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docs/storage-openstack-swift.md

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@@ -6,7 +6,7 @@ title: Accessing OpenStack Swift from Spark
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Spark's support for Hadoop InputFormat allows it to process data in OpenStack Swift using the
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same URI formats as in Hadoop. You can specify a path in Swift as input through a
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URI of the form <code>swift://container.PROVIDER/path</code>. You will also need to set your
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Swift security credentials, through <code>core-sites.xml</code> or via
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Swift security credentials, through <code>core-site.xml</code> or via
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<code>SparkContext.hadoopConfiguration</code>.
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Current Swift driver requires Swift to use Keystone authentication method.
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@@ -37,7 +37,7 @@ For example, for Maven support, add the following to the <code>pom.xml</code> fi
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# Configuration Parameters
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Create <code>core-sites.xml</code> and place it inside <code>/spark/conf</code> directory.
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Create <code>core-site.xml</code> and place it inside <code>/spark/conf</code> directory.
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There are two main categories of parameters that should to be configured: declaration of the
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Swift driver and the parameters that are required by Keystone.
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@@ -100,7 +100,7 @@ contains a list of Keystone mandatory parameters. <code>PROVIDER</code> can be a
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</table>
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For example, assume <code>PROVIDER=SparkTest</code> and Keystone contains user <code>tester</code> with password <code>testing</code>
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defined for tenant <code>test</code>. Than <code>core-sites.xml</code> should include:
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defined for tenant <code>test</code>. Than <code>core-site.xml</code> should include:
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{% highlight xml %}
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<configuration>
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<code>fs.swift.service.PROVIDER.tenant</code>,
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<code>fs.swift.service.PROVIDER.username</code>,
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<code>fs.swift.service.PROVIDER.password</code> contains sensitive information and keeping them in
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<code>core-sites.xml</code> is not always a good approach.
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We suggest to keep those parameters in <code>core-sites.xml</code> for testing purposes when running Spark
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<code>core-site.xml</code> is not always a good approach.
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We suggest to keep those parameters in <code>core-site.xml</code> for testing purposes when running Spark
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via <code>spark-shell</code>.
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For job submissions they should be provided via <code>sparkContext.hadoopConfiguration</code>.

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