Overflow pages are used to hold a key or data item that cannot fit on a single page. You do not have to do anything to cause overflow pages to be created, other than to store data that is too large for your database's page size. Also, the only way you can prevent overflow pages from being created is to be sure to select a page size that is large enough to hold your database entries.

Because overflow pages exist outside of the normal database structure, their use is expensive from a performance perspective. If you select too small of a page size, then your database will be forced to use an excessive number of overflow pages. This will significantly harm your application's performance.

For this reason, you want to select a page size that is at least large enough to hold multiple entries given the expected average size of your database entries. In BTree's case, for best results select a page size that can hold at least 4 such entries.

You can see how many overflow pages your database is using by using the Db::stat() method, or by examining your database using the db_stat command line utility.

Locking and multi-threaded access to DB databases is built into the product. However, in order to enable the locking subsystem and in order to provide efficient sharing of the cache between databases, you must use an environment. Environments and multi-threaded access are not fully described in this manual (see the Berkeley DB Programmer's Reference Manual for information), however, we provide some information on sizing your pages in a multi-threaded/multi-process environment in the interest of providing a complete discussion on the topic.

If your application is multi-threaded, or if your databases are accessed by more than one process at a time, then page size can influence your application's performance. The reason why is that for most access methods (Queue is the exception), DB implements page-level locking. This means that the finest locking granularity is at the page, not at the record.

In most cases, database pages contain multiple database records. Further, in order to provide safe access to multiple threads or processes, DB performs locking on pages as entries on those pages are read or written.

As the size of your page increases relative to the size of your database entries, the number of entries that are held on any given page also increase. The result is that the chances of two or more readers and/or writers wanting to access entries on any given page also increases.

When two or more threads and/or processes want to manage data on a page, lock contention occurs. Lock contention is resolved by one thread (or process) waiting for another thread to give up its lock. It is this waiting activity that is harmful to your application's performance.

It is possible to select a page size that is so large that your application will spend excessive, and noticeable, amounts of time resolving lock contention. Note that this scenario is particularly likely to occur as the amount of concurrency built into your application increases.

Oh the other hand, if you select too small of a page size, then that that will only make your tree deeper, which can also cause performance penalties. The trick, therefore, is to select a reasonable page size (one that will hold a sizeable number of records) and then reduce the page size if you notice lock contention.

You can examine the number of lock conflicts and deadlocks occurring in your application by examining your database environment lock statistics. Either use the DbEnv::lock_stat() Environment.getLockStats() method, or use the db_stat command line utility. The number of unavailable locks that your application waited for is held in the lock statistic's st_lock_wait field.

Page size can affect how efficient DB is at moving data to and from disk. For some applications, especially those for which the in-memory cache can not be large enough to hold the entire working dataset, IO efficiency can significantly impact application performance.

Most operating systems use an internal block size to determine how much data to move to and from disk for a single I/O operation. This block size is usually equal to the filesystem's block size. For optimal disk I/O efficiency, you should select a database page size that is equal to the operating system's I/O block size.

Essentially, DB performs data transfers based on the database page size. That is, it moves data to and from disk a page at a time. For this reason, if the page size does not match the I/O block size, then the operating system can introduce inefficiencies in how it responds to DB's I/O requests.

For example, suppose your page size is smaller than your operating system block size. In this case, when DB writes a page to disk it is writing just a portion of a logical filesystem page. Any time any application writes just a portion of a logical filesystem page, the operating system brings in the real filesystem page, over writes the portion of the page not written by the application, then writes the filesystem page back to disk. The net result is significantly more disk I/O than if the application had simply selected a page size that was equal to the underlying filesystem block size.

Alternatively, if you select a page size that is larger than the underlying filesystem block size, then the operating system may have to read more data than is necessary to fulfill a read request. Further, on some operating systems, requesting a single database page may result in the operating system reading enough filesystem blocks to satisfy the operating system's criteria for read-ahead. In this case, the operating system will be reading significantly more data from disk than is actually required to fulfill DB's read request.

Page sizing can be confusing at first, so here are some general guidelines that you can use to select your page size.

In general, and given no other considerations, a page size that is equal to your filesystem block size is the ideal situation.

If your data is designed such that 4 database entries cannot fit on a single page (assuming BTree), then grow your page size to accommodate your data. Once you've abandoned matching your filesystem's block size, the general rule is that larger page sizes are better.

The exception to this rule is if you have a great deal of concurrency occurring in your application. In this case, the closer you can match your page size to the ideal size needed for your application's data, the better. Doing so will allow you to avoid unnecessary contention for page locks.