-<html><head><meta http-equiv="Content-Type" content="text/html; charset=ISO-8859-1"><title>DHCP Performance Guide</title><link rel="stylesheet" type="text/css" href="bind10-guide.css"><meta name="generator" content="DocBook XSL Stylesheets V1.76.1"><meta name="description" content="BIND 10 is a framework that features Domain Name System (DNS) and Dynamic Host Configuration Protocol (DHCP) software with development managed by Internet Systems Consortium (ISC). This document describes various aspects of DHCP performance, measurements and tuning. It covers BIND 10 DHCP (codename Kea), existing ISC DHCP4 software, perfdhcp (a DHCP performance measurement tool) and other related topics."></head><body bgcolor="white" text="black" link="#0000FF" vlink="#840084" alink="#0000FF"><div class="book" title="DHCP Performance Guide"><div class="titlepage"><div><div><h1 class="title"><a name="id
p25504"></a>DHCP Performance Guide</h1></div><div><div class="author"><h3 class="author"><span class="firstname">Tomasz</span> <span class="surname">Mrugalski</span></h3></div></div><div><p class="releaseinfo">This is a companion document for BIND 10 version
+<html><head><meta http-equiv="Content-Type" content="text/html; charset=ISO-8859-1"><title>DHCP Performance Guide</title><link rel="stylesheet" type="text/css" href="bind10-guide.css"><meta name="generator" content="DocBook XSL Stylesheets V1.76.1"><meta name="description" content="BIND 10 is a framework that features Domain Name System (DNS) and Dynamic Host Configuration Protocol (DHCP) software with development managed by Internet Systems Consortium (ISC). This document describes various aspects of DHCP performance, measurements and tuning. It covers BIND 10 DHCP (codename Kea), existing ISC DHCP4 software, perfdhcp (a DHCP performance measurement tool) and other related topics."></head><body bgcolor="white" text="black" link="#0000FF" vlink="#840084" alink="#0000FF"><div class="book" title="DHCP Performance Guide"><div class="titlepage"><div><div><h1 class="title"><a name="id
m25635296"></a>DHCP Performance Guide</h1></div><div><div class="author"><h3 class="author"><span class="firstname">Tomasz</span> <span class="surname">Mrugalski</span></h3></div></div><div><p class="releaseinfo">This is a companion document for BIND 10 version
20120712.</p></div><div><p class="copyright">Copyright © 2012 Internet Systems Consortium, Inc. ("ISC")</p></div><div><div class="abstract" title="Abstract"><p class="title"><b>Abstract</b></p><p>BIND 10 is a framework that features Domain Name System
(DNS) and Dynamic Host Configuration Protocol (DHCP)
software with development managed by Internet Systems Consortium (ISC).
This document describes various aspects of DHCP performance,
measurements and tuning. It covers BIND 10 DHCP (codename Kea),
existing ISC DHCP4 software, perfdhcp (a DHCP performance
- measurement tool) and other related topics.</p></div></div></div><hr></div><div class="toc"><p><b>Table of Contents</b></p><dl><dt><span class="preface"><a href="#idp31
888">Preface</a></span></dt><dd><dl><dt><span class="section"><a href="#acknowledgements">1. Acknowledgements</a></span></dt></dl></dd><dt><span class="chapter"><a href="#intro">1. Introduction</a></span></dt><dt><span class="chapter"><a href="#dhcp4">2. ISC DHCP 4.x</a></span></dt><dt><span class="chapter"><a href="#kea">3. Kea</a></span></dt><dd><dl><dt><span class="section"><a href="#idp40256">3.1. Backend performance evaluation</a></span></dt><dt><span class="section"><a href="#mysql-backend">3.2. MySQL backend</a></span></dt><dd><dl><dt><span class="section"><a href="#idp65808">3.2.1. MySQL tweaks</a></span></dt></dl></dd><dt><span class="section"><a href="#sqlite-ubench">3.3. SQLite-ubench</a></span></dt><dd><dl><dt><span class="section"><a href="#sqlite-tweaks">3.3.1. SQLite tweaks</a></span></dt></dl></dd><dt><span class="section"><a href="#memfile-ubench">3.4. memfile-ubench</a></span></dt><dd><dl><dt><span class="section"><a href="#memfile-tweaks">3.4.1. memfile tweaks</a></span></dt></dl></dd><dt><span class="section"><a href="#idp90368">3.5. Basic performance measurements</a></span></dt><dt><span class="section"><a href="#idp166048">3.6. Optimized performance measurements</a></span></dt><dt><span class="section"><a href="#idp241056">3.7. Conclusions</a></span></dt><dt><span class="section"><a href="#idp247008">3.8. Possible further optimizations</a></span></dt></dl></dd><dt><span class="chapter"><a href="#perfdhcp">4. perfdhcp</a></span></dt></dl></div><div class="list-of-tables"><p><b>List of Tables</b></p><dl><dt>3.1. <a href="#idp94000">Synchronous results (basic)</a></dt><dt>3.2. <a href="#idp115200">Asynchronous results (basic)</a></dt><dt>3.3. <a href="#tbl-basic-perf-results">Estimated basic performance</a></dt><dt>3.4. <a href="#idp169760">Synchronous results (optimized)</a></dt><dt>3.5. <a href="#idp190384">Asynchronous results (optimized)</a></dt><dt>3.6. <a href="#tbl-optim-perf-results">Estimated optimized performance</a></dt></dl></div><div class="preface" title="Preface"><div class="titlepage"><div><div><h2 class="title"><a name="idp31888"></a>Preface</h2></div></div></div><div class="toc"><p><b>Table of Contents</b></p><dl><dt><span class="section"><a href="#acknowledgements">1. Acknowledgements</a></span></dt></dl></div><div class="section" title="1. Acknowledgements"><div class="titlepage"><div><div><h2 class="title" style="clear: both"><a name="acknowledgements"></a>1. Acknowledgements</h2></div></div></div><p>ISC would like to acknowledge generous support for
+ measurement tool) and other related topics.</p></div></div></div><hr></div><div class="toc"><p><b>Table of Contents</b></p><dl><dt><span class="preface"><a href="#idp31
