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    <title>MongoDB Jira</title>
    <link>https://jira.mongodb.org</link>
    <description>This file is an XML representation of an issue</description>
    <language>en-us</language>    <build-info>
        <version>9.7.1</version>
        <build-number>970001</build-number>
        <build-date>13-04-2023</build-date>
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<item>
            <title>[SERVER-18562] YCSB load  phase (insert only) push 16 core machine to 100 % due to high resoultion timers</title>
                <link>https://jira.mongodb.org/browse/SERVER-18562</link>
                <project id="10000" key="SERVER">Core Server</project>
                    <description>&lt;p&gt;MongoDB shell version: 3.1.3-pre-&lt;/p&gt;

&lt;p&gt;Environment:&lt;/p&gt;

&lt;p&gt;&#8226; Single mongod with wiredtiger as storage engine &lt;br/&gt;
&#8226; Windows 2012 &lt;br/&gt;
&#8226; WriedTiger default configuration &lt;br/&gt;
&#8226; EC2 machine c3.4xlarge&lt;/p&gt;

&lt;p&gt;Workload:&lt;/p&gt;

&lt;p&gt;&#8226; Used YCSB load &lt;/p&gt;

&lt;p&gt;Issue -&lt;/p&gt;

&lt;p&gt;During insert only workload it&apos;s appear that high resolution counter which responsible to notify if operation take longer then X (100msec default) consume 60% of the CPU&lt;/p&gt;

&lt;p&gt;The impact is so big that it mask the different between SSD drive to spin disk on windows. &lt;/p&gt;</description>
                <environment></environment>
        <key id="205231">SERVER-18562</key>
            <summary>YCSB load  phase (insert only) push 16 core machine to 100 % due to high resoultion timers</summary>
                <type id="1" iconUrl="https://jira.mongodb.org/secure/viewavatar?size=xsmall&amp;avatarId=14703&amp;avatarType=issuetype">Bug</type>
                                            <priority id="2" iconUrl="https://jira.mongodb.org/images/icons/priorities/critical.svg">Critical - P2</priority>
                        <status id="6" iconUrl="https://jira.mongodb.org/images/icons/statuses/closed.png" description="The issue is considered finished, the resolution is correct. Issues which are closed can be reopened.">Closed</status>
                    <statusCategory id="3" key="done" colorName="success"/>
                                    <resolution id="9">Done</resolution>
                                        <assignee username="backlog-server-platform">DO NOT USE - Backlog - Platform Team</assignee>
                                    <reporter username="eitan.klein">Eitan Klein</reporter>
                        <labels>
                            <label>32qa</label>
                    </labels>
                <created>Tue, 19 May 2015 18:40:16 +0000</created>
                <updated>Mon, 3 Jun 2019 15:26:06 +0000</updated>
                            <resolved>Mon, 3 Jun 2019 15:26:06 +0000</resolved>
                                    <version>3.1.3</version>
                                                    <component>Internal Code</component>
                                        <votes>1</votes>
                                    <watches>8</watches>
                                                                                                                <comments>
                            <comment id="955015" author="mark.benvenuto" created="Tue, 30 Jun 2015 20:24:51 +0000"  >&lt;p&gt;I ran the following tests to compare the impact of various time APIs on different platforms. I was not interested in comparing which platform is faster overall. I wanted to understand the relative performance of the various timing apis on each platform.&lt;/p&gt;

&lt;p&gt;Using &lt;a href=&quot;https://github.com/DigitalInBlue/Celero&quot; class=&quot;external-link&quot; target=&quot;_blank&quot; rel=&quot;nofollow noopener&quot;&gt;https://github.com/DigitalInBlue/Celero&lt;/a&gt;, a micro benchmark framework, I evaluated the following time sources on 3 platforms. I ran 10 samples of 1000000 calls each in each case.&lt;/p&gt;

