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Carol McDonald Describes Locking and Concurrency in JPA 2.0

Posted by editor on September 14, 2009 at 9:34 PM PDT

In her lastest Enterprise Tech Tip, Carol McDonald writes about Locking and Concurrency in Java Persistence 2.0. I'm pointing out Carol's article in Java Today, but I'd also like to talk a bit more about what she covers here.

If you haven't done a lot of work with databases, in particular what I'd call "low-level" work on tuning the performance of databases in an enterprise environment, then it's possible that you've never really given much thought to the problems of locking and concurrency. Yet, these are fundamental to the reliablility of database transactions. As Carol says:

Locking is a technique for handling database transaction concurrency. When two or more database transactions concurrently access the same data, locking is used to ensure that only one transaction at a time can change the data.

Sounds simple enough, right? But, it's not quite that simple, because a single method for performing locking may work well under some conditions, and poorly under others. Carol explains:

There are generally two locking approaches: optimistic and pessimistic. Optimistic locking assumes that there will be infrequent conflicts between concurrent transactions, that is, they won't often try to read and change the same data at the same time. In optimistic locking, the objective is to give concurrent transactions a lot of freedom to process simultaneously, but to detect and prevent collisions. Two transactions can access the same data simultaneously. However, to prevent collisions, a check is made to detect any changes made to the data since the data was last read.

Pessimistic locking assumes that transactions will frequently collide. In pessimistic locking, a transaction that reads the data locks it. Another transaction cannot change the data until the first transaction commits the read.

It's all about the likelihood that someone (or some application) that accesses a data element will update the element, and the frequency with which those updates occur with respect to the access times and the total number of updates. If at a given time, 100 people may request access to a data element, but only one of them will seek to update it any time soon, then pessimistic locking is more efficient. Few requests to update the data element are expected, so it is very likely that when that one person chooses to update the element, it won't have changed from what it was before.

Why do we care? Well, locking and unlocking data elements consumes time and processing power. The database application will be able to support fewer concurrent users if the most efficient method for locking and enabling concurrency is not applied.

Carol summarizes locking support in JPA 1.0, and identifies the additional locking support that is implemented in JPA 2.0. For example, JPA 2.0 adds five new lock modes (including the first support for pessimistic locking). The new lock modes are:

  • OPTIMISITIC
  • OPTIMISTIC_FORCE_INCREMENT
  • PESSIMISTIC_READ
  • PESSIMISTIC_WRITE
  • PESSIMISTIC_FORCE_INCREMENT

This post would be too long if I went into the details that differentiate these lock modes, and covered additional details of what's in JPA 2.0. But, of course, I don't have to do that, since you can find it all in Carol's article!

Formally (at least going by its URL address), Carol's Enterprise Tech Tips site is a blog. But, in just about every case, I'd call her entries more full-fledged technology articles than blog posts. They're insightful, well-structured, detailed tutorials on currently relevant topics in enterprise Java software engineering. Always a great read, and an excellent reference on the topic at hand.

Thanks, Carol!


In Java Today, Carol McDonald has published a new Enterprise Tech Tip, Locking and Concurrency in Java Persistence 2.0:

The Java Persistence API (informally referred to as JPA) provides a plain old Java object (POJO)-based persistence model for Java EE and Java SE applications. It handles the details of how relational data is mapped to Java objects, and it standardizes Object/Relational (O/R) mapping. The latest update to JPA, Java Persistence 2.0, adds a number of new features such as additional O/R mapping functionality and new query language capabilities. Another area that has been enhanced in JPA 2.0 is locking and concurrency...

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