15

If I have a Scala paragraph with a DataFrame, can I share and use that with python. (As I understand it pyspark uses py4j)

I tried this:

Scala paragraph:

x.printSchema
z.put("xtable", x )

Python paragraph:

%pyspark

import numpy as np
import pandas as pd

import matplotlib.pyplot as plt
import seaborn as sns

the_data = z.get("xtable")

print the_data

sns.set()
g = sns.PairGrid(data=the_data,
                 x_vars=dependent_var,
                 y_vars=sensor_measure_columns_names +  operational_settings_columns_names,
                 hue="UnitNumber", size=3, aspect=2.5)
g = g.map(plt.plot, alpha=0.5)
g = g.set(xlim=(300,0))
g = g.add_legend()

Error :

Traceback (most recent call last):
  File "/tmp/zeppelin_pyspark.py", line 222, in <module>
    eval(compiledCode)
  File "<string>", line 15, in <module>
  File "/usr/local/lib/python2.7/dist-packages/seaborn/axisgrid.py", line 1223, in __init__
    hue_names = utils.categorical_order(data[hue], hue_order)
TypeError: 'JavaObject' object has no attribute '__getitem__'

Solution:

%pyspark

import numpy as np
import pandas as pd

import matplotlib.pyplot as plt
import seaborn as sns

import StringIO
def show(p):
    img = StringIO.StringIO()
    p.savefig(img, format='svg')
    img.seek(0)
    print "%html <div style='width:600px'>" + img.buf + "</div>"

df = sqlContext.table("fd").select()
df.printSchema
pdf = df.toPandas()

g = sns.pairplot(data=pdf,
                 x_vars=["setting1","setting2"],
                 y_vars=["s4", "s3", 
                         "s9", "s8", 
                         "s13", "s6"],
                 hue="id", aspect=2)
show(g)   

cluster visualisation

oluies
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1 Answers1

28

You can register DataFrame as a temporary table in Scala:

// registerTempTable in Spark 1.x
df.createTempView("df")

and read it in Python with SQLContext.table:

df = sqlContext.table("df")

If you really want to use put / get you'll have build Python DataFrame from scratch:

z.put("df", df: org.apache.spark.sql.DataFrame)
from pyspark.sql import DataFrame

df = DataFrame(z.get("df"), sqlContext)

To plot with matplotlib you'll have convert DataFrame to a local Python object with either collect or toPandas:

pdf = df.toPandas()

Please note that it will fetch data to the driver.

See also moving Spark DataFrame from Python to Scala whithn Zeppelin

zero323
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  • When using Spark 1.6.0 or previous, you need to explicitly declare a new SQLContext for each language you use. Infact, due to [SPARK-13180](https://issues.apache.org/jira/browse/SPARK-13180) bug, the HiveContext created by Zeppelin at startup is not working. In this case the only way I found to share DataFrame across Python and Scala is to put the Dataframe reference itself in the Zeppelin context from Scala and recover it from Python with `DataFrame(z.get("df"), sqlContext)`. – Ameba Spugnosa Jan 03 '17 at 13:45
  • by creating any temptable you can access it in `%sql` – Junaid May 24 '17 at 05:54