<?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>question Re: HDFS user group mapping with AD in Archives of Support Questions (Read Only)</title>
    <link>https://community.cloudera.com/t5/Archives-of-Support-Questions/HDFS-user-group-mapping-with-AD/m-p/99674#M12814</link>
    <description>&lt;P&gt;There is a group mapping provider called CompositeGroupsMapping, which is capable of combining the groups returned from multiple other group mapping providers.  The user's effective group memberships are then the union of all groups returned from the underlying group mapping providers.  You could potentially set up CompositeGroupsMapping to combine results from AD and the local user database.&lt;/P&gt;&lt;P&gt;Unfortunately, I don't believe there is any step-by-step documentation available that discusses CompositeGroupsMapping.  Instead, you'd need to review Apache JIRA &lt;A href="https://issues.apache.org/jira/browse/HADOOP-8943"&gt;HADOOP-8943&lt;/A&gt; and the attached patch to see how it works.  There are also comments in core-default.xml that show example usage.&lt;/P&gt;&lt;P&gt;&lt;A href="https://github.com/apache/hadoop/blob/release-2.7.1/hadoop-common-project/hadoop-common/src/main/resources/core-default.xml#L100-L190"&gt;https://github.com/apache/hadoop/blob/release-2.7.1/hadoop-common-project/hadoop-common/src/main/resources/core-default.xml#L100-L190&lt;/A&gt;&lt;/P&gt;</description>
    <pubDate>Thu, 17 Dec 2015 02:18:12 GMT</pubDate>
    <dc:creator>cnauroth</dc:creator>
    <dc:date>2015-12-17T02:18:12Z</dc:date>
    <item>
      <title>HDFS user group mapping with AD</title>
      <link>https://community.cloudera.com/t5/Archives-of-Support-Questions/HDFS-user-group-mapping-with-AD/m-p/99673#M12813</link>
      <description>&lt;P&gt;users connect to Hive through Knox uses AD credentials...integrated HDFS with AD groups... now HDFS is not able to recognize local user groups.&lt;/P&gt;</description>
      <pubDate>Thu, 17 Dec 2015 01:00:20 GMT</pubDate>
      <guid>https://community.cloudera.com/t5/Archives-of-Support-Questions/HDFS-user-group-mapping-with-AD/m-p/99673#M12813</guid>
      <dc:creator>chrsvarma</dc:creator>
      <dc:date>2015-12-17T01:00:20Z</dc:date>
    </item>
    <item>
      <title>Re: HDFS user group mapping with AD</title>
      <link>https://community.cloudera.com/t5/Archives-of-Support-Questions/HDFS-user-group-mapping-with-AD/m-p/99674#M12814</link>
      <description>&lt;P&gt;There is a group mapping provider called CompositeGroupsMapping, which is capable of combining the groups returned from multiple other group mapping providers.  The user's effective group memberships are then the union of all groups returned from the underlying group mapping providers.  You could potentially set up CompositeGroupsMapping to combine results from AD and the local user database.&lt;/P&gt;&lt;P&gt;Unfortunately, I don't believe there is any step-by-step documentation available that discusses CompositeGroupsMapping.  Instead, you'd need to review Apache JIRA &lt;A href="https://issues.apache.org/jira/browse/HADOOP-8943"&gt;HADOOP-8943&lt;/A&gt; and the attached patch to see how it works.  There are also comments in core-default.xml that show example usage.&lt;/P&gt;&lt;P&gt;&lt;A href="https://github.com/apache/hadoop/blob/release-2.7.1/hadoop-common-project/hadoop-common/src/main/resources/core-default.xml#L100-L190"&gt;https://github.com/apache/hadoop/blob/release-2.7.1/hadoop-common-project/hadoop-common/src/main/resources/core-default.xml#L100-L190&lt;/A&gt;&lt;/P&gt;</description>
      <pubDate>Thu, 17 Dec 2015 02:18:12 GMT</pubDate>
      <guid>https://community.cloudera.com/t5/Archives-of-Support-Questions/HDFS-user-group-mapping-with-AD/m-p/99674#M12814</guid>
      <dc:creator>cnauroth</dc:creator>
      <dc:date>2015-12-17T02:18:12Z</dc:date>
    </item>
  </channel>
</rss>

