[ Skip to the content ]

Institute of Formal and Applied Linguistics Wiki

[ Back to the navigation ]

You are here: start » courses » mapreduce-tutorial » step-15

Differences

This shows you the differences between two versions of the page.

Link to this comparison view

Both sides previous revision Previous revision
Last revision Both sides next revision
courses:mapreduce-tutorial:step-15 [2012/01/26 23:19]
straka 		courses:mapreduce-tutorial:step-15 [2012/01/28 23:23]
majlis Added links to previous and next chapter.
Line 9: Line 9:
 When dealing with iterative algorithms, each iteration is usually implemented as one Hadoop job. The Hadoop input_path contains the input data and each mapper also reads the current clusters. The reducers are used to aggregate the data and output new cluster centers. A controlling script is taking care of executing Hadoop jobs and stopping the iteration when the algorithm converges. When dealing with iterative algorithms, each iteration is usually implemented as one Hadoop job. The Hadoop input_path contains the input data and each mapper also reads the current clusters. The reducers are used to aggregate the data and output new cluster centers. A controlling script is taking care of executing Hadoop jobs and stopping the iteration when the algorithm converges.
  
 +----
 +
 +<html>
 +<table style="width:100%">
 +<tr>
 +<td style="text-align:left; width: 33%; "></html>[[step-14|Step 14]]: N-gram language model.<html></td>
 +<td style="text-align:center; width: 33%; "></html>[[.|Overview]]<html></td>
 +<td style="text-align:right; width: 33%; "></html><html></td>
 +</tr>
 +</table>
 +</html>

[ Back to the navigation ] [ Back to the content ]