744">Preface</a></span></dt><dd><dl><dt><span class="section"><a href="#acknowledgements">1. Acknowledgements</a></span></dt></dl></dd><dt><span class="chapter"><a href="#intro">1. Introduction</a></span></dt><dt><span class="chapter"><a href="#dhcp4">2. ISC DHCP 4.x</a></span></dt><dt><span class="chapter"><a href="#kea">3. Kea</a></span></dt><dd><dl><dt><span class="section"><a href="#idp40176">3.1. Backend performance evaluation</a></span></dt><dt><span class="section"><a href="#mysql-backend">3.2. MySQL backend</a></span></dt><dd><dl><dt><span class="section"><a href="#idp64224">3.2.1. MySQL tweaks</a></span></dt></dl></dd><dt><span class="section"><a href="#sqlite-ubench">3.3. SQLite-ubench</a></span></dt><dd><dl><dt><span class="section"><a href="#sqlite-tweaks">3.3.1. SQLite tweaks</a></span></dt></dl></dd><dt><span class="section"><a href="#memfile-ubench">3.4. memfile-ubench</a></span></dt><dd><dl><dt><span class="section"><a href="#memfile-tweaks">3.4.1. memfile tweaks</a></span></dt></dl></dd><dt><span class="section"><a href="#idp104752">3.5. Basic performance measurements</a></span></dt><dt><span class="section"><a href="#idm38464">3.6. Optimized performance measurements</a></span></dt><dt><span class="section"><a href="#idp275344">3.7. Conclusions</a></span></dt><dt><span class="section"><a href="#idp281328">3.8. Possible further optimizations</a></span></dt></dl></dd><dt><span class="chapter"><a href="#perfdhcp">4. perfdhcp</a></span></dt></dl></div><div class="list-of-tables"><p><b>List of Tables</b></p><dl><dt>3.1. <a href="#idp108384">Synchronous results (basic)</a></dt><dt>3.2. <a href="#idp129440">Asynchronous results (basic)</a></dt><dt>3.3. <a href="#tbl-basic-perf-results">Estimated basic performance</a></dt><dt>3.4. <a href="#idp204944">Synchronous results (optimized)</a></dt><dt>3.5. <a href="#idp225424">Asynchronous results (optimized)</a></dt><dt>3.6. <a href="#tbl-optim-perf-results">Estimated optimized performance</a></dt></dl></div><div class="preface" title="Preface"><div class="titlepage"><div><div><h2 class="title"><a name="idp31744"></a>Preface</h2></div></div></div><div class="toc"><p><b>Table of Contents</b></p><dl><dt><span class="section"><a href="#acknowledgements">1. Acknowledgements</a></span></dt></dl></div><div class="section" title="1. Acknowledgements"><div class="titlepage"><div><div><h2 class="title" style="clear: both"><a name="acknowledgements"></a>1. Acknowledgements</h2></div></div></div><p>ISC would like to acknowledge generous support for
BIND 10 development of DHCPv4 and DHCPv6 components provided
by <a class="ulink" href="http://www.comcast.com/" target="_top">Comcast</a>.</p></div></div><div class="chapter" title="Chapter 1. Introduction"><div class="titlepage"><div><div><h2 class="title"><a name="intro"></a>Chapter 1. Introduction</h2></div></div></div><p>
This document is in the early stages of development. It is
tools, and the pros an cons of various optimization techniques.
</p></div><div class="chapter" title="Chapter 2. ISC DHCP 4.x"><div class="titlepage"><div><div><h2 class="title"><a name="dhcp4"></a>Chapter 2. ISC DHCP 4.x</h2></div></div></div><p>
TODO: Write something about ISC DHCP4 here.
- </p></div><div class="chapter" title="Chapter 3. Kea"><div class="titlepage"><div><div><h2 class="title"><a name="kea"></a>Chapter 3. Kea</h2></div></div></div><div class="toc"><p><b>Table of Contents</b></p><dl><dt><span class="section"><a href="#idp40
256">3.1. Backend performance evaluation</a></span></dt><dt><span class="section"><a href="#mysql-backend">3.2. MySQL backend</a></span></dt><dd><dl><dt><span class="section"><a href="#idp65808">3.2.1. MySQL tweaks</a></span></dt></dl></dd><dt><span class="section"><a href="#sqlite-ubench">3.3. SQLite-ubench</a></span></dt><dd><dl><dt><span class="section"><a href="#sqlite-tweaks">3.3.1. SQLite tweaks</a></span></dt></dl></dd><dt><span class="section"><a href="#memfile-ubench">3.4. memfile-ubench</a></span></dt><dd><dl><dt><span class="section"><a href="#memfile-tweaks">3.4.1. memfile tweaks</a></span></dt></dl></dd><dt><span class="section"><a href="#idp90368">3.5. Basic performance measurements</a></span></dt><dt><span class="section"><a href="#idp166048">3.6. Optimized performance measurements</a></span></dt><dt><span class="section"><a href="#idp241056">3.7. Conclusions</a></span></dt><dt><span class="section"><a href="#idp247008">3.8. Possible further optimizations</a></span></dt></dl></div><p>
+ </p></div><div class="chapter" title="Chapter 3. Kea"><div class="titlepage"><div><div><h2 class="title"><a name="kea"></a>Chapter 3. Kea</h2></div></div></div><div class="toc"><p><b>Table of Contents</b></p><dl><dt><span class="section"><a href="#idp40
176">3.1. Backend performance evaluation</a></span></dt><dt><span class="section"><a href="#mysql-backend">3.2. MySQL backend</a></span></dt><dd><dl><dt><span class="section"><a href="#idp64224">3.2.1. MySQL tweaks</a></span></dt></dl></dd><dt><span class="section"><a href="#sqlite-ubench">3.3. SQLite-ubench</a></span></dt><dd><dl><dt><span class="section"><a href="#sqlite-tweaks">3.3.1. SQLite tweaks</a></span></dt></dl></dd><dt><span class="section"><a href="#memfile-ubench">3.4. memfile-ubench</a></span></dt><dd><dl><dt><span class="section"><a href="#memfile-tweaks">3.4.1. memfile tweaks</a></span></dt></dl></dd><dt><span class="section"><a href="#idp104752">3.5. Basic performance measurements</a></span></dt><dt><span class="section"><a href="#idm38464">3.6. Optimized performance measurements</a></span></dt><dt><span class="section"><a href="#idp275344">3.7. Conclusions</a></span></dt><dt><span class="section"><a href="#idp281328">3.8. Possible further optimizations</a></span></dt></dl></div><p>
- </p><div class="section" title="3.1. Backend performance evaluation"><div class="titlepage"><div><div><h2 class="title" style="clear: both"><a name="idp40
256"></a>3.1. Backend performance evaluation</h2></div></div></div><p>
+ </p><div class="section" title="3.1. Backend performance evaluation"><div class="titlepage"><div><div><h2 class="title" style="clear: both"><a name="idp40
176"></a>3.1. Backend performance evaluation</h2></div></div></div><p>
Kea will support several different database backends, using
both popular databases (like MySQL or SQLite) and
custom-developed solutions (such as an in-memory database).
for performance measurements.
