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<h1>Parallel <span style="font-variant:small-caps">Secondo</span> Using Hadoop</h2>

Starting with release 3.3, it is possible to use <span style="font-variant:small-caps">Secondo</span> for parallel processing of queries.
Hadoop needs to be installed together with <span style="font-variant:small-caps">Secondo</span>. Queries in <span style="font-variant:small-caps">Secondo</span>'s executable language can be embedded into Hadoop Map or Reduce steps. Essentially Hadoop is used as a distributed operating system that assigns tasks to <span style="font-variant:small-caps">Secondo</span> instances on different computers and supervises their execution. This approach, as is known for the MapReduce approach, is highly fault-tolerant and suitable for large networks of hundreds of computers.
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Parallel queries can be formulated in one <span style="font-variant:small-caps">Secondo</span> system as a query in executable language containing hadoopMap and hadoopReduce operations.


The following documentation is available:

<ul>
  <li> <a href="../papers/PSexample.pdf">Example: How to Write Parallel Queries in Parallel Secondo</a></li>
  <li> <a href="../papers/PSUserGuide.pdf">User Guide For Parallel Secondo</a></li>
  <li>J. Lu and R.H. G&uuml;ting, <a href="../papers/CouplingHadoop366.pdf">Simple and Efficient Coupling of Hadoop With a Database Engine.</a> Fernuniversit&auml;t in Hagen, Informatik-Report 366 - 10/2012.</li>
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  Last Changed: 2012-11-10
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