将pandas数据帧转换为zeppelin中的spark数据帧

Question

我是齐柏林飞艇的新手.我有一个用例,其中我有一个pandas数据帧.我需要使用zeppelin的内置图表来可视化集合我在这里没有明确的方法.我的理解是使用zeppelin,如果它是RDD格式,我们可以将数据可视化.所以,我想将pandas dataframe转换为spark数据帧,然后进行一些查询(使用sql),我会想象.首先,我试图将pandas数据帧转换为spark,但我失败了

%pyspark
import pandas as pd
from pyspark.sql import SQLContext
print sc
df = pd.DataFrame([("foo", 1), ("bar", 2)], columns=("k", "v"))
print type(df)
print df
sqlCtx = SQLContext(sc)
sqlCtx.createDataFrame(df).show()

我得到了以下错误

Traceback (most recent call last): File "/tmp/zeppelin_pyspark.py", 
line 162, in <module> eval(compiledCode) File "<string>", 
line 8, in <module> File "/home/bala/Software/spark-1.5.0-bin-hadoop2.6/python/pyspark/sql/context.py", 
line 406, in createDataFrame rdd, schema = self._createFromLocal(data, schema) File "/home/bala/Software/spark-1.5.0-bin-hadoop2.6/python/pyspark/sql/context.py", 
line 322, in _createFromLocal struct = self._inferSchemaFromList(data) File "/home/bala/Software/spark-1.5.0-bin-hadoop2.6/python/pyspark/sql/context.py", 
line 211, in _inferSchemaFromList schema = _infer_schema(first) File "/home/bala/Software/spark-1.5.0-bin-hadoop2.6/python/pyspark/sql/types.py", 
line 829, in _infer_schema raise TypeError("Can not infer schema for type: %s" % type(row)) 
TypeError: Can not infer schema for type: <type 'str'> 

有人可以帮帮我吗？如果我在任何地方都错了,请纠正我.

Answer 1

以下适用于Zeppelin 0.6.0,Spark 1.6.2和Python 3.5.2:

%pyspark
import pandas as pd
df = pd.DataFrame([("foo", 1), ("bar", 2)], columns=("k", "v"))
z.show(sqlContext.createDataFrame(df))

其呈现为:

Answer 2

我刚刚将你的代码复制并粘贴在笔记本中,它可以工作.

%pyspark
import pandas as pd
from pyspark.sql import SQLContext
print sc
df = pd.DataFrame([("foo", 1), ("bar", 2)], columns=("k", "v"))
print type(df)
print df
sqlCtx = SQLContext(sc)
sqlCtx.createDataFrame(df).show()

<pyspark.context.SparkContext object at 0x10b0a2b10>
<class 'pandas.core.frame.DataFrame'>
     k  v
0  foo  1
1  bar  2
+---+-+
|  k|v|
+---+-+
|foo|1|
|bar|2|
+---+-+

我正在使用这个版本:zeppelin-0.5.0-incubating-bin-spark-1.4.0_hadoop-2.3.tgz