</p><p>All benchmarks are implemented as single threaded applications
that take advantage of a single database connection.</p><p>
- Those benchmarks are stored in tests/tools/dhcp-ubench
- directory of the BIND 10 source tree. This directory contains simplified prototypes for
+ Those benchmarks are stored in tests/tools/dhcp-ubench directory of the
+ BIND 10 source tree. This directory contains simplified prototypes for
the various database back-ends that are planned or considered as a
- possibly for BIND10 DHCP. Athough trivial now, the benchmarks are
- expected to evolve into useful tools that will allow users to
- measure performance in their specific environment.
+ possibly for BIND10 DHCP. These benchmarks are expected to evolve into
+ useful tools that will allow users to measure performance in their
+ specific environment.
</p><p>
Currently the following benchmarks are implemented:
</p><div class="itemizedlist"><ul class="itemizedlist" type="disc"><li class="listitem"><p>In memory + flat file</p></li><li class="listitem"><p>SQLite</p></li><li class="listitem"><p>MySQL</p></li></ul></div><p>
</p><p>
- As the benchmarks require additional (sometimes heavy) dependencies, they are not
- built by default. Actually, their build system is completely separate from that
- of the rest of BIND 10.
- It is anticipated that they will be eventually merged into the rest of BIND 10, but
- that is a low priority for now.
+ As the benchmarks require additional (sometimes heavy) dependencies, they
+ are not built by default. Actually, their build system is completely
+ separate from that of the rest of BIND 10. It will be eventually merged
+ with the main BIND 10 build system.
</p><p>
All benchmarks will follow the same pattern:
</p><div class="orderedlist"><ol class="orderedlist" type="1"><li class="listitem"><p>Prepare operation (connect to a database, create a file etc.)</p></li><li class="listitem"><p>Measure timestamp 0</p></li><li class="listitem"><p>Commit new lease4 record (repeated N times)</p></li><li class="listitem"><p>Measure timestamp 1</p></li><li class="listitem"><p>Search for random lease4 record (repeated N times)</p></li><li class="listitem"><p>Measure timestamp 2</p></li><li class="listitem"><p>Update existing lease4 record (repeated N times)</p></li><li class="listitem"><p>Measure timestamp 3</p></li><li class="listitem"><p>Delete existing lease4 record (repeated N times)</p></li><li class="listitem"><p>Measure timestamp 4</p></li><li class="listitem"><p>Print out statistics, based on N and measured timestamps.</p></li></ol></div><p>
the same list of parameters, some of them are specific to a given backend.
To get a list of supported parameters, run the benchmark with the "-h" option:
- </p><pre class="screen">$ <strong class="userinput"><code>./mysql_ubench -h</code></strong>
-This is a benchmark designed to measure expected performance
-of several backends. This particular version identifies itself
-as following:
-MySQL client version is 5.5.24
-
-Possible command-line parameters:
- -h - help (you are reading this)
- -m hostname - specifies MySQL server to connect (MySQL backend only)
- -u username - specifies MySQL user name (MySQL backend only)
- -p password - specifies MySQL passwod (MySQL backend only)
- -f name - database or filename (MySQL, SQLite and memfile)
- -n integer - number of test repetitions (MySQL, SQLite and memfile)
- -s yes|no - synchronous/asynchronous operation (MySQL, SQLite and memfile)
- -v yes|no - verbose mode (MySQL, SQLite and memfile)
- -c yes|no - should compiled statements be used (MySQL only)
-</pre><p>
-
+ </p><pre class="screen">$ <strong class="userinput"><code>./mysql_ubench -h</code></strong></pre><p>
</p><p>Synchronous operation requires database backend to
physically store changes to disk before proceeding. This
property ensures that no data is lost in case of the server
failure. Unfortunately, it slows operation
considerably. Asynchronous mode allows database to write data at
a later time (usually controlled by the database engine on OS
- disk buffering mechanism).</p><div class="section" title="3.2.1. MySQL tweaks"><div class="titlepage"><div><div><h3 class="title"><a name="idp65808"></a>3.2.1. MySQL tweaks</h3></div></div></div><p>One parameter that has huge impact on performance is the choice of backend engine.
+ disk buffering mechanism).</p><div class="section" title="3.2.1. MySQL tweaks"><div class="titlepage"><div><div><h3 class="title"><a name="idp64224"></a>3.2.1. MySQL tweaks</h3></div></div></div><p>To modify the default mysql_ubench parameters, command line
+ switches can be used. The currently supported switches are
+ (default values specified in brackets):
+ </p><div class="orderedlist"><ol class="orderedlist" type="1"><li class="listitem"><p>-f name - name of the database ("kea")</p></li><li class="listitem"><p>-m hostname - name of the database host ("localhost")</p></li><li class="listitem"><p>-u user - MySQL username ("root")</p></li><li class="listitem"><p>-p password - MySQL password ("secret")</p></li><li class="listitem"><p>-n num - number of iterations (100)</p></li><li class="listitem"><p>-s yes|no - should the operations be performed in a synchronous (yes)
+ or asynchronous (no) manner (yes)</p></li><li class="listitem"><p>-v yes|no - verbose mode. Should the test print out progress? (yes)</p></li><li class="listitem"><p>-c yes|no - precompiled statements. Should the SQL statements be precompiled? (yes)</p></li></ol></div><p>
+ </p><p>One parameter that has huge impact on performance is the choice of backend engine.
You can get a list of engines of your MySQL implementation by using
</p><pre class="screen">> <strong class="userinput"><code>show engines;</code></strong></pre><p>
switches can be used. The currently supported switches are
(default values specified in brackets):
</p><div class="orderedlist"><ol class="orderedlist" type="1"><li class="listitem"><p>-f filename - name of the database file ("sqlite.db")</p></li><li class="listitem"><p>-n num - number of iterations (100)</p></li><li class="listitem"><p>-s yes|no - should the operations be performed in a synchronous (yes)
- or asynchronous (no) manner (yes)</p></li><li class="listitem"><p>-v yes|no - verbose mode. Should the test print out progress? (yes)</p></li><li class="listitem"><p>-c yes|no - precompiled statements. Should the SQL statements be precompiled?</p></li></ol></div><p>
+ or asynchronous (no) manner (yes)</p></li><li class="listitem"><p>-v yes|no - verbose mode. Should the test print out progress? (yes)</p></li><li class="listitem"><p>-c yes|no - precompiled statements. Should the SQL statements be precompiled?
