Databases have a tough job. They accept SQL queries from many clients concurrently and execute the queries as efficiently as possible against the data. Processing statements can be an expensive operation but databases are now written in such a way so that this overhead is minimized. However, these optimizations need assistance from the application developers if we are to capitalize on them. This article shows you how the correct use of PreparedStatements can significantly help a database perform these optimizations.
Obviously, don't expect alot of detail here; we'll only examine the aspects important to this article. When a database receives a statement, the database engine first parses the statement and looks for syntax errors. Once the statement is parsed, the database needs to figure out the most efficient way to execute the statement. This can be computationally quite expensive. The database checks what indexes, if any, can help, or whether it should do a full read of all rows in a table. Databases use statistics on the data to figure out what is the best way. Once the query plan is created then it can be executed by the database engine.
It takes CPU power to do the access plan generation. Ideally, if we send the same statement to the database twice, then we'd like the database to reuse the access plan for the first statement. This uses less CPU than if it regenerated the plan a second time.
Databases are tuned to do statement caches. They usually include some kind of statement cache. This cache uses the statement itself as a key and the access plan is stored in the cache with the corresponding statement. This allows the database engine to reuse the plans for statements that have been executed previously. For example, if we sent the database a statement such as "select a,b from t where c = 2", then the computed access plan is cached. If we send the same statement later, the database can reuse the previous access plan, thus saving us CPU power.
Note however, that the entire statement is the key. For example, if we later sent the statement "select a,b from t where c = 3", it would not find an access plan. This is because the "c=3" is different from the cached plan "c=2". So, for example:
Here the cache won't be used. Each iteration of the loop sends a different SQL statement to the database. A new access plan is computed for each iteration and we're basically throwing CPU cycles away using this approach. However, look at the next snippet:
Here it will be much more efficient. The statement sent to the database is parameterized using the '?' marker in the sql. This means every iteration is sending the same statement to the database with different parameters for the "c=?" part. This allows the database to reuse the access plans for the statement and makes the program execute more efficiently inside the database. This basically let's your application run faster or makes more CPU available to users of the database.
Things can get more complicated when we use a J2EE server. Normally, a prepared statement is associated with a single database connection. When the connection is closed, the preparedstatement is discarded. Normally, a fat client application would get a database connection and then hold it for its lifetime. It would also create all prepared statements eagerly or lazily . Eagerly means that they are all created at once when the application starts. Lazily means that they are created as they are used. An eager approach gives a delay when the application starts but once it starts then it performs optimally. A lazy approach gives a fast start but as the application runs, the prepared statements are created when they are first used by the application. This gives an uneven performance until all statements are prepared but the application eventually settles and runs as fast as the eager application. Which is best depends on whether you need a fast start or even performance.
The problem with a J2EE application is that it can't work like this. It only keeps a connection for the duration of the request. This means that it must create the prepared statements every time the request is executed. This is not as efficient as the fat client approach where the prepared statements are created once, rather than on every request. J2EE vendors have noticed this and designed connection pooling to avoid this performance disadvantage.
When the J2EE server gives your application a connection, it isn't giving you the actual connection; you're getting a wrapper. You can verify this by looking at the name of the class for the connection you are given. It won't be a database JDBC connection, it'll be a class created by your application server. Normally, if you called close on a connection then the jdbc driver closes the connection. We want the connection to be returned to the pool when close is called by a J2EE application. We do this by making a proxy jdbc connection class that looks like a real connection. It has a reference to the actual connection. When we invoke any method on the connection then the proxy forwards the call to the real connection. But, when we call methods such as close instead of calling close on the real connection, it simply returns the connection to the connection pool and then marks the proxy connection as invalid so that if it is used again by the application we'll get an exception.
Wrapping is very useful as it also helps J2EE application server implementers to add support for prepared statements in a sensible way. When an application calls Connection.prepareStatement, it is returned a PreparedStatement object by the driver. The application then keeps the handle while it has the connection and closes it before it closes the connection when the request finishes. However, after the connection is returned to the pool and later reused by the same, or another application, , then ideally, we want the same PreparedStatement to be returned to the application.
J2EE PreparedStatement Cache is implemented using a cache inside the J2EE server connection pool manager. The J2EE server keeps a list of prepared statements for each database connection in the pool. When an application calls prepareStatement on a connection, the application server checks if that statement was previously prepared. If it was, the PreparedStatement object will be in the cache and this will be returned to the application. If not, the call is passed to the jdbc driver and the query/preparedstatement object is added in that connections cache.
We need a cache per connection because that's the way jdbc drivers work. Any preparedstatements returned are specific to that connection.
If we want to take advantage of this cache, the same rules apply as before. We need to use parameterized queries so that they will match ones already prepared in the cache. Most application servers will allow you to tune the size of this prepared statement cache.
In conclusion, we should use parameterized queries with prepared statements. This reduces the load on the database by allowing it to reuse access plans that were already prepared. This cache is database-wide so if you can arrange for all your applications to use similar parameterized SQL, you will improve the efficiency of this caching scheme as an application can take advantage of prepared statements used by another application. This is an advantage of an application server because logic that accesses the database should be centralized in a data access layer (either an OR-mapper, entity beans or straight JDBC).
Finally, the correct use of prepared statements also lets you take advantage of the prepared statement cache in the application server. This improves the performance of your application as the application can reduce the number of calls to the JDBC driver by reusing a previous prepared statement call. This makes it competitive with fat clients efficiency-wise and removes the disadvantage of not being able to keep a dedicated connection.
If you use parameterized prepared statements, you improve the efficiency of the database and your application server hosted code. Both of these improvements will allow your application to improve its performance.