&lt;div class=&apos;table-wrap&apos;&gt;
&lt;table class=&apos;confluenceTable&apos;&gt;&lt;tbody&gt;
&lt;tr&gt;
&lt;th class=&apos;confluenceTh&apos;&gt;Time Source&lt;/th&gt;
&lt;th class=&apos;confluenceTh&apos;&gt;Accuracy&lt;/th&gt;
&lt;/tr&gt;
&lt;tr&gt;
&lt;td class=&apos;confluenceTd&apos;&gt;curTimeMicros64&lt;/td&gt;
&lt;td class=&apos;confluenceTd&apos;&gt;100ns&lt;/td&gt;
&lt;/tr&gt;
&lt;tr&gt;
&lt;td class=&apos;confluenceTd&apos;&gt;QueryPerformanceCounter&lt;/td&gt;
&lt;td class=&apos;confluenceTd&apos;&gt;100ns&lt;/td&gt;
&lt;/tr&gt;
&lt;tr&gt;
&lt;td class=&apos;confluenceTd&apos;&gt;GetCurrentTime&lt;/td&gt;
&lt;td class=&apos;confluenceTd&apos;&gt;1ms-12ms&lt;/td&gt;
&lt;/tr&gt;
&lt;tr&gt;
&lt;td class=&apos;confluenceTd&apos;&gt;GetTickCount64&lt;/td&gt;
&lt;td class=&apos;confluenceTd&apos;&gt;1ms-12ms&lt;/td&gt;
&lt;/tr&gt;
&lt;tr&gt;
&lt;td class=&apos;confluenceTd&apos;&gt;QueryUnbiasedInterruptTime&lt;/td&gt;
&lt;td class=&apos;confluenceTd&apos;&gt;1ms-12ms&lt;/td&gt;
&lt;/tr&gt;
&lt;/tbody&gt;&lt;/table&gt;
&lt;/div&gt;

&lt;p&gt;Note: curTimeMicros64 comes from MongoDB&apos;s time_support.cpp&lt;/p&gt;

&lt;p&gt;&lt;b&gt;Test Platforms&lt;/b&gt;&lt;/p&gt;
&lt;ul class=&quot;alternate&quot; type=&quot;square&quot;&gt;
	&lt;li&gt;Thinkmate, Windows 8.1, 6 Core, Intel Core i7 4930K&lt;/li&gt;
	&lt;li&gt;EC2 c3.2xlarge, Windows 2008 R2, 8 vcpu, 15 GB RAM&lt;/li&gt;
	&lt;li&gt;Azure A6, WIndows 2008 R2, 4 vcpu, 28 GB RAM&lt;/li&gt;
	&lt;li&gt;Azure A6, WIndows 2012 R2, 4 vcpu, 28 GB RAM&lt;/li&gt;
&lt;/ul&gt;


&lt;p&gt;&lt;b&gt;Results&lt;/b&gt;&lt;/p&gt;

&lt;div class=&apos;table-wrap&apos;&gt;
&lt;table class=&apos;confluenceTable&apos;&gt;&lt;tbody&gt;
&lt;tr&gt;
&lt;th class=&apos;confluenceTh&apos;&gt;Platform&lt;/th&gt;
&lt;th class=&apos;confluenceTh&apos;&gt;curTimeMicros64&lt;/th&gt;
&lt;th class=&apos;confluenceTh&apos;&gt;QueryPerformanceCounter&lt;/th&gt;
&lt;th class=&apos;confluenceTh&apos;&gt;GetCurrentTime&lt;/th&gt;
&lt;th class=&apos;confluenceTh&apos;&gt;GetTickCount64&lt;/th&gt;
&lt;th class=&apos;confluenceTh&apos;&gt;QueryUnbiasedInterruptTime&lt;/th&gt;
&lt;/tr&gt;
&lt;tr&gt;
&lt;td class=&apos;confluenceTd&apos;&gt;Physical&lt;/td&gt;
&lt;td class=&apos;confluenceTd&apos;&gt;16.273037&lt;/td&gt;
&lt;td class=&apos;confluenceTd&apos;&gt;  15.642062&lt;/td&gt;
&lt;td class=&apos;confluenceTd&apos;&gt;  15.580168&lt;/td&gt;
&lt;td class=&apos;confluenceTd&apos;&gt; 15.486621&lt;/td&gt;
&lt;td class=&apos;confluenceTd&apos;&gt; 14.946076&lt;/td&gt;
&lt;/tr&gt;
&lt;tr&gt;
&lt;td class=&apos;confluenceTd&apos;&gt;EC2 &lt;/td&gt;
&lt;td class=&apos;confluenceTd&apos;&gt;49.318997&lt;/td&gt;
&lt;td class=&apos;confluenceTd&apos;&gt;  48.494332&lt;/td&gt;
&lt;td class=&apos;confluenceTd&apos;&gt;  14.757635&lt;/td&gt;
&lt;td class=&apos;confluenceTd&apos;&gt; 14.754738&lt;/td&gt;
&lt;td class=&apos;confluenceTd&apos;&gt; 14.777106&lt;/td&gt;
&lt;/tr&gt;
&lt;tr&gt;
&lt;td class=&apos;confluenceTd&apos;&gt;Azure-2008 &lt;/td&gt;
&lt;td class=&apos;confluenceTd&apos;&gt;52.732029&lt;/td&gt;
&lt;td class=&apos;confluenceTd&apos;&gt;  50.263894&lt;/td&gt;
&lt;td class=&apos;confluenceTd&apos;&gt;  45.385883&lt;/td&gt;
&lt;td class=&apos;confluenceTd&apos;&gt; 44.678298&lt;/td&gt;
&lt;td class=&apos;confluenceTd&apos;&gt; 44.314290&lt;/td&gt;
&lt;/tr&gt;
&lt;tr&gt;
&lt;td class=&apos;confluenceTd&apos;&gt;Azure-2012 &lt;/td&gt;
&lt;td class=&apos;confluenceTd&apos;&gt;39.428120&lt;/td&gt;
&lt;td class=&apos;confluenceTd&apos;&gt;  37.207951&lt;/td&gt;
&lt;td class=&apos;confluenceTd&apos;&gt;  30.978468&lt;/td&gt;
&lt;td class=&apos;confluenceTd&apos;&gt; 32.044333&lt;/td&gt;
&lt;td class=&apos;confluenceTd&apos;&gt; 32.818515&lt;/td&gt;
&lt;/tr&gt;
&lt;/tbody&gt;&lt;/table&gt;
&lt;/div&gt;