(yes)</p></li></ol></div><p>
</p><p>SQLite can run in asynchronous or synchronous mode. This
mode can be controlled by using "synchronous" parameter. It is set
using the SQLite command:</p><p><span class="command"><strong>PRAGMA synchronous = ON|OFF</strong></span></p><p>Another tweakable feature is journal mode. It can be
that file append operation is faster than modifications introduced
in the middle of the file (as it often requires moving all data
after modified point, effectively requiring writing large parts of
- the whole file, not just changed fragment).</p><div class="section" title="3.4.1. memfile tweaks"><div class="titlepage"><div><div><h3 class="title"><a name="memfile-tweaks"></a>3.4.1. memfile tweaks</h3></div></div></div><p>To modify default memfile_ubench parameters, command line
+ the whole file, not just changed fragment).</p><p>There are no preparatory steps required for memfile benchmark.
+ The only requirement is the ability to create and write specified lease
+ file (dhcpd.leases in the current directory). The tests can be run
+ as follows:
+ </p><pre class="screen">> <strong class="userinput"><code>./memfile_ubench</code></strong></pre><p>
+ or
+ </p><pre class="screen">> <strong class="userinput"><code>./memfile_ubench > results-memfile.txt</code></strong></pre><p>
+ </p><div class="section" title="3.4.1. memfile tweaks"><div class="titlepage"><div><div><h3 class="title"><a name="memfile-tweaks"></a>3.4.1. memfile tweaks</h3></div></div></div><p>To modify default memfile_ubench parameters, command line
switches can be used. Currently supported switches are
(default values specified in brackets):
</p><div class="orderedlist"><ol class="orderedlist" type="1"><li class="listitem"><p>-f filename - name of the database file ("dhcpd.leases")</p></li><li class="listitem"><p>-n num - number of iterations (100)</p></li><li class="listitem"><p>-s yes|no - should the operations be performend in a synchronous (yes)
</p><p>memfile can run in asynchronous or synchronous mode. This
mode can be controlled by using sync parameter. It uses
fflush() and fsync() in synchronous mode to make sure that
- data is not buffered and physically stored on disk.</p></div></div><div class="section" title="3.5. Basic performance measurements"><div class="titlepage"><div><div><h2 class="title" style="clear: both"><a name="idp
90368"></a>3.5. Basic performance measurements</h2></div></div></div><p>This section contains sample results for backend performance measurements,
+ data is not buffered and physically stored on disk.</p></div></div><div class="section" title="3.5. Basic performance measurements"><div class="titlepage"><div><div><h2 class="title" style="clear: both"><a name="idp
104752"></a>3.5. Basic performance measurements</h2></div></div></div><p>This section contains sample results for backend performance measurements,
taken using microbenchmarks. Tests were conducted on reasonably powerful machine:
</p><pre class="screen">
CPU: Quad-core Intel(R) Core(TM) i7-2600K CPU @ 3.40GHz (8 logical cores)
asynchronous. As those modes offer radically different
performances, synchronous mode was conducted for one
thousand repetitions and asynchronous mode was conducted for
- one hundred thousand repetitions.</p><div class="table"><a name="idp94000"></a><p class="title"><b>Table 3.1. Synchronous results (basic)</b></p><div class="table-contents"><table summary="Synchronous results (basic)" border="1"><colgroup><col align="center" class="Backend"><col align="center" class="Num"><col align="center" class="Create"><col align="center" class="Search"><col align="center" class="Update"><col align="center" class="Delete"></colgroup><thead><tr><th align="center">Backend</th><th align="center">Operations</th><th align="center">Create [s]</th><th align="center">Search [s]</th><th align="center">Update [s]</th><th align="center">Delete [s]</th><th align="center">Average [s]</th></tr></thead><tbody><tr><td align="center">MySQL</td><td align="center">1,000</td><td align="center">31.604</td><td align="center"> 0.117</td><td align="center">27.964</td><td align="center">27.695</td><td align="center">21.845</td></tr><tr><td align="center">SQLite</td><td align="center">1,000</td><td align="center">61.421</td><td align="center"> 0.033</td><td align="center">59.477</td><td align="center">56.034</td><td align="center">44.241</td></tr><tr><td align="center">memfile</td><td align="center">1,000</td><td align="center">38.224</td><td align="center"> 0.001</td><td align="center">38.041</td><td align="center">38.017</td><td align="center">28.571</td></tr></tbody></table></div></div><br class="table-break"><p>The following parameters were measured for asynchronous mode.
- MySQL and SQLite were run with one hundred thousand repetitions. Memfile
- was run for one million repetitions due to its much higher performance.</p><div class="table"><a name="idp115200"></a><p class="title"><b>Table 3.2. Asynchronous results (basic)</b></p><div class="table-contents"><table summary="Asynchronous results (basic)" border="1"><colgroup><col align="center" class="Backend"><col align="center" class="Num"><col align="center" class="Create"><col align="center" class="Search"><col align="center" class="Update"><col align="center" class="Delete"></colgroup><thead><tr><th align="center">Backend</th><th align="center">Operations</th><th align="center">Create [s]</th><th align="center">Search [s]</th><th align="center">Update [s]</th><th align="center">Delete [s]</th><th align="center">Average [s]</th></tr></thead><tbody><tr><td align="center">MySQL</td><td align="center">100,000</td><td align="center">10.585</td><td align="center">10.386</td><td align="center">10.062</td><td align="center"> 8.890</td><td align="center"> 9.981</td></tr><tr><td align="center">SQLite</td><td align="center">100,000</td><td align="center"> 3.710</td><td align="center"> 3.159</td><td align="center"> 2.865</td><td align="center"> 2.439</td><td align="center"> 3.044</td></tr><tr><td align="center">memfile</td><td align="center">1,000,000</td><td align="center"> 1.300</td><td align="center"> 0.039</td><td align="center"> 1.307</td><td align="center"> 1.278</td><td align="center"> 0.981</td></tr></tbody></table></div></div><br class="table-break"><p>The presented performance results can be converted into operations per second metrics.
