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<p>Library Version 18.1.40</p>
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<h2 class="title" style="clear: both"><a id="transapp_tune"></a>Transaction tuning</h2>
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<p>
There are a few different issues to consider when tuning the
performance of Berkeley DB transactional applications. First,
you should review <a class="xref" href="am_misc_tune.html" title="Access method tuning">Access method tuning</a>, as the tuning issues for
access method applications are applicable to transactional
applications as well. The following are additional tuning
issues for Berkeley DB transactional applications:
</p>
<div class="variablelist">
<dl>
<dt>
<span class="term">access method</span>
</dt>
<dd>
Highly concurrent applications should use the
Queue access method, where possible, as it provides
finer-granularity of locking than the other access
methods. Otherwise, applications usually see better
concurrency when using the Btree access method than
when using either the Hash or Recno access
methods.
</dd>
<dt>
<span class="term">record numbers</span>
</dt>
<dd>
Using record numbers outside of the Queue access
method will often slow down concurrent applications as
they limit the degree of concurrency available in the
database. Using the Recno access method, or the Btree
access method with retrieval by record number
configured can slow applications down.
</dd>
<dt>
<span class="term">Btree database size</span>
</dt>
<dd>
When using the Btree access method, applications
supporting concurrent access may see excessive numbers
of deadlocks in small databases. There are two
different approaches to resolving this problem. First,
as the Btree access method uses page-level locking,
decreasing the database page size can result in fewer
lock conflicts. Second, in the case of databases that
are cyclically growing and shrinking, turning off
reverse splits (with <a href="../api_reference/C/dbset_flags.html#dbset_flags_DB_REVSPLITOFF" class="olink">DB_REVSPLITOFF</a>) can leave the
database with enough pages that there will be fewer
lock conflicts.
</dd>
<dt>
<span class="term">read locks</span>
</dt>
<dd>
Performing all read operations outside of
transactions or at <a class="xref" href="transapp_read.html" title="Degrees of isolation">Degrees of isolation</a> can often
significantly increase application throughput. In
addition, limiting the lifetime of non-transactional
cursors will reduce the length of times locks are
held, thereby improving concurrency.
</dd>
<dt>
<span class="term"><a href="../api_reference/C/envset_flags.html#set_flags_DB_DIRECT_DB" class="olink">DB_DIRECT_DB</a>, <a href="../api_reference/C/envlog_set_config.html#log_set_config_DB_LOG_DIRECT" class="olink">DB_LOG_DIRECT</a></span>
</dt>
<dd>
On some systems, avoiding caching in the
operating system can improve write throughput and
allow the creation of larger Berkeley DB
caches.
</dd>
<dt>
<span class="term"><a href="../api_reference/C/dbopen.html#dbopen_DB_READ_UNCOMMITTED" class="olink">DB_READ_UNCOMMITTED</a>, <a href="../api_reference/C/dbcget.html#dbcget_DB_READ_COMMITTED" class="olink">DB_READ_COMMITTED</a></span>
</dt>
<dd>
<p>
Consider decreasing the level of isolation of
transaction using the <a href="../api_reference/C/dbopen.html#dbopen_DB_READ_UNCOMMITTED" class="olink">DB_READ_UNCOMMITTED</a>, or
<a href="../api_reference/C/dbcget.html#dbcget_DB_READ_COMMITTED" class="olink">DB_READ_COMMITTED</a> flags for transactions or
cursors or the <a href="../api_reference/C/dbopen.html#dbopen_DB_READ_UNCOMMITTED" class="olink">DB_READ_UNCOMMITTED</a> flag on
individual read operations. The
<a href="../api_reference/C/dbcget.html#dbcget_DB_READ_COMMITTED" class="olink">DB_READ_COMMITTED</a> flag will release read locks
on cursors as soon as the data page is nolonger
referenced. This is also called <span class="emphasis"><em> degree
2 isolation</em></span>. This will tend to
block write operations for shorter periods for
applications that do not need to have repeatable
reads for cursor operations.
</p>
<p>
The <a href="../api_reference/C/dbopen.html#dbopen_DB_READ_UNCOMMITTED" class="olink">DB_READ_UNCOMMITTED</a> flag will allow read
operations to potentially return data which has
been modified but not yet committed, and can
significantly increase application throughput in
applications that do not require data be
guaranteed to be permanent in the database. This
is also called <span class="emphasis"><em>degree 1
isolation</em></span>, or <span class="emphasis"><em>dirty
reads</em></span>.
</p>
</dd>
<dt>
<span class="term">
<a href="../api_reference/C/dbcget.html#dbcget_DB_RMW" class="olink">DB_RMW</a>
</span>
</dt>
<dd>
If there are many deadlocks, consider using the
<a href="../api_reference/C/dbcget.html#dbcget_DB_RMW" class="olink">DB_RMW</a> flag to immediately acquire write locks when
reading data items that will subsequently be modified.
Although this flag may increase contention (because
write locks are held longer than they would otherwise
be), it may decrease the number of deadlocks that
occur.
