<?xml version="1.0" encoding="UTF-8"?>
<rss xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:taxo="http://purl.org/rss/1.0/modules/taxonomy/" version="2.0">
  <channel>
    <title>topic Re: proc freq for huge data in SAS Programming</title>
    <link>https://communities.sas.com/t5/SAS-Programming/proc-freq-for-huge-data/m-p/11997#M1231</link>
    <description>I think FREQ try to build this in physical memory. &lt;BR /&gt;
On way of doing this is to use SQL, which will use utility files on disk during sort/summarization. &lt;BR /&gt;
Or you could try a divide and conquer strategi...&lt;BR /&gt;
&lt;BR /&gt;
/Linus</description>
    <pubDate>Thu, 05 Nov 2009 08:07:49 GMT</pubDate>
    <dc:creator>LinusH</dc:creator>
    <dc:date>2009-11-05T08:07:49Z</dc:date>
    <item>
      <title>proc freq for huge data</title>
      <link>https://communities.sas.com/t5/SAS-Programming/proc-freq-for-huge-data/m-p/11996#M1230</link>
      <description>I got a huge data of over 100 million records, 2 variables a and b. I need to do &lt;BR /&gt;
proc freq;&lt;BR /&gt;
table a*b;&lt;BR /&gt;
run;&lt;BR /&gt;
&lt;BR /&gt;
I got:&lt;BR /&gt;
ERROR: The requested table is too large to process.&lt;BR /&gt;
&lt;BR /&gt;
any suggestions to beat this beast? many thanks!</description>
      <pubDate>Wed, 04 Nov 2009 22:12:00 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Programming/proc-freq-for-huge-data/m-p/11996#M1230</guid>
      <dc:creator>abdullala</dc:creator>
      <dc:date>2009-11-04T22:12:00Z</dc:date>
    </item>
    <item>
      <title>Re: proc freq for huge data</title>
      <link>https://communities.sas.com/t5/SAS-Programming/proc-freq-for-huge-data/m-p/11997#M1231</link>
      <description>I think FREQ try to build this in physical memory. &lt;BR /&gt;
On way of doing this is to use SQL, which will use utility files on disk during sort/summarization. &lt;BR /&gt;
Or you could try a divide and conquer strategi...&lt;BR /&gt;
&lt;BR /&gt;
/Linus</description>
      <pubDate>Thu, 05 Nov 2009 08:07:49 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Programming/proc-freq-for-huge-data/m-p/11997#M1231</guid>
      <dc:creator>LinusH</dc:creator>
      <dc:date>2009-11-05T08:07:49Z</dc:date>
    </item>
  </channel>
</rss>