+ one hundred thousand repetitions.</p><div class="table"><a name="idp108384"></a><p class="title"><b>Table 3.1. Synchronous results (basic)</b></p><div class="table-contents"><table summary="Synchronous results (basic)" border="1"><colgroup><col align="center" class="Backend"><col align="center" class="Num"><col align="center" class="Create"><col align="center" class="Search"><col align="center" class="Update"><col align="center" class="Delete"></colgroup><thead><tr><th align="center">Backend</th><th align="center">Operations</th><th align="center">Create [s]</th><th align="center">Search [s]</th><th align="center">Update [s]</th><th align="center">Delete [s]</th><th align="center">Average [s]</th></tr></thead><tbody><tr><td align="center">MySQL</td><td align="center">1,000</td><td align="center">31.604</td><td align="center"> 0.117</td><td align="center">27.964</td><td align="center">27.695</td><td align="center">21.845</td></tr><tr><td align="center">SQLite</td><td align="center">1,000</td><td align="center">61.421</td><td align="center"> 0.033</td><td align="center">59.477</td><td align="center">56.034</td><td align="center">44.241</td></tr><tr><td align="center">memfile</td><td align="center">1,000</td><td align="center">38.224</td><td align="center"> 0.001</td><td align="center">38.041</td><td align="center">38.017</td><td align="center">28.571</td></tr></tbody></table></div></div><br class="table-break"><p>The following parameters were measured for asynchronous mode.
+ MySQL and SQLite were run with one hundred thousand repetitions.</p><div class="table"><a name="idp129440"></a><p class="title"><b>Table 3.2. Asynchronous results (basic)</b></p><div class="table-contents"><table summary="Asynchronous results (basic)" border="1"><colgroup><col align="center" class="Backend"><col align="center" class="Num"><col align="center" class="Create"><col align="center" class="Search"><col align="center" class="Update"><col align="center" class="Delete"></colgroup><thead><tr><th align="center">Backend</th><th align="center">Operations</th><th align="center">Create [s]</th><th align="center">Search [s]</th><th align="center">Update [s]</th><th align="center">Delete [s]</th><th align="center">Average [s]</th></tr></thead><tbody><tr><td align="center">MySQL</td><td align="center">100,000</td><td align="center">10.585</td><td align="center">10.386</td><td align="center">10.062</td><td align="center"> 8.890</td><td align="center"> 9.981</td></tr><tr><td align="center">SQLite</td><td align="center">100,000</td><td align="center"> 3.710</td><td align="center"> 3.159</td><td align="center"> 2.865</td><td align="center"> 2.439</td><td align="center"> 3.044</td></tr><tr><td align="center">memfile</td><td align="center">100,000</td><td align="center"> 1.300</td><td align="center"> 0.039</td><td align="center"> 1.307</td><td align="center"> 1.278</td><td align="center"> 0.981</td></tr></tbody></table></div></div><br class="table-break"><p>The presented performance results can be converted into operations per second metrics.
It should be noted that due to large differences between various operations (sometimes
over three orders of magnitude), it is difficult to create a simple, readable chart with
- that data.</p><div class="table"><a name="tbl-basic-perf-results"></a><p class="title"><b>Table 3.3. Estimated basic performance</b></p><div class="table-contents"><table summary="Estimated basic performance" border="1"><colgroup><col align="center" class="Backend"><col align="center" class="Create"><col align="center" class="Search"><col align="center" class="Update"><col align="center" class="Delete"><col align="center" class="Average"></colgroup><thead><tr><th align="center">Backend</th><th align="center">Create [oper/s]</th><th align="center">Search [oper/s]</th><th align="center">Update [oper/s]</th><th align="center">Delete [oper/s]</th><th align="center">Average [oper/s]</th></tr></thead><tbody><tr><td align="center">MySQL (async)</td><td align="center">9447.47</td><td align="center">9627.97</td><td align="center">9938.00</td><td align="center">11248.34</td><td align="center">10065.45</td></tr><tr><td align="center">SQLite (async)</td><td align="center">26951.59</td><td align="center">31654.29</td><td align="center">34899.70</td><td align="center">40993.59</td><td align="center">33624.79</td></tr><tr><td align="center">memfile (async)</td><td align="center">76944.27</td><td align="center">2542588.35</td><td align="center">76504.54</td><td align="center">78269.25</td><td align="center">693576.60</td></tr><tr><td align="center">MySQL (sync)</td><td align="center">31.64</td><td align="center">8575.45</td><td align="center">35.76</td><td align="center">36.11</td><td align="center">2169.74</td></tr><tr><td align="center">SQLite (sync)</td><td align="center">16.28</td><td align="center">20045.37</td><td align="center">16.81</td><td align="center">17.85</td><td align="center">7524.08</td></tr><tr><td align="center">memfile (sync)</td><td align="center">26.16</td><td align="center">1223990.21</td><td align="center">26.29</td><td align="center">26.30</td><td align="center">306017.24</td></tr></tbody></table></div></div><br class="table-break"><div class="mediaobject"><img src="performance-results-graph1.png"
alt="Basic performance measurements"><div class="caption"><p>Graphical representation of the basic performance results
- presented in table <a class="xref" href="#tbl-basic-perf-results" title="Table 3.3. Estimated basic performance">Table 3.3, “Estimated basic performance”</a>.</p></div></div></div><div class="section" title="3.6. Optimized performance measurements"><div class="titlepage"><div><div><h2 class="title" style="clear: both"><a name="id
p166048"></a>3.6. Optimized performance measurements</h2></div></div></div><p>This section contains sample results for backend performance measurements,