</dd>
<dt>
<span class="term"><a href="../api_reference/C/envset_flags.html#set_flags_DB_TXN_WRITE_NOSYNC" class="olink">DB_TXN_WRITE_NOSYNC</a>, <a href="../api_reference/C/envset_flags.html#envset_flags_DB_TXN_NOSYNC" class="olink">DB_TXN_NOSYNC</a></span>
</dt>
<dd>
By default, transactional commit in Berkeley DB
implies durability, that is, all committed operations
will be present in the database after recovery from
any application or system failure. For applications
not requiring that level of certainty, specifying the
<a href="../api_reference/C/envset_flags.html#envset_flags_DB_TXN_NOSYNC" class="olink">DB_TXN_NOSYNC</a> flag will often provide a significant
performance improvement. In this case, the database
will still be fully recoverable, but some number of
committed transactions might be lost after application
or system failure.
</dd>
<dt>
<span class="term">access databases in order</span>
</dt>
<dd>
When modifying multiple databases in a single
transaction, always access physical files and
databases within physical files, in the same order
where possible. In addition, avoid returning to a
physical file or database, that is, avoid accessing a
database, moving on to another database and then
returning to the first database. This can
significantly reduce the chance of deadlock between
threads of control.
</dd>
<dt>
<span class="term">large key/data items</span>
</dt>
<dd>
Transactional protections in Berkeley DB are
guaranteed by before and after physical image logging.
This means applications modifying large key/data items
also write large log records, and, in the case of the
default transaction commit, threads of control must
wait until those log records have been flushed to
disk. Applications supporting concurrent access should
try and keep key/data items small wherever
possible.
</dd>
<dt>
<span class="term">mutex selection</span>
</dt>
<dd>
<p>
During configuration, Berkeley DB selects a
mutex implementation for the architecture.
Berkeley DB normally prefers blocking-mutex
implementations over non-blocking ones. For
example, Berkeley DB will select POSIX pthread
mutex interfaces rather than assembly-code
test-and-set spin mutexes because pthread mutexes
are usually more efficient and less likely to
waste CPU cycles spinning without getting any work
accomplished.
</p>
<p>
For some applications and systems (generally
highly concurrent applications on large
multiprocessor systems), Berkeley DB makes the
wrong choice. In some cases, better performance
can be achieved by configuring with the
<a href="../installation/build_unix_conf.html#build_unix_conf.--with-mutex" class="olink">--with-mutex</a> argument and selecting a different
mutex implementation than the one selected by
Berkeley DB. When a test-and-set spin mutex
implementation is selected, it may be useful to
tune the number of spins made before yielding the
processor and sleeping. This may be particularly
beneficial for systems containing several
hyperthreaded processor cores. For more
information, see the <a href="../api_reference/C/mutexset_tas_spins.html" class="olink">DB_ENV->mutex_set_tas_spins()</a> method.
</p>
<p>
Finally, Berkeley DB may put multiple mutexes
on individual cache lines. When tuning Berkeley DB
for large multiprocessor systems, it may be useful
to tune mutex alignment using the <a href="../api_reference/C/mutexset_align.html" class="olink">DB_ENV->mutex_set_align()</a>
method.
</p>
</dd>
<dt>
<span class="term">
<a href="../installation/build_unix_conf.html#build_unix_conf.--enable-posixmutexes" class="olink">--enable-posix-mutexes</a>
</span>
</dt>
<dd>
By default, the Berkeley DB library will only
select the POSIX pthread mutex implementation if it
supports mutexes shared between multiple processes. If
your application does not share its database
environment between processes and your system's POSIX
mutex support was not selected because it did not
support inter-process mutexes, you may be able to
increase performance and transactional throughput by
configuring with the <a href="../installation/build_unix_conf.html#build_unix_conf.--enable-posixmutexes" class="olink">--enable-posix-mutexes</a>
argument.
</dd>
<dt>
<span class="term">log buffer size</span>
</dt>
<dd>
Berkeley DB internally maintains a buffer of log
writes. The buffer is written to disk at transaction
commit, by default, or, whenever it is filled. If it
is consistently being filled before transaction
commit, it will be written multiple times per
transaction, costing application performance. In these
cases, increasing the size of the log buffer can
increase application throughput.
</dd>
<dt>
<span class="term">log file location</span>
</dt>
<dd>
If the database environment's log files are on
the same disk as the databases, the disk arms will
have to seek back-and-forth between the two. Placing
the log files and the databases on different disk arms
can often increase application throughput.
</dd>
<dt>
<span class="term">trickle write</span>
</dt>
<dd>
In some applications, the cache is sufficiently
active and dirty that readers frequently need to write
a dirty page in order to have space in which to read a
new page from the backing database file. You can use
the <a href="../api_reference/C/db_stat.html" class="olink">db_stat</a> utility (or the statistics returned by the
<a href="../api_reference/C/mempstat.html" class="olink">DB_ENV->memp_stat()</a> method) to see how often this is happening
in your application's cache. In this case, using a
separate thread of control and the <a href="../api_reference/C/memptrickle.html" class="olink">DB_ENV->memp_trickle()</a>
method to trickle-write pages can often increase the
overall throughput of the application.
</dd>
</dl>
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