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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-22815] Investigate if there is a better cutoff for an optimized $sample than 5% of the collection</title>
                <link>https://jira.mongodb.org/browse/SERVER-22815</link>
                <project id="10000" key="SERVER">Core Server</project>
                    <description>&lt;p&gt;When &lt;a href=&quot;https://jira.mongodb.org/browse/SERVER-19182&quot; title=&quot;Integrate storage engine optimizations into $sample stage&quot; class=&quot;issue-link&quot; data-issue-key=&quot;SERVER-19182&quot;&gt;&lt;del&gt;SERVER-19182&lt;/del&gt;&lt;/a&gt; was implemented, we chose 5% as the cutoff for when we will switch from the optimized &lt;tt&gt;$sampleFromRandomCursor&lt;/tt&gt; to the normal &lt;tt&gt;$sample&lt;/tt&gt; implementation.&lt;/p&gt;

&lt;p&gt;The &lt;tt&gt;$sampleFromRandomCursor&lt;/tt&gt; implementation will do repeated random walks over a tree (in currently supported storage engines), whereas the &lt;tt&gt;$sample&lt;/tt&gt; implementation will do a full collection scan, then a top-k sort based on an injected random value.&lt;/p&gt;

&lt;p&gt;It is thought that the &lt;tt&gt;$sample&lt;/tt&gt; implementation will be faster after a certain threshold percentage. This is because a collection scan likely has a data access pattern of large sequential reads, where the random tree walks do a bunch of random point accesses. Especially on spinning disks, the former becomes more appealing as you look at a larger and larger percent of the collection.&lt;/p&gt;

&lt;p&gt;We should do some benchmarking to see if 5% is a good cutoff for a variety of setups. It will likely depend on at least the following factors:&lt;/p&gt;
&lt;ul&gt;
	&lt;li&gt;Storage engine&lt;/li&gt;
	&lt;li&gt;Type of disk&lt;/li&gt;
	&lt;li&gt;Amount of memory&lt;/li&gt;
	&lt;li&gt;Number of documents in the collection&lt;/li&gt;
	&lt;li&gt;Size of documents&lt;/li&gt;
&lt;/ul&gt;


&lt;p&gt;It may be very hard to find a number that is suited to all combinations, but it may be that there is a better choice than 5%.&lt;/p&gt;</description>
                <environment></environment>
        <key id="267474">SERVER-22815</key>
            <summary>Investigate if there is a better cutoff for an optimized $sample than 5% of the collection</summary>
                <type id="3" iconUrl="https://jira.mongodb.org/secure/viewavatar?size=xsmall&amp;avatarId=14718&amp;avatarType=issuetype">Task</type>
                                            <priority id="3" iconUrl="https://jira.mongodb.org/images/icons/priorities/major.svg">Major - P3</priority>
                        <status id="10038" iconUrl="https://jira.mongodb.org/images/icons/subtask.gif" description="">Backlog</status>
                    <statusCategory id="2" key="new" colorName="default"/>
                                    <resolution id="-1">Unresolved</resolution>
                                        <assignee username="backlog-query-optimization">Backlog - Query Optimization</assignee>
                                    <reporter username="charlie.swanson@mongodb.com">Charlie Swanson</reporter>
                        <labels>
                            <label>eng-l</label>
                    </labels>
                <created>Tue, 23 Feb 2016 16:31:52 +0000</created>
                <updated>Tue, 6 Dec 2022 04:32:32 +0000</updated>
                                                                            <component>Aggregation Framework</component>
                                        <votes>0</votes>
                                    <watches>7</watches>
                                                                                                                <comments>
                            <comment id="1182616" author="thomasr" created="Wed, 24 Feb 2016 01:14:33 +0000"  >&lt;p&gt;I can share one data point, on WiredTiger, version 3.2.1, SSDs (MacBook Pro), all default settings: &lt;/p&gt;

&lt;p&gt;I repeatedly $sampled for increasing numbers of documents (in steps of 1000) in a collection of 1M docs, and logged the time it took to return the first batch: &lt;/p&gt;

&lt;p/&gt;
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					&lt;pre style=&quot;font-size: 1em; margin: 0 10px;   width: auto; padding: 0;&quot;&gt;&lt;span style=&quot;color: black; font-family: &apos;Consolas&apos;, &apos;Bitstream Vera Sans Mono&apos;, &apos;Courier New&apos;, Courier, monospace !important;&quot;&gt;46000                    19&lt;/span&gt;&lt;/pre&gt;
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					&lt;pre style=&quot;font-size: 1em; margin: 0 10px;   width: auto; padding: 0;&quot;&gt;&lt;span style=&quot;color: black; font-family: &apos;Consolas&apos;, &apos;Bitstream Vera Sans Mono&apos;, &apos;Courier New&apos;, Courier, monospace !important;&quot;&gt;51000                    5821&lt;/span&gt;&lt;/pre&gt;
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&lt;p/&gt;

&lt;p&gt;As soon as we go above 5% of the collection (&amp;gt; 50k docs), the time to get the first batch jumps up massively (250x), because it switches to the collection scan with top-n sort which is blocking. Basically this means we have to wait for the full collection scan to be completed. Additionally, it also requires the &quot;allowDiskUse: true&quot; option for larger documents at this point due to the sort stage.&lt;/p&gt;</comment>
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