Details
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Bug
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Status: Open
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Major
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Resolution: Unresolved
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0.8.1
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None
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None
Description
I am currently trying to generate visualizations in zeppelin (0.8.1) notebooks using the pyspark interpreter with python 3.7.3.
Generating the following simple plot with seaborn (0.9.0) takes around 5 minutes (with very high CPU usage throughout the duration):
%pyspark
import seaborn as sns
import numpy as np
import pandas as pddata = pd.DataFrame(np.random.rand(100,3))
sns.pairplot(data)
This behavior is rather inconsistent as the following (much more data intensive) plot is rendered instantly
%pyspark
import seaborn as sns
import numpy as np
import pandas as pddf = pd.DataFrame(data = np.random.rand(10000,2))
sns.lineplot(x = 0, y = 1, data = df)
I noticed that using matplotlib (3.1.0) is generally much faster for and almost as snappy as I am used to from jupyter notebook environments.
I have already read about issue [ZEPPELIN-1894|https://jira.apache.org/jira/browse/ZEPPELIN-1894] but I can render the mentioned scatterplot instantly as well.
I already stated my question on StackOverflow but I think here is a better place: