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There is a fundamental difference in the way you access data in Java and in a relational database. In Java, when you access a user s billing information, you call aUser.getBillingDetails().getAccountNumber() or something similar. This is the most natural way to access object-oriented data, and it s often described as walking the object network. You navigate from one object to another, following pointers between instances. Unfortunately, this isn t an efficient way to retrieve data from an SQL database. The single most important thing you can do to improve the performance of data access code is to minimize the number of requests to the database. The most obvious way to do this is to minimize the number of SQL queries. (Of course, there are other more sophisticated ways that follow as a second step.) Therefore, efficient access to relational data with SQL usually requires joins between the tables of interest. The number of tables included in the join when retrieving data determines the depth of the object network you can navigate in memory. For example, if you need to retrieve a User and aren t interested in the user s billing information, you can write this simple query:

Quality of Service (QoS) sion on a network. A set of standards for assuring the quality of data transmis

On the other hand, if you need to retrieve a User and then subsequently visit each of the associated BillingDetails instances (let s say, to list all the user s credit cards), you write a different query:

SELECT * FROM Test.TestTran WHERE Col1 = 1; /* Still returns the 1 row with the value 1 for the Col2 column. */

select * from USERS u left outer join BILLING_DETAILS bd on bd.USER_ID = u.USER_ID where u.USER_ID = 123

UPDATE Test.TestTran SET Col2 = 10 WHERE Col1 = 1; /* Sets the Col2 column of both rows to the value 10. */ SELECT * FROM Test.TestTran WHERE Col1 = 1; /* Returns 2 rows with the value 10 for the Col2 column in both rows. */

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As you can see, to efficiently use joins you need to know what portion of the object network you plan to access when you retrieve the initial User this is before you start navigating the object network! On the other hand, any object persistence solution provides functionality for fetching the data of associated objects only when the object is first accessed. However, this piecemeal style of data access is fundamentally inefficient in the context of a relational database, because it requires executing one statement for each node or collection of the object network that is accessed. This is the dreaded n+1 selects problem. This mismatch in the way you access objects in Java and in a relational database is perhaps the single most common source of performance problems in Java applications. There is a natural tension between too many selects and too big

Queue Length A performance counter that measures the number of instructions that are waiting to be processed by an object such as the Processor or Physical Disk. If the Queue Length is greater than 2 or 3 for an extended period of time, it is a reflection that the system s resources are not sufficient for the demands being placed on that system.

selects, which retrieve unnecessary information into memory. Yet, although we ve been blessed with innumerable books and magazine articles advising us to use StringBuffer for string concatenation, it seems impossible to find any advice about strategies for avoiding the n+1 selects problem. Fortunately, Hibernate provides sophisticated features for efficiently and transparently fetching networks of objects from the database to the application accessing them. We discuss these features in chapters 13, 14, and 15.

SELECT * FROM Test.TestTran WHERE Col1 = 1; /* Still returns the 1 row with the value 1 for the Col2 column. */

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