Berkeley DB Reference Guide: Locking Subsystem
Description: Berkeley DB: An embedded database programmatic toolkit.
Keywords: embedded,database,programmatic,toolkit,b+tree,btree,hash,hashing,transaction,transactions,locking,logging,access method,access methods,java,C,C++

### Berkeley DB Reference Guide: Locking Subsystem |

# Page locks

Under normal operation, the access methods use page locking. The pagesize of a database is set when the database is created and may be specified by calling the DB->set_pagesize function. If not specified, the Berkeley DB package tries to select a pagesize that will provide the best I/O performance by setting the page size equal to the block size of the underlying file system.

In the Btree access method, Berkeley DB uses a technique called lock coupling to improve concurrency. The traversal of a Btree requires reading a page, searching that page to determine which page to search next and then repeating this process on the next page. Once a page has been searched, it will never be accessed again for this operation, unless a page split is required. To improve concurrency in the tree, once the next page to read/search has been determined, that page is locked, and then atomically (i.e., without relinquishing control of the lock manager) the original page lock is released.

As the Recno access method is built upon Btree, it too uses lock coupling for read operations. However, as the Recno access method must maintain a count of records on its internal pages, it cannot lock couple during write operations. Instead, it retains write locks on all internal pages during every update operation. For this reason, it is not possible to have high concurrency in the Recno access method in the presence of write operations.

The Queue access method only uses short term page locks. That is, a page lock is released prior to requesting another page lock. Record locks are used for transaction isolation. The provides a high degree of concurrency for write operations. A metadata page is used to keep track of the head and tail of the queue. This page is never locked during other locking or I/O operations.

The Hash access method does not have such traversal issues, but because it implements dynamic hashing, it must always refer to its metadata while computing a hash function. This metadata is stored on a special page in the hash database. This page must therefore be read locked on every operation. Fortunately, it need only be write locked when new pages are allocated to the file, which happens in three cases: 1) a hash bucket becomes full and needs to split, 2) a key or data item is too large to fit on a normal page, and 3) the number of duplicate items for a fixed key becomes sufficiently large that they are moved to an auxiliary page. In this case, the access method must obtain a write lock on the metadata page, thus requiring that all readers be blocked from entering the tree until the update completes.

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