Alberto Bonsanto created SPARK-11992:
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Summary: Severl numbers in my spark shell (pyspark)
Key: SPARK-11992
URL: https://issues.apache.org/jira/browse/SPARK-11992
Project: Spark
Issue Type: Question
Components: MLlib, PySpark
Affects Versions: 1.5.2
Environment: Linux Ubuntu 14.04 LTS
Jupyter
Spark 1.5.2
Reporter: Alberto Bonsanto
Priority: Blocker
The problem is very weird, I am currently trying to fit some classifiers from
mllib library (SVM, LogisticRegression, RandomForest, DecisionTree and
NaiveBayes), so they might classify the data properly, I am trying to compare
their performances evaluating their predictions using my current validation
data (the typical pipeline), and the problem is that when I try to fit any of
those, my spark-shell console prints millions and millions of entries, and
after that the fitting process gets stopped, you can see it
[here|http://i.imgur.com/mohLnwr.png]
Some details:
- My data has around 15M of entries.
- I use LabeledPoints to represent each entry, where the features are
SparseVectors and they have *104* features or dimensions.
- I don't show many things in the console,
[log4j.properties|https://gist.github.com/Bonsanto/c487624db805f56882b8]
- The program is running locally in a computer with 16GB of RAM.
I have already asked this, in StackOverflow, you can see it here [Crazy
print|http://stackoverflow.com/questions/33807347/pyspark-shell-outputs-several-numbers-instead-of-the-loading-arrow]
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