我在*上遇到了自己的问题(how to load a dataframe from a python requests stream that is downloading a csv file?),已经取得了一些进展,但是我收到了*错误：

import requests
import numpy as np
import pandas as pd

import sys
if sys.version_info[0] < 3: 
    from StringIO import StringIO
else:
    from io import StringIO

from pyspark.sql import SQLContext
sqlContext = SQLContext(sc)

chunk_size = 1024

url = "https://{0}:8443/gateway/default/webhdfs/v1/{1}?op=OPEN".format(host, filepath)

r = requests.get(url, auth=(username, password), 
                 verify=False, allow_redirects=True, 
                 stream=True)

df = None
curr_line = 1
remainder = ''
for chunk in r.iter_content(chunk_size):
    txt = remainder + chunk
    [lines, remainder] = txt.rsplit('\n', 1)

    pdf = pd.read_csv(StringIO(lines), sep='|', header=None)

    if df == None:
        df = sqlContext.createDataFrame(pdf)
    else:
        df = df.unionAll(sqlContext.createDataFrame(pdf))

print df.count()

堆栈跟踪在这里：

---------------------------------------------------------------------------
Py4JJavaError                             Traceback (most recent call last)
<ipython-input-4-b3a89df3c7d8> in <module>()
     36         df = sqlContext.createDataFrame(pdf)
     37     else:
---> 38         df = df.unionAll(sqlContext.createDataFrame(pdf))
     39 
     40     #curr_line = curr_line + 1

/usr/local/src/spark160master/spark/python/pyspark/sql/dataframe.py in unionAll(self, other)
    993         This is equivalent to `UNION ALL` in SQL.
    994         """
--> 995         return DataFrame(self._jdf.unionAll(other._jdf), self.sql_ctx)
    996 
    997     @since(1.3)

/usr/local/src/spark160master/spark/python/lib/py4j-0.9-src.zip/py4j/java_gateway.py in __call__(self, *args)
    811         answer = self.gateway_client.send_command(command)
    812         return_value = get_return_value(
--> 813             answer, self.gateway_client, self.target_id, self.name)
    814 
    815         for temp_arg in temp_args:

/usr/local/src/spark160master/spark/python/pyspark/sql/utils.py in deco(*a, **kw)
     43     def deco(*a, **kw):
     44         try:
---> 45             return f(*a, **kw)
     46         except py4j.protocol.Py4JJavaError as e:
     47             s = e.java_exception.toString()

/usr/local/src/spark160master/spark/python/lib/py4j-0.9-src.zip/py4j/protocol.py in get_return_value(answer, gateway_client, target_id, name)
    306                 raise Py4JJavaError(
    307                     "An error occurred while calling {0}{1}{2}.\n".
--> 308                     format(target_id, ".", name), value)
    309             else:
    310                 raise Py4JError(

Py4JJavaError: An error occurred while calling o19563.unionAll.
: java.lang.*Error

我不确定如何解决此问题.任何提示表示赞赏.

解决方法:

您不应该在不控制分区数量的情况下迭代地合并分布式数据结构.您会找到一个完整的解释,说明* due to long RDD Lineage中发生了什么,但是不幸的是DataFrames有点棘手：

dfs = ... # A list of pyspark.sql.DataFrame

def unionAll(*dfs):
    if not dfs:
        raise ValueError()
    first = dfs[0]
    return df.sql_ctx.createDataFrame(
        df._sc.union([df.rdd for df in dfs]), first.schema
    )

unionAll(*dfs)