+ that data.</p><div class="table"><a name="tbl-basic-perf-results"></a><p class="title"><b>Table 3.3. Estimated basic performance</b></p><div class="table-contents"><table summary="Estimated basic performance" border="1"><colgroup><col align="center" class="Backend"><col align="center" class="Create"><col align="center" class="Search"><col align="center" class="Update"><col align="center" class="Delete"><col align="center" class="Average"></colgroup><thead><tr><th align="center">Backend</th><th align="center">Create [oper/s]</th><th align="center">Search [oper/s]</th><th align="center">Update [oper/s]</th><th align="center">Delete [oper/s]</th><th align="center">Average [oper/s]</th></tr></thead><tbody><tr><td align="center">MySQL (async)</td><td align="center">9447.47</td><td align="center">9627.97</td><td align="center">9938.00</td><td align="center">11248.34</td><td align="center">10065.45</td></tr><tr><td align="center">SQLite (async)</td><td align="center">26951.59</td><td align="center">31654.29</td><td align="center">34899.70</td><td align="center">40993.59</td><td align="center">33624.79</td></tr><tr><td align="center">memfile (async)</td><td align="center">76944.27</td><td align="center">2542588.35</td><td align="center">76504.54</td><td align="center">78269.25</td><td align="center">693576.60</td></tr><tr><td align="center">MySQL (sync)</td><td align="center">31.64</td><td align="center">8575.45</td><td align="center">35.76</td><td align="center">36.11</td><td align="center">2169.74</td></tr><tr><td align="center">SQLite (sync)</td><td align="center">16.28</td><td align="center">20045.37</td><td align="center">16.81</td><td align="center">17.85</td><td align="center">7524.08</td></tr><tr><td align="center">memfile (sync)</td><td align="center">26.16</td><td align="center">1223990.21</td><td align="center">26.29</td><td align="center">26.30</td><td align="center">306017.24</td></tr></tbody></table></div></div><br class="table-break"><div class="mediaobject"><img src="performance-results-graph1.png"><div class="caption"><p>Graphical representation of the basic performance results
+ presented in table <a class="xref" href="#tbl-basic-perf-results" title="Table 3.3. Estimated basic performance">Table 3.3, “Estimated basic performance”</a>.</p></div></div></div><div class="section" title="3.6. Optimized performance measurements"><div class="titlepage"><div><div><h2 class="title" style="clear: both"><a name="id
m38464"></a>3.6. Optimized performance measurements</h2></div></div></div><p>This section contains sample results for backend performance measurements,
taken using microbenchmarks. Tests were conducted on reasonably powerful machine:
</p><pre class="screen">
CPU: Quad-core Intel(R) Core(TM) i7-2600K CPU @ 3.40GHz (8 logical cores)
asynchronous. As those modes offer radically different
performances, synchronous mode was conducted for one
thousand repetitions and asynchronous mode was conducted for
- one hundred thousand repetitions.</p><div class="table"><a name="idp169760"></a><p class="title"><b>Table 3.4. Synchronous results (optimized)</b></p><div class="table-contents"><table summary="Synchronous results (optimized)" border="1"><colgroup><col align="center" class="Backend"><col align="center" class="Num"><col align="center" class="Create"><col align="center" class="Search"><col align="center" class="Update"><col align="center" class="Delete"></colgroup><thead><tr><th align="center">Backend</th><th align="center">Operations</th><th align="center">Create [s]</th><th align="center">Search [s]</th><th align="center">Update [s]</th><th align="center">Delete [s]</th><th align="center">Average [s]</th></tr></thead><tbody><tr><td align="center">MySQL</td><td align="center">1,000</td><td align="center">27.887</td><td align="center"> 0.106</td><td align="center">28.223</td><td align="center">27.696</td><td align="center">20.978</td></tr><tr><td align="center">SQLite</td><td align="center">1,000</td><td align="center">61.299</td><td align="center"> 0.015</td><td align="center">59.648</td><td align="center">61.098</td><td align="center">45.626</td></tr><tr><td align="center">memfile</td><td align="center">1,000</td><td align="center">39.564</td><td align="center"> 0.001</td><td align="center">39.543</td><td align="center">39.326</td><td align="center">29.608</td></tr></tbody></table></div></div><br class="table-break"><p>The following parameters were measured for asynchronous mode.
- MySQL and SQLite were run with one hundred thousand repetitions. Memfile
- was run for one million repetitions due to its much higher performance.</p><div class="table"><a name="idp190384"></a><p class="title"><b>Table 3.5. Asynchronous results (optimized)</b></p><div class="table-contents"><table summary="Asynchronous results (optimized)" border="1"><colgroup><col align="center" class="Backend"><col align="center" class="Num"><col align="center" class="Create"><col align="center" class="Search"><col align="center" class="Update"><col align="center" class="Delete"></colgroup><thead><tr><th align="center">Backend</th><th align="center">Operations</th><th align="center">Create [s]</th><th align="center">Search [s]</th><th align="center">Update [s]</th><th align="center">Delete [s]</th><th align="center">Average [s]</th></tr></thead><tbody><tr><td align="center">MySQL</td><td align="center">100,000</td><td align="center">8.507</td><td align="center">9.698</td><td align="center">7.785</td><td align="center">8.326</td><td align="center">8.579</td></tr><tr><td align="center">SQLite</td><td align="center">100,000</td><td align="center"> 1.562</td><td align="center"> 0.949</td><td align="center"> 1.513</td><td align="center"> 1.502</td><td align="center"> 1.382</td></tr><tr><td align="center">memfile</td><td align="center">1,000,000</td><td align="center">1.302</td><td align="center">0.038</td><td align="center">1.306</td><td align="center">1.263</td><td align="center">0.977</td></tr></tbody></table></div></div><br class="table-break"><p>The presented performance results can be converted into operations per second metrics.
+ one hundred thousand repetitions.</p><div class="table"><a name="idp204944"></a><p class="title"><b>Table 3.4. Synchronous results (optimized)</b></p><div class="table-contents"><table summary="Synchronous results (optimized)" border="1"><colgroup><col align="center" class="Backend"><col align="center" class="Num"><col align="center" class="Create"><col align="center" class="Search"><col align="center" class="Update"><col align="center" class="Delete"></colgroup><thead><tr><th align="center">Backend</th><th align="center">Operations</th><th align="center">Create [s]</th><th align="center">Search [s]</th><th align="center">Update [s]</th><th align="center">Delete [s]</th><th align="center">Average [s]</th></tr></thead><tbody><tr><td align="center">MySQL</td><td align="center">1,000</td><td align="center">27.887</td><td align="center"> 0.106</td><td align="center">28.223</td><td align="center">27.696</td><td align="center">20.978</td></tr><tr><td align="center">SQLite</td><td align="center">1,000</td><td align="center">61.299</td><td align="center"> 0.015</td><td align="center">59.648</td><td align="center">61.098</td><td align="center">45.626</td></tr><tr><td align="center">memfile</td><td align="center">1,000</td><td align="center">39.564</td><td align="center"> 0.001</td><td align="center">39.543</td><td align="center">39.326</td><td align="center">29.608</td></tr></tbody></table></div></div><br class="table-break"><p>The following parameters were measured for asynchronous mode.
