【发布时间】：2018-08-16 11:37:33
【问题描述】：
我正在尝试将网站名称与 URL 分开。例如 - 如果 URL 是 www.google.com，则输出应该是“google”。我尝试了下面的代码，除了最后一行 - “websites.collect()”，一切正常。
我使用数据框来存储网站名称，然后将其转换为 rdd 并对值应用拆分函数以获得所需的输出。
逻辑似乎没问题，但我猜我的包配置和安装有一些错误。
错误如下图：-
---------------------------------------------------------------------------
Py4JJavaError Traceback (most recent call last)
<ipython-input-11-a88287400951> in <module>()
----> 1 websites.collect()
C:\ProgramData\Anaconda3\lib\site-packages\pyspark\rdd.py in collect(self)
822 """
823 with SCCallSiteSync(self.context) as css:
--> 824 port = self.ctx._jvm.PythonRDD.collectAndServe(self._jrdd.rdd())
825 return list(_load_from_socket(port, self._jrdd_deserializer))
826
C:\ProgramData\Anaconda3\lib\site-packages\py4j\java_gateway.py in __call__(self, *args)
1158 answer = self.gateway_client.send_command(command)
1159 return_value = get_return_value(
-> 1160 answer, self.gateway_client, self.target_id, self.name)
1161
1162 for temp_arg in temp_args:
C:\ProgramData\Anaconda3\lib\site-packages\pyspark\sql\utils.py in deco(*a, **kw)
61 def deco(*a, **kw):
62 try:
---> 63 return f(*a, **kw)
64 except py4j.protocol.Py4JJavaError as e:
65 s = e.java_exception.toString()
C:\ProgramData\Anaconda3\lib\site-packages\py4j\protocol.py in get_return_value(answer, gateway_client, target_id, name)
318 raise Py4JJavaError(
319 "An error occurred while calling {0}{1}{2}.\n".
--> 320 format(target_id, ".", name), value)
321 else:
322 raise Py4JError(
Py4JJavaError: An error occurred while calling z:org.apache.spark.api.python.PythonRDD.collectAndServe.
: java.lang.IllegalArgumentException
at org.apache.xbean.asm5.ClassReader.<init>(Unknown Source)
at org.apache.xbean.asm5.ClassReader.<init>(Unknown Source)
at org.apache.xbean.asm5.ClassReader.<init>(Unknown Source)
at org.apache.spark.util.ClosureCleaner$.getClassReader(ClosureCleaner.scala:46)
at org.apache.spark.util.FieldAccessFinder$$anon$3$$anonfun$visitMethodInsn$2.apply(ClosureCleaner.scala:449)
at org.apache.spark.util.FieldAccessFinder$$anon$3$$anonfun$visitMethodInsn$2.apply(ClosureCleaner.scala:432)
at scala.collection.TraversableLike$WithFilter$$anonfun$foreach$1.apply(TraversableLike.scala:733)
at scala.collection.mutable.HashMap$$anon$1$$anonfun$foreach$2.apply(HashMap.scala:103)
at scala.collection.mutable.HashMap$$anon$1$$anonfun$foreach$2.apply(HashMap.scala:103)
at scala.collection.mutable.HashTable$class.foreachEntry(HashTable.scala:230)
at scala.collection.mutable.HashMap.foreachEntry(HashMap.scala:40)
at scala.collection.mutable.HashMap$$anon$1.foreach(HashMap.scala:103)
at scala.collection.TraversableLike$WithFilter.foreach(TraversableLike.scala:732)
at org.apache.spark.util.FieldAccessFinder$$anon$3.visitMethodInsn(ClosureCleaner.scala:432)
at org.apache.xbean.asm5.ClassReader.a(Unknown Source)
at org.apache.xbean.asm5.ClassReader.b(Unknown Source)
at org.apache.xbean.asm5.ClassReader.accept(Unknown Source)
at org.apache.xbean.asm5.ClassReader.accept(Unknown Source)
at org.apache.spark.util.ClosureCleaner$$anonfun$org$apache$spark$util$ClosureCleaner$$clean$14.apply(ClosureCleaner.scala:262)
at org.apache.spark.util.ClosureCleaner$$anonfun$org$apache$spark$util$ClosureCleaner$$clean$14.apply(ClosureCleaner.scala:261)
at scala.collection.immutable.List.foreach(List.scala:381)
at org.apache.spark.util.ClosureCleaner$.org$apache$spark$util$ClosureCleaner$$clean(ClosureCleaner.scala:261)
at org.apache.spark.util.ClosureCleaner$.clean(ClosureCleaner.scala:159)
at org.apache.spark.SparkContext.clean(SparkContext.scala:2292)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2066)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2092)
at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:939)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:363)
at org.apache.spark.rdd.RDD.collect(RDD.scala:938)
at org.apache.spark.api.python.PythonRDD$.collectAndServe(PythonRDD.scala:153)
at org.apache.spark.api.python.PythonRDD.collectAndServe(PythonRDD.scala)
at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(Unknown Source)
at java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(Unknown Source)
at java.base/java.lang.reflect.Method.invoke(Unknown Source)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:282)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:214)
at java.base/java.lang.Thread.run(Unknown Source)
代码：-
from pyspark import SparkConf, SparkContext
conf = (SparkConf()
.setMaster("local[*]")
.setAppName("Test")
.set("spark.executor.memory", "8g")
)
sc = SparkContext(conf = conf)
from pyspark.sql import SQLContext
sqlContext = SQLContext(sc)
schemaWebsite = sc.parallelize([
(0, "www.google.com"), (1, "www.hackerrank.com"),(2, "www.walmart.com/in"),
(3, "www.amazon.in"),(4, "www.ndtv.com")]).toDF(["id", "ev"])
websites = schemaWebsite.rdd.map(lambda x : x[1].split(".")[1])
websites.collect()
【问题讨论】：
-
看来spark配置有问题。你能打印 sc._conf.getAll() 的输出吗
-
[('spark.executor.memory', '16g'), ('spark.driver.host', '.......'), ('spark.driver .port', '52092'), ('spark.rdd.compress', 'True'), ('spark.app.name', 'Test'), ('spark.serializer.objectStreamReset', '100') , ('spark.master', 'local[*]'), ('spark.executor.id', 'driver'), ('spark.submit.deployMode', 'client'), ('spark.app. id', 'local-1520492861811'), ('spark.ui.showConsoleProgress', 'true')] 以上是输出。我没有分享“spark.driver.host”.....
-
你的 spark 和 java 版本是多少。尝试将 JAVA_HOME 设置为 Java 1.8 一次。
标签： python apache-spark pyspark rdd