[英]OSError: [WinError 123] The filename, directory name, or volume label syntax is incorrect
[英]Jupyter Notebook PySpark OSError [WinError 123] The filename, directory name, or volume label syntax is incorrect:
系統配置:操作系統:Windows 10 Python版本:3.7 Spark版本:2.4.4 SPARK_HOME:C:\spark\spark-2.4.4-bin-hadoop2.7
問題我正在使用 PySpark 對數據幀中一行的所有列進行並行計算。 我將 Pandas Dataframe 轉換為 Spark Dataframe。 在 spark 數據幀上,執行地圖轉換和收集操作。 同時,執行收集操作時會彈出帶有 OSError 的 Py4J 錯誤。 錯誤出現在 import sklearn 語句和經過訓練的分類器(ML 模型)中。
代碼片段
from sklearn.neural_network.multilayer_perceptron import MLPClassifier
classifier=MLPClassifier()
classifier.fit(x_train, y_train)
def func1(rows,trained_model=classifier):
items = rows.asDict()
row = pd.Series(items)
output = func2(row,trained_model) # Consumes pandas series in other file having import sklearn statement
return output
spdf=spark.createDataFrame(pandasDF)
result=spdf.rdd.map(lambda row:func1(row)).collect()
錯誤
---------------------------------------------------------------------------
Py4JJavaError Traceback (most recent call last)
<ipython-input-33-0bfb9d088e2d> in <module>
----> 1 result=spdf.rdd.map(lambda row:clusterCreation(row)).collect()
2 print(type(result))
.
.
.
Py4JJavaError: An error occurred while calling z:org.apache.spark.api.python.PythonRDD.collectAndServe.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 2 in stage 2.0 failed 1 times, most recent failure: Lost task 2.0 in stage 2.0 (TID 5, localhost, executor driver): org.apache.spark.api.python.PythonException: Traceback (most recent call last):
File "C:\spark\spark-2.4.4-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\worker.py", line 364, in main
File "C:\spark\spark-2.4.4-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\worker.py", line 71, in read_command
File "C:\spark\spark-2.4.4-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\serializers.py", line 580, in loads
return pickle.loads(obj, encoding=encoding)
.
.
.
File "C:\Users\rkagr\Anaconda3\lib\site-packages\sklearn\ensemble\__init__.py", line 7, in <module>
from .forest import RandomForestClassifier
File "C:\Users\rkagr\Anaconda3\lib\site-packages\sklearn\ensemble\forest.py", line 53, in <module>
from ..metrics import r2_score
File "C:\Users\rkagr\Anaconda3\lib\site-packages\sklearn\metrics\__init__.py", line 7, in <module>
from .ranking import auc
File "C:\Users\rkagr\Anaconda3\lib\site-packages\sklearn\metrics\ranking.py", line 35, in <module>
from ..preprocessing import label_binarize
File "C:\Users\rkagr\Anaconda3\lib\site-packages\sklearn\preprocessing\__init__.py", line 6, in <module>
from ._function_transformer import FunctionTransformer
File "C:\Users\rkagr\Anaconda3\lib\site-packages\sklearn\preprocessing\_function_transformer.py", line 5, in <module>
from ..utils.testing import assert_allclose_dense_sparse
File "C:\Users\rkagr\Anaconda3\lib\site-packages\sklearn\utils\testing.py", line 718, in <module>
import pytest
File "C:\Users\rkagr\Anaconda3\lib\site-packages\pytest.py", line 6, in <module>
from _pytest.assertion import register_assert_rewrite
File "C:\Users\rkagr\Anaconda3\lib\site-packages\_pytest\assertion\__init__.py", line 6, in <module>
from _pytest.assertion import rewrite
File "C:\Users\rkagr\Anaconda3\lib\site-packages\_pytest\assertion\rewrite.py", line 20, in <module>
from _pytest.assertion import util
File "C:\Users\rkagr\Anaconda3\lib\site-packages\_pytest\assertion\util.py", line 5, in <module>
import _pytest._code
File "C:\Users\rkagr\Anaconda3\lib\site-packages\_pytest\_code\__init__.py", line 2, in <module>
from .code import Code # noqa
File "C:\Users\rkagr\Anaconda3\lib\site-packages\_pytest\_code\code.py", line 11, in <module>
import pluggy
File "C:\Users\rkagr\Anaconda3\lib\site-packages\pluggy\__init__.py", line 16, in <module>
from .manager import PluginManager, PluginValidationError
File "C:\Users\rkagr\Anaconda3\lib\site-packages\pluggy\manager.py", line 6, in <module>
import importlib_metadata
File "C:\Users\rkagr\Anaconda3\lib\site-packages\importlib_metadata\__init__.py", line 466, in <module>
__version__ = version(__name__)
File "C:\Users\rkagr\Anaconda3\lib\site-packages\importlib_metadata\__init__.py", line 433, in version
return distribution(package).version
File "C:\Users\rkagr\Anaconda3\lib\site-packages\importlib_metadata\__init__.py", line 406, in distribution
return Distribution.from_name(package)
File "C:\Users\rkagr\Anaconda3\lib\site-packages\importlib_metadata\__init__.py", line 176, in from_name
dist = next(dists, None)
File "C:\Users\rkagr\Anaconda3\lib\site-packages\importlib_metadata\__init__.py", line 362, in <genexpr>
for path in map(cls._switch_path, paths)
File "C:\Users\rkagr\Anaconda3\lib\site-packages\importlib_metadata\__init__.py", line 377, in _search_path
if not root.is_dir():
File "C:\Users\rkagr\Anaconda3\lib\pathlib.py", line 1351, in is_dir
return S_ISDIR(self.stat().st_mode)
File "C:\Users\rkagr\Anaconda3\lib\pathlib.py", line 1161, in stat
return self._accessor.stat(self)
OSError: [WinError 123] The filename, directory name, or volume label syntax is incorrect: 'C:\\C:\\spark\\spark-2.4.4-bin-hadoop2.7\\jars\\spark-core_2.11-2.4.4.jar'
MCVE這個 MCVE 定義函數只返回與字典相同的輸入行,而原始代碼在一些處理后返回字典。
import findspark
findspark.init()
findspark.find()
import pyspark
from pyspark import SparkContext, SparkConf
from pyspark.sql import SparkSession
conf = SparkConf().setAppName('MRC').setMaster('local[2]')
sc = SparkContext.getOrCreate(conf=conf)
spark = SparkSession.builder.getOrCreate()
import sklearn
import sklearn.datasets
import sklearn.model_selection
import sklearn.ensemble
iris = sklearn.datasets.load_iris()
train, test, labels_train, labels_test = sklearn.model_selection.train_test_split(iris.data, iris.target, train_size=0.80)
classifier = sklearn.ensemble.RandomForestClassifier()
classifier.fit(train, labels_train)
import pickle
path = './random_classifier.mdl'
pickle.dump(classifier, open(path,'wb'))
import pandas as pd
pddf=pd.DataFrame(test)
spdf=spark.createDataFrame(pddf)
def clusterCreation(rows,classifier_path):
items = rows.asDict()
row = pd