ODIn/spark-instrumented-optimizer
1
0
Fork 0
Code Issues Pull requests Projects Releases Wiki Activity

Clarify that Python 2.7 is only needed for MLlib

Browse source
This commit is contained in:
Matei Zaharia 2014-01-15 14:20:39 -08:00
parent 59f475c79f
commit 2ffdaefbcb
2 changed files with 4 additions and 3 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

3
docs/mllib-guide.md
View file

@ -21,7 +21,8 @@ depends on native Fortran routines. You may need to install the
if it is not already present on your nodes. MLlib will throw a linking error if it cannot
detect these libraries automatically.
To use MLlib in Python, you will also need [NumPy](http://www.numpy.org) version 1.7 or newer.
To use MLlib in Python, you will need [NumPy](http://www.numpy.org) version 1.7 or newer
and Python 2.7.
# Binary Classification

4
docs/python-programming-guide.md
View file

@ -52,7 +52,7 @@ In addition, PySpark fully supports interactive use---simply run `./bin/pyspark`
# Installing and Configuring PySpark
PySpark requires Python 2.7 or higher.
PySpark requires Python 2.6 or higher.
PySpark applications are executed using a standard CPython interpreter in order to support Python modules that use C extensions.
We have not tested PySpark with Python 3 or with alternative Python interpreters, such as [PyPy](http://pypy.org/) or [Jython](http://www.jython.org/).
@ -152,7 +152,7 @@ Many of the methods also contain [doctests](http://docs.python.org/2/library/doc
# Libraries
[MLlib](mllib-guide.html) is also available in PySpark. To use it, you'll need
[NumPy](http://www.numpy.org) version 1.7 or newer. The [MLlib guide](mllib-guide.html) contains
[NumPy](http://www.numpy.org) version 1.7 or newer, and Python 2.7. The [MLlib guide](mllib-guide.html) contains
some example applications.
# Where to Go from Here