我在PySpark中有一个dataFrame。我想将StringIndexer用于标签列，因此我将函数定义为：
def indexer(column, dataframe):
from pyspark.ml.feature import StringIndexer
# Indexing the column
stringIndexer = StringIndexer(inputCol=column, outputCol='categoryIndex')
model = stringIndexer.fit(dataframe)
indexed = model.transform(dataframe)
return indexed
enc = indexer('y', df)
print(enc)
我定义了Spark会话，并将dataFrame读取为：
spark = pyspark.sql.SparkSession.builder.appName("example")\
.master("local[*]").getOrCreate()
和
df = spark.read.format("csv").option("header","true")\
.option("sep",";").load('bank-additional-full.csv')
我有运行正常的Spark版本2.3.0：
$pyspark
Python 3.5.2 (default, Oct 8 2019, 13:06:37)
[GCC 5.4.0 20160609] on linux
Type "help", "copyright", "credits" or "license" for more information.
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
Welcome to
____ __
/ __/__ ___ _____/ /__
_\ \/ _ \/ _ `/ __/ '_/
/__ / .__/\_,_/_/ /_/\_\ version 2.3.0
/_/
Using Python version 3.5.2 (default, Oct 8 2019 13:06:37)
SparkSession available as 'spark'.
>>>
我的Java版本是：
$java -version
openjdk version "1.8.0_242"
OpenJDK Runtime Environment (build 1.8.0_242-8u242-b08-0ubuntu3~16.04-b08)
OpenJDK 64-Bit Server VM (build 25.242-b08, mixed mode)
但是，运行代码后，出现以下错误：
Traceback (most recent call last):
File "/home/saeidsoheily/Desktop/Python codeS/baseLines/pyspark_logisticRegression.py", line 56, in <module>
enc = one_hot_encode('job', df)
File "/home/saeidsoheily/Desktop/Python codeS/baseLines/pyspark_logisticRegression.py", line 50, in one_hot_encode
model = stringIndexer.fit(dataframe)
File "/usr/local/lib/python3.5/dist-packages/pyspark/ml/base.py", line 132, in fit
return self._fit(dataset)
File "/usr/local/lib/python3.5/dist-packages/pyspark/ml/wrapper.py", line 288, in _fit
java_model = self._fit_java(dataset)
File "/usr/local/lib/python3.5/dist-packages/pyspark/ml/wrapper.py", line 285, in _fit_java
return self._java_obj.fit(dataset._jdf)
File "/usr/local/lib/python3.5/dist-packages/py4j/java_gateway.py", line 1160, in __call__
answer, self.gateway_client, self.target_id, self.name)
File "/usr/local/lib/python3.5/dist-packages/pyspark/sql/utils.py", line 63, in deco
return f(*a, **kw)
File "/usr/local/lib/python3.5/dist-packages/py4j/protocol.py", line 320, in get_return_value
format(target_id, ".", name), value)
py4j.protocol.Py4JJavaError: An error occurred while calling o45.fit.
: java.lang.IllegalArgumentException
at org.apache.xbean.asm5.ClassReader.<init>(Unknown Source)
at org.apache.xbean.asm5.ClassReader.<init>(Unknown Source)
at org.apache.xbean.asm5.ClassReader.<init>(Unknown Source)
at org.apache.spark.util.ClosureCleaner$.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$$anonfun$collect$1.apply(RDD.scala:939)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:363)
at org.apache.spark.rdd.RDD.collect(RDD.scala:938)
at org.apache.spark.rdd.PairRDDFunctions$$anonfun$countByKey$1.apply(PairRDDFunctions.scala:370)
at org.apache.spark.rdd.PairRDDFunctions$$anonfun$countByKey$1.apply(PairRDDFunctions.scala:370)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:363)
at org.apache.spark.rdd.PairRDDFunctions.countByKey(PairRDDFunctions.scala:369)
at org.apache.spark.rdd.RDD$$anonfun$countByValue$1.apply(RDD.scala:1208)
at org.apache.spark.rdd.RDD$$anonfun$countByValue$1.apply(RDD.scala:1208)
at org.apache.spark.rdd.RDDOperationScope$.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.countByValue(RDD.scala:1207)
at org.apache.spark.ml.feature.StringIndexer.fit(StringIndexer.scala:140)
at org.apache.spark.ml.feature.StringIndexer.fit(StringIndexer.scala:109)
at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.base/java.lang.reflect.Method.invoke(Method.java:564)
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(Thread.java:844)
Process finished with exit code 1
有什么办法解决吗？
答案 0 :(得分：-3)
您的错误消息清楚地表明传递的参数存在问题
py4j.protocol.Py4JJavaError: An error occurred while calling o45.fit.
: java.lang.IllegalArgumentException
检查specification并验证代码。它采用4个参数，但您仅传递了2个。