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<title>Berkeley DB Reference Guide: Locking granularity</title>
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<td><b><dl><dt>Berkeley DB Reference Guide:<dd>Locking Subsystem</dl></b></td>
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<p align=center><b>Locking granularity</b></p>
<p>With the exception of the Queue access method, the Berkeley DB access methods
do page-level locking.  The size of pages in a database may be set when
the database is created by calling the <a href="../../api_c/db_set_pagesize.html">DB-&gt;set_pagesize</a> method.  If
not specified by the application, Berkeley DB selects a page size that will
provide the best I/O performance by setting the page size equal to the
block size of the underlying file system.  Selecting a smaller page size
can result in increased concurrency for some applications.</p>
<p>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 the original page lock is released atomically (that is, without
relinquishing control of the lock manager).  When page splits become
necessary, write locks are reacquired.</p>
<p>Because the Recno access method is built upon Btree, it also uses lock
coupling for read operations.  However, because 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.</p>
<p>The Queue access method uses only 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.</p>
<p>The Hash access method does not have such traversal issues, but it must
always refer to its metadata while computing a hash function because it
implements dynamic hashing.  This metadata is stored on a special page
in the hash database.  This page must therefore be read-locked on every
operation.  Fortunately, it needs to be write-locked only when new pages
are allocated to the file, which happens in three cases:</p>
<p><ul type=disc>
<li>a hash bucket becomes full and needs to split
<li>a key or data item is too large to fit on a normal page
<li>the number of duplicate items for a fixed key becomes so large that they
are moved to an auxiliary page
</ul>
<p>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.</p>
<p>Finally, when traversing duplicate data items for a key, the lock on
the key value also acts as a lock on all duplicates of that key.
Therefore, two conflicting threads of control cannot access the same
duplicate set simultaneously.</p>
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