside the database Get your DBA to help you with that performance evaluation; only he has the knowledge to decide what SQL execution plan is the best (If you want to become an expert in this area, we recommend the book SQL Tuning by Dan Tow, [Tow, 2003]) The two configuration properties hibernateformat_sql and hibernate use_sql_comments make it a lot easier to read and categorize SQL statements in your log files Enable both during optimization.

Several Ant tasks support the <mapper> datatype, allowing file names to be mapped to one or more corresponding files. Section 3.10 discusses the built-in mappers in detail. In almost all cases, the provided mappers are sufficient, but you may find a need to write a custom one. In fact, we found such a need during the writing of this book, and we will use it as an example. We wanted to speed up our builds that incorporated unit tests, but the <junit> task simply reruns all tests each time it is encountered. By using <uptodate> to compare timestamps on the unit test results with the actual Java source files, we are able to bypass testing if they have already been run. The problem encountered was that the Java source files are in a directory structure based on package names, while the unit test results are written to a flat directory structure with the dotted package name used in the XML file name. Section 4.8 provides more details on this short-circuiting technique. We developed the package mapper to solve this problem (which is now part of Ant, as of version 1.5), shown in listing 20.4.

Next, execute use case by use case of your application and note how many and what SQL statements are executed by Hibernate A use case can be a single screen in your web application or a sequence of user dialogs This step also involves collecting the object retrieval methods you use in each use case: walking the object links, retrieval by identifier, HQL, and Criteria queries Your goal is to bring down the number (and complexity) of SQL statements for each use case by tuning the default fetch plan and fetching strategy in metadata It s time to define your fetch plan Everything is lazy loaded by default Consider switching to lazy="false" (or FetchTypeEAGER) on many-to-one, one-to-one, and (sometimes) collection mappings The global fetch plan defines the objects that are always eagerly loaded.

Optimize your queries and enable eager fetching if you need eagerly loaded objects not globally, but in a particular procedure a use case only Once the fetch plan is defined and the amount of data required by a particular use case is known, optimize how this data is retrieved You may encounter two common issues:.

public class PackageNameMapper extends GlobPatternMapper { /** * Returns the part of the given string that matches the * in the * "from" pattern replacing file separators with dots * *@param name Source filename *@return Replaced variable part */ protected String extractVariablePart(String name) { String var = name.substring(prefixLength, name.length() - postfixLength); return var.replace(File.separatorChar, '.'); } }

The SQL statements use join operations that are too complex and slow. First optimize the SQL execution plan with your DBA. If this doesn t solve the problem, remove fetch="join" on collection mappings (or don t set it in the first place). Optimize all your many-to-one and one-to-one associations by considering if they really need a fetch="join" strategy or if the associated object should be loaded with a secondary select. Also try to tune with the global hibernate.max_fetch_depth configuration option, but keep in mind that this is best left at a value between 1 and 5.

A custom mapper must implement the org.apache.tools.ant.util.FileNameMapper interface, which glob mapper class does. We subclass the GlobPatternMapper to inherit the asterisk (*) pattern-matching capability. By overriding its extractVariablePart method, all that was needed was to replace file separators with dots. The FileNameMapper interface s primary method has this signature: