如果我有一个带有DataFrame的Scala段落,我可以与python共享和使用它. (据我所知,pyspark使用py4j)

我试过这个：

斯卡拉段落：

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

Python段落：

%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()

错误：

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__'

解：

%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)   

解决方法:

您可以在Scala中将DataFrame注册为临时表：

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

并使用SQLContext.table在Python中读取它：

df = sqlContext.table("df")

如果你真的想使用put / get,你将从头开始构建Python DataFrame：

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

from pyspark.sql import DataFrame

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

要使用matplotlib绘图,您将使用collect或toPandas将DataFrame转换为本地Python对象：

pdf = df.toPandas()

请注意,它会将数据提取给驱动程序.

另见moving Spark DataFrame from Python to Scala whithn Zeppelin