&lt;p&gt;&lt;b&gt;Summary&lt;/b&gt;&lt;br/&gt;
It is no surprise that virtual machines are slower then real machines. On the physical machine case, the I expect QPC to cost more then coarse time apis, and it does. Just not by much.&lt;/p&gt;

&lt;p&gt;On the Azure platforms, we see slower times for all counters, but the relative time source performance is as expected. Also, overall, 2012 R2 is better then 2008 R2 in this micro benchmark. &lt;/p&gt;

&lt;p&gt;The surprising thing is the QPC is &lt;em&gt;significantly&lt;/em&gt; slower, almost 4x, then the other time sources on EC2. &lt;/p&gt;</comment>
                            <comment id="948832" author="schwerin" created="Wed, 24 Jun 2015 01:25:37 +0000"  >&lt;p&gt;&lt;a href=&quot;https://jira.mongodb.org/secure/ViewProfile.jspa?name=eitan.klein&quot; class=&quot;user-hover&quot; rel=&quot;eitan.klein&quot;&gt;eitan.klein&lt;/a&gt;, why is this not a dupe of &lt;a href=&quot;https://jira.mongodb.org/browse/SERVER-18613&quot; title=&quot;We can double the WiredTiger YCSB load throughput on windows by eliminate the expensive timer operations&quot; class=&quot;issue-link&quot; data-issue-key=&quot;SERVER-18613&quot;&gt;&lt;del&gt;SERVER-18613&lt;/del&gt;&lt;/a&gt;, at least in terms of how it might be fixed?&lt;/p&gt;</comment>
                            <comment id="948830" author="schwerin" created="Wed, 24 Jun 2015 01:23:16 +0000"  >&lt;p&gt;We should use QueryPerformanceCounter on systems where rdtsc is fast, as GetTickCount64 has 10ms resolution (actually, probably 1ms).&lt;/p&gt;</comment>
                            <comment id="947499" author="eitan.klein" created="Mon, 22 Jun 2015 22:20:06 +0000"  >&lt;p&gt;&lt;a href=&quot;https://jira.mongodb.org/secure/ViewProfile.jspa?name=acm&quot; class=&quot;user-hover&quot; rel=&quot;acm&quot;&gt;acm&lt;/a&gt;&lt;/p&gt;

&lt;p&gt;Per our discussion, I think we should use GetTickCount64() API for the tracing methods should be good for our monitor system, and believe it significant faster&lt;/p&gt;</comment>
                    </comments>
                <issuelinks>
                            <issuelinktype id="10011">
                    <name>Depends</name>
                                            <outwardlinks description="depends on">
                                        <issuelink>
            <issuekey id="210008">SERVER-18922</issuekey>
        </issuelink>
                            </outwardlinks>
                                                        </issuelinktype>
                            <issuelinktype id="10012">
                    <name>Related</name>
                                            <outwardlinks description="related to">
                                        <issuelink>
            <issuekey id="205790">SERVER-18613</issuekey>
        </issuelink>
                            </outwardlinks>
                                                                <inwardlinks description="is related to">
                                        <issuelink>
            <issuekey id="190143">SERVER-17630</issuekey>
        </issuelink>
            <issuelink>
            <issuekey id="28815">SERVER-4740</issuekey>
        </issuelink>
                            </inwardlinks>
                                    </issuelinktype>
                    </issuelinks>
                <attachments>
                            <attachment id="74914" name="YCSB-Load.png" size="146104" author="eitan.klein" created="Tue, 19 May 2015 18:40:16 +0000"/>
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