+ MySQL and SQLite were run with one hundred thousand repetitions.</p><div class="table"><a name="idp225424"></a><p class="title"><b>Table 3.5. Asynchronous results (optimized)</b></p><div class="table-contents"><table summary="Asynchronous results (optimized)" border="1"><colgroup><col align="center" class="Backend"><col align="center" class="Num"><col align="center" class="Create"><col align="center" class="Search"><col align="center" class="Update"><col align="center" class="Delete"></colgroup><thead><tr><th align="center">Backend</th><th align="center">Operations</th><th align="center">Create [s]</th><th align="center">Search [s]</th><th align="center">Update [s]</th><th align="center">Delete [s]</th><th align="center">Average [s]</th></tr></thead><tbody><tr><td align="center">MySQL</td><td align="center">100,000</td><td align="center">8.507</td><td align="center">9.698</td><td align="center">7.785</td><td align="center">8.326</td><td align="center">8.579</td></tr><tr><td align="center">SQLite</td><td align="center">100,000</td><td align="center"> 1.562</td><td align="center"> 0.949</td><td align="center"> 1.513</td><td align="center"> 1.502</td><td align="center"> 1.382</td></tr><tr><td align="center">memfile</td><td align="center">100,000</td><td align="center">1.302</td><td align="center">0.038</td><td align="center">1.306</td><td align="center">1.263</td><td align="center">0.977</td></tr></tbody></table></div></div><br class="table-break"><p>The presented performance results can be converted into operations per second metrics.
It should be noted that due to large differences between various operations (sometime
over three orders of magnitude), it is difficult to create a simple, readable chart with
the data.</p><div class="table"><a name="tbl-optim-perf-results"></a><p class="title"><b>Table 3.6. Estimated optimized performance</b></p><div class="table-contents"><table summary="Estimated optimized performance" border="1"><colgroup><col align="center" class="Backend"><col align="center" class="Create"><col align="center" class="Search"><col align="center" class="Update"><col align="center" class="Delete"><col align="center" class="Average"></colgroup><thead><tr><th align="center">Backend</th><th align="center">Create [oper/s]</th><th align="center">Search [oper/s]</th><th align="center">Update [oper/s]</th><th align="center">Delete [oper/s]</th><th align="center">Average [oper/s]</th></tr></thead><tbody><tr><td align="center">MySQL (async)</td><td align="center">11754.84</td><td align="center">10311.34</td><td align="center">12845.35</td><td align="center">12010.24</td><td align="center">11730.44</td></tr><tr><td align="center">SQLite (async)</td><td align="center">64005.90</td><td align="center">105391.29</td><td align="center">66075.51</td><td align="center">66566.43</td><td align="center">75509.78</td></tr><tr><td align="center">memfile (async)</td><td align="center">76832.16</td><td align="center">2636018.56</td><td align="center">76542.50</td><td align="center">79188.81</td><td align="center">717145.51</td></tr><tr><td align="center">MySQL (sync)</td><td align="center">35.86</td><td align="center">9461.10</td><td align="center">35.43</td><td align="center">36.11</td><td align="center">2392.12</td></tr><tr><td align="center">SQLite (sync)</td><td align="center">16.31</td><td align="center">67036.11</td><td align="center">16.76</td><td align="center">16.37</td><td align="center">16771.39</td></tr><tr><td align="center">memfile (sync)</td><td align="center">25.28</td><td align="center">3460207.61</td><td align="center">25.29</td><td align="center">25.43</td><td align="center">865070.90</td></tr></tbody></table></div></div><br class="table-break"><div class="mediaobject"><img src="performance-results-graph2.png" alt="Optimized performance measurements"><div class="caption"><p>Graphical representation of the optimized performance
- results presented in table <a class="xref" href="#tbl-optim-perf-results" title="Table 3.6. Estimated optimized performance">Table 3.6, “Estimated optimized performance”</a>.</p></div></div></div><div class="section" title="3.7. Conclusions"><div class="titlepage"><div><div><h2 class="title" style="clear: both"><a name="idp2
41056"></a>3.7. Conclusions</h2></div></div></div><p>
+ results presented in table <a class="xref" href="#tbl-optim-perf-results" title="Table 3.6. Estimated optimized performance">Table 3.6, “Estimated optimized performance”</a>.</p></div></div></div><div class="section" title="3.7. Conclusions"><div class="titlepage"><div><div><h2 class="title" style="clear: both"><a name="idp2
75344"></a>3.7. Conclusions</h2></div></div></div><p>
Improvements gained by introducing support for precompiled
statements in MySQL is somewhat disappointing - between 6 and
29%. On the other hand, the improvement in SQLite is
factor here is a disk access time. Even migrating to high
performance 15,000 rpm disk is expected to only roughly double
number of leases per second, compared to the current results.
- The reason is that to write a file to disk, at least two writes
+ The reason is that to write a file to disk, at least two disk
+ sector writes
are required: the new content and i-node modification of the
file. The easiest way to boost synchronous performance is to
switch to SSD disks. Memory-backed RAM disks are also a viable
solution. However, care should be taken to properly engineer
- backup strategy for RAM disks.
+ backup strategy for such RAM disks.
</p><p>
While the custom made backend (memfile) provides the best
perfomance, it carries over all the limitations existing in
message. The provided results should be considered as only rough
estimates. They can also be used for relative comparisons
between backends.
- </p></div><div class="section" title="3.8. Possible further optimizations"><div class="titlepage"><div><div><h2 class="title" style="clear: both"><a name="idp2
47008"></a>3.8. Possible further optimizations</h2></div></div></div><p>
+ </p></div><div class="section" title="3.8. Possible further optimizations"><div class="titlepage"><div><div><h2 class="title" style="clear: both"><a name="idp2
81328"></a>3.8. Possible further optimizations</h2></div></div></div><p>
For basic measurements the code was compiled with -g -O0
flags. For optimized measurements the benchmarking code was
compiled with -Ofast (optimize for speed). In both cases, the
that take advantage of a single database connection.</para>
<para>
- Those benchmarks are stored in tests/tools/dhcp-ubench
- directory of the BIND 10 source tree. This directory contains simplified prototypes for
+ Those benchmarks are stored in tests/tools/dhcp-ubench directory of the
+ BIND 10 source tree. This directory contains simplified prototypes for
the various database back-ends that are planned or considered as a
- possibly for BIND10 DHCP. Athough trivial now, the benchmarks are
- expected to evolve into useful tools that will allow users to
- measure performance in their specific environment.
+ possibly for BIND10 DHCP. These benchmarks are expected to evolve into
+ useful tools that will allow users to measure performance in their
+ specific environment.
</para>
<para>
</para>
<para>
- As the benchmarks require additional (sometimes heavy) dependencies, they are not
- built by default. Actually, their build system is completely separate from that
- of the rest of BIND 10.
- It is anticipated that they will be eventually merged into the rest of BIND 10, but
- that is a low priority for now.
+ As the benchmarks require additional (sometimes heavy) dependencies, they
+ are not built by default. Actually, their build system is completely
+ separate from that of the rest of BIND 10. It will be eventually merged
+ with the main BIND 10 build system.
