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--- spark:spark-introduction [2014/11/04 09:39]
straka
+++ spark:spark-introduction [2014/11/11 08:57]
straka
@@ Line 7: / Line 7: @@
 To run interactive Python shell in local Spark mode, run (on your local workstation or on cluster)
   IPYTHON=1 pyspark
-The IPYTHON=1 parameter instructs Spark to use ''ipython'' instead of ''python'' (the ''ipython'' is an enhanced interactive shell than Python). If you do not want ''ipython'' or you do not have it installed (it is installed everywhere on the cluster, but maybe not on your local workstations -- ask our IT if you want it), leave out the ''IPYTHON=1''.
+The IPYTHON=1 parameter instructs Spark to use ''ipython'' instead of ''python'' (the ''ipython'' is an enhanced interactive shell than Python). If you do not want ''ipython'' or you do not have it installed (it is installed everywhere on the cluster, but maybe not on your local workstations -- ask our IT if you want it), use only ''pyspark''.
 After a local Spark executor is started, the Python shell starts. Severel lines above
@@ Line 63: / Line 63: @@
 ===== K-Means Example =====
-To show an example of iterative algorithm, consider [[http://en.wikipedia.org/wiki/K-means_clustering|Standard iterative K-Means algorithm]].
+An example implementing [[http://en.wikipedia.org/wiki/K-means_clustering|Standard iterative K-Means algorithm]] follows:
 <file python>
 import numpy as np

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