Geoip2的Python库不pySpark的地图功能工作 [英] Geoip2's python library doesn't work in pySpark's map function

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问题描述

我使用geoip2的Python库和pySpark得到一些IP地址的地理地址。我的code是这样的:

I'm using geoip2's python library and pySpark to get the geographical address of some IPs. My code is like:

geoDBpath = 'somePath/geoDB/GeoLite2-City.mmdb'
geoPath = os.path.join(geoDBpath)
sc.addFile(geoPath)
reader = geoip2.database.Reader(SparkFiles.get(geoPath))
def ip2city(ip):
    try:
        city = reader.city(ip).city.name
    except:
        city = 'not found'
    return city

我试过

print ip2city("128.101.101.101")

它的工作原理。
但是,当我试图做这rdd.map:

It works. But when I tried to do this in rdd.map:

rdd = sc.parallelize([ip1, ip2, ip3, ip3, ...])
print rdd.map(lambda x: ip2city(x))

据报道

    Traceback (most recent call last):
  File "/home/worker/software/spark/python/pyspark/rdd.py", line 1299, in take
    res = self.context.runJob(self, takeUpToNumLeft, p)
  File "/home/worker/software/spark/python/pyspark/context.py", line 916, in runJob
    port = self._jvm.PythonRDD.runJob(self._jsc.sc(), mappedRDD._jrdd, partitions)
  File "/home/worker/software/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/java_gateway.py", line 538, in __call__
  File "/home/worker/software/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/protocol.py", line 300, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling z:org.apache.spark.api.python.PythonRDD.runJob.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 1.0 failed 1 times, most recent failure: Lost task 0.0 in stage 1.0 (TID 1, localhost): org.apache.spark.api.python.PythonException: Traceback (most recent call last):
  File "/home/worker/software/spark/python/lib/pyspark.zip/pyspark/worker.py", line 98, in main
    command = pickleSer._read_with_length(infile)
  File "/home/worker/software/spark/python/lib/pyspark.zip/pyspark/serializers.py", line 164, in _read_with_length
    return self.loads(obj)
  File "/home/worker/software/spark/python/lib/pyspark.zip/pyspark/serializers.py", line 422, in loads
    return pickle.loads(obj)
TypeError: Required argument 'fileno' (pos 1) not found

    at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:166)
    at org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:207)
    at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:125)
    at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:70)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:264)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
    at org.apache.spark.scheduler.Task.run(Task.scala:88)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
    at java.lang.Thread.run(Thread.java:745)

可以在任何一个可以告诉我如何在rdd.map的ip2city功能工作()。
谢谢!

Could any one tell my how to make the ip2city function work in rdd.map(). Thanks!

推荐答案

它看起来像你的code中的问题来自于一个对象。它不能作为一个封闭的一部分,正确的序列化,发送到workers.To处理这个你必须初始化它的工人。你可以处理这个问题的方法之一是使用 mapPartitions

It looks like the problem with your code comes from a reader object. It cannot be correctly serialized as a part of a closure and send to the workers.To deal with this you have instantiate it on the workers. One way you can handle this is to use mapPartitions:

from pyspark import SparkFiles

geoDBpath = 'GeoLite2-City.mmdb'
sc.addFile(geoDBpath)

def partitionIp2city(iter):
    from geoip2 import database

    def ip2city(ip):
        try:
           city = reader.city(ip).city.name
        except:
            city = 'not found'
        return city

    reader = database.Reader(SparkFiles.get(geoDBpath))
    return [ip2city(ip) for ip in iter]

rdd = sc.parallelize(['128.101.101.101', '85.25.43.84'])
rdd.mapPartitions(partitionIp2city).collect()

## ['Minneapolis', None]

这篇关于Geoip2的Python库不pySpark的地图功能工作的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持IT屋!

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