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<h2 class="title" style="clear: both"><a id="accessmethods"></a>Access Methods</h2>
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<p>
While this manual will focus primarily on the BTree access method, it is
still useful to briefly describe all of the access methods that DB
makes available.
</p>
<p>
Note that an access method can be selected only when the database is
created. Once selected, actual API usage is generally
identical across all access methods. That is, while some
exceptions exist, mechanically you interact with the library in the same
way regardless of which access method you have selected.
</p>
<p>
The access method that you should choose is gated first by what you want
to use as a key, and then secondly by the performance that you see
for a given access method.
</p>
<p>
The following are the available access methods:
</p>
<div class="informaltable">
<table border="1" width="80%">
<colgroup>
<col align="left" />
<col align="left" />
</colgroup>
<thead>
<tr>
<th align="center">Access Method</th>
<th align="center">Description</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left">BTree</td>
<td align="left" valign="top">
<p>
Data is stored in a sorted, balanced tree structure.
Both the key and the data for BTree records can be
arbitrarily complex. That is, they can contain single values
such as an integer or a string, or complex types such as a
structure. Also, although not the default
behavior, it is possible for two records to
use keys that compare as equals. When this occurs, the
records are considered to be duplicates of one another.
</p>
</td>
</tr>
<tr>
<td align="left">Hash</td>
<td align="left" valign="top">
<p>
Data is stored in an extended linear hash table. Like
BTree, the key and the data used for Hash records can be of
arbitrarily complex data. Also, like BTree, duplicate
records are optionally supported.
</p>
</td>
</tr>
<tr>
<td align="left">Queue</td>
<td align="left" valign="top">
<p>
Data is stored in a queue as fixed-length records. Each
record uses a logical record number as its key. This access
method is designed for fast inserts at the tail of the
queue, and it has a special operation that deletes and
returns a record from the head of the queue.
</p>
<p>
This access method is unusual in that it provides record
level locking. This can provide
beneficial performance improvements in applications
requiring concurrent access to the queue.
</p>
</td>
</tr>
<tr>
<td align="left">Recno</td>
<td align="left" valign="top">
<p>
Data is stored in either fixed or variable-length records.
Like Queue, Recno records use logical record numbers as keys.
</p>
</td>
</tr>
</tbody>
</table>
</div>
<div class="sect2" lang="en" xml:lang="en">
<div class="titlepage">
<div>
<div>
<h3 class="title"><a id="selectAM"></a>Selecting Access Methods</h3>
</div>
</div>
<div></div>
</div>
<p>
To select an access method, you should first consider what you want
to use as a key for you database records. If you want to use
arbitrary data (even strings), then you should use either BTree or
Hash. If you want to use logical record numbers (essentially
integers) then you should use Queue or Recno.
</p>
<p>
Once you have made this decision, you must choose between either
BTree or Hash, or Queue or Recno. This decision is described next.
</p>
</div>
<div class="sect2" lang="en" xml:lang="en">
<div class="titlepage">
<div>
<div>
<h3 class="title"><a id="BTreeVSHash"></a>Choosing between BTree and Hash</h3>
</div>
</div>
<div></div>
</div>
<p>
For small working datasets that fit entirely in memory, there is no
difference between BTree and Hash. Both will perform just as well
as the other. In this situation, you might just as well use BTree,
if for no other reason than the majority of DB applications use
BTree.
</p>
<p>
Note that the main concern here is your
working dataset, not your entire dataset. Many applications maintain
large amounts of information but only need to access some small
portion of that data with any frequency. So what you want to
consider is the data that you will routinely use, not the sum total
of all the data managed by your application.
</p>
<p>
However, as your working dataset grows to the point
where you cannot fit it all into memory, then you need to take more
care when choosing your access method. Specifically, choose:
</p>
<div class="itemizedlist">
<ul type="disc">
<li>
<p>
BTree if your keys have some locality of reference. That is,
if they sort well and you can expect that a query for a
given key will likely be followed by a query for one of its
neighbors.
</p>
</li>
<li>
<p>
Hash if your dataset is extremely large. For any given
access method, DB must maintain a certain amount of internal
information. However, the amount of information that DB
must maintain for BTree is much greater than for Hash. The
result is that as your dataset grows, this internal
information can dominate the cache to the point where there
is relatively little space left for application data.
As a result, BTree can be forced to perform disk I/O much more
frequently than would Hash given the same amount of data.
</p>
<p>
Moreover, if your dataset becomes so large that DB will
almost certainly have to perform disk I/O to satisfy a
random request, then Hash will definitely out perform BTree
because it has fewer internal records to search through than
does BTree.
</p>
</li>
</ul>
</div>
</div>
<div class="sect2" lang="en" xml:lang="en">
<div class="titlepage">
<div>
<div>
<h3 class="title"><a id="QueueVSRecno"></a>Choosing between Queue and Recno</h3>
</div>
</div>
<div></div>
</div>
<p>
Queue or Recno are used when the application wants to use logical
record numbers for the primary database key. Logical record numbers
are essentially integers that uniquely identify the database
record. They can be either mutable or fixed, where a mutable record
number is one that might change as database records are stored or
deleted. Fixed logical record numbers never change regardless of
what database operations are performed.
</p>
<p>
When deciding between Queue and Recno, choose:
</p>
<div class="itemizedlist">
<ul type="disc">
<li>
<p>
Queue if your application requires high degrees of
concurrency. Queue provides record-level locking (as opposed
to the page-level locking that the other access methods
use), and this can result in significantly faster throughput
for highly concurrent applications.
</p>
<p>
Note, however, that Queue provides support only for fixed
length records. So if the size of the data that you want to
store varies widely from record to record, you should
probably choose an access method other than Queue.
</p>
</li>
<li>
<p>
Recno if you want mutable record numbers. Queue is only
capable of providing fixed record numbers. Also, Recno
provides support for databases whose permanent storage is a
flat text file. This is useful for applications looking for
fast, temporary storage while the data is being read or
modified.
</p>
</li>
</ul>
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