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Adds Python refreshTable snippet
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docs/sql-programming-guide.md

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@@ -1271,6 +1271,15 @@ sqlContext.refreshTable("my_table")
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</div>
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<div data-lang="python" markdown="1">
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{% highlight python %}
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# sqlContext is an existing HiveContext
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sqlContext.refreshTable("my_table")
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{% endhighlight %}
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</div>
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<div data-lang="sql" markdown="1">
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{% highlight sql %}
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on all of the worker nodes, as they will need access to the Hive serialization and deserialization libraries
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(SerDes) in order to access data stored in Hive.
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Configuration of Hive is done by placing your `hive-site.xml` file in `conf/`. Please note when running
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the query on a YARN cluster (`yarn-cluster` mode), the `datanucleus` jars under the `lib_managed/jars` directory
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Configuration of Hive is done by placing your `hive-site.xml` file in `conf/`. Please note when running
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the query on a YARN cluster (`yarn-cluster` mode), the `datanucleus` jars under the `lib_managed/jars` directory
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and `hive-site.xml` under `conf/` directory need to be available on the driver and all executors launched by the
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YARN cluster. The convenient way to do this is adding them through the `--jars` option and `--file` option of the
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`spark-submit` command.
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#### DataFrame data reader/writer interface
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Based on user feedback, we created a new, more fluid API for reading data in (`SQLContext.read`)
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and writing data out (`DataFrame.write`),
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and writing data out (`DataFrame.write`),
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and deprecated the old APIs (e.g. `SQLContext.parquetFile`, `SQLContext.jsonFile`).
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See the API docs for `SQLContext.read` (

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