</para>
<para>
<para>Before running tests, you need to initialize your database. You can
use mysql.schema script for that purpose.</para>
-
+
<para><emphasis>WARNING: It will drop existing
Kea database. Do not run this on your production server. </emphasis></para>
-
+
<para>Assuming your
MySQL user is "kea", you can initialize your test database by:
the same list of parameters, some of them are specific to a given backend.
To get a list of supported parameters, run the benchmark with the "-h" option:
- <screen>$ <userinput>./mysql_ubench -h</userinput>
-This is a benchmark designed to measure expected performance
-of several backends. This particular version identifies itself
-as following:
-MySQL client version is 5.5.24
-
-Possible command-line parameters:
- -h - help (you are reading this)
- -m hostname - specifies MySQL server to connect (MySQL backend only)
- -u username - specifies MySQL user name (MySQL backend only)
- -p password - specifies MySQL passwod (MySQL backend only)
- -f name - database or filename (MySQL, SQLite and memfile)
- -n integer - number of test repetitions (MySQL, SQLite and memfile)
- -s yes|no - synchronous/asynchronous operation (MySQL, SQLite and memfile)
- -v yes|no - verbose mode (MySQL, SQLite and memfile)
- -c yes|no - should compiled statements be used (MySQL only)
-</screen>
-
+ <screen>$ <userinput>./mysql_ubench -h</userinput></screen>
</para>
<para>Synchronous operation requires database backend to
<section>
<title>MySQL tweaks</title>
+ <para>To modify the default mysql_ubench parameters, command line
+ switches can be used. The currently supported switches are
+ (default values specified in brackets):
+ <orderedlist>
+ <listitem><para>-f name - name of the database ("kea")</para></listitem>
+ <listitem><para>-m hostname - name of the database host ("localhost")</para></listitem>
+ <listitem><para>-u user - MySQL username ("root")</para></listitem>
+ <listitem><para>-p password - MySQL password ("secret")</para></listitem>
+ <listitem><para>-n num - number of iterations (100)</para></listitem>
+ <listitem><para>-s yes|no - should the operations be performed in a synchronous (yes)
+ or asynchronous (no) manner (yes)</para></listitem>
+ <listitem><para>-v yes|no - verbose mode. Should the test print out progress? (yes)</para></listitem>
+ <listitem><para>-c yes|no - precompiled statements. Should the SQL statements be precompiled? (yes)</para></listitem>
+ </orderedlist>
+ </para>
+
+
<para>One parameter that has huge impact on performance is the choice of backend engine.
You can get a list of engines of your MySQL implementation by using
<listitem><para>-s yes|no - should the operations be performed in a synchronous (yes)
or asynchronous (no) manner (yes)</para></listitem>
<listitem><para>-v yes|no - verbose mode. Should the test print out progress? (yes)</para></listitem>
- <listitem><para>-c yes|no - precompiled statements. Should the SQL statements be precompiled?</para></listitem>
+ <listitem><para>-c yes|no - precompiled statements. Should the SQL statements be precompiled? (yes)</para></listitem>
</orderedlist>
</para>
<para>SQLite can run in asynchronous or synchronous mode. This
mode can be controlled by using "synchronous" parameter. It is set
using the SQLite command:</para>
-
+
<para><command>PRAGMA synchronous = ON|OFF</command></para>
<para>Another tweakable feature is journal mode. It can be
after modified point, effectively requiring writing large parts of
the whole file, not just changed fragment).</para>
+ <para>There are no preparatory steps required for memfile benchmark.
+ The only requirement is the ability to create and write specified lease
+ file (dhcpd.leases in the current directory). The tests can be run
+ as follows:
+ <screen>> <userinput>./memfile_ubench</userinput></screen>
+ or
+ <screen>> <userinput>./memfile_ubench > results-memfile.txt</userinput></screen>
+ </para>
+
<section id="memfile-tweaks">
<title>memfile tweaks</title>
<para>To modify default memfile_ubench parameters, command line
</table>
<para>The following parameters were measured for asynchronous mode.
- MySQL and SQLite were run with one hundred thousand repetitions. Memfile
- was run for one million repetitions due to its much higher performance.</para>
+ MySQL and SQLite were run with one hundred thousand repetitions.</para>
<!-- raw results async -->
<table><title>Asynchronous results (basic)</title>
<row>
<entry>memfile</entry>
- <entry>1,000,000</entry>
+ <entry>100,000</entry>
<entry> 1.300</entry>
<entry> 0.039</entry>
<entry> 1.307</entry>
</tgroup>
</table>
+ <!-- that is obsolete approach that is going to be removed in docbook 5.0.
+ Its only advantage is that it actually works with docbook2pdf -->
+ <!--
+ <figure>
+ <title>Graphical representation of the basic performance
+ results presented in table <xref linkend="tbl-basic-perf-results" />.</title>
+ <graphic scale="100" fileref="performance-results-graph1.png" />
+ </figure>-->
+
+ <!-- this works great for HTML export, but is silently ignored by docbook2pdf
+ and docbook2ps tools. -->
<mediaobject>
<imageobject>
- <imagedata fileref="performance-results-graph1.png" format="PNG"/>
+ <imagedata fileref="performance-results-graph1.png" format="PNG" />
</imageobject>
- <textobject>
- <phrase>Basic performance measurements</phrase>
- </textobject>
<caption>
<para>Graphical representation of the basic performance results
presented in table <xref linkend="tbl-basic-perf-results" />.</para>
</table>
<para>The following parameters were measured for asynchronous mode.
- MySQL and SQLite were run with one hundred thousand repetitions. Memfile
- was run for one million repetitions due to its much higher performance.</para>
+ MySQL and SQLite were run with one hundred thousand repetitions.</para>
<!-- raw results async -->
<table><title>Asynchronous results (optimized)</title>
<row>
<entry>memfile</entry>
- <entry>1,000,000</entry>
+ <entry>100,000</entry>
<entry>1.302</entry>
<entry>0.038</entry>
<entry>1.306</entry>
factor here is a disk access time. Even migrating to high
performance 15,000 rpm disk is expected to only roughly double
number of leases per second, compared to the current results.
- The reason is that to write a file to disk, at least two writes
+ The reason is that to write a file to disk, at least two disk
+ sector writes
are required: the new content and i-node modification of the
file. The easiest way to boost synchronous performance is to
switch to SSD disks. Memory-backed RAM disks are also a viable
solution. However, care should be taken to properly engineer
- backup strategy for RAM disks.
+ backup strategy for such RAM disks.
</para>
<para>
projects / thirdparty / kea.git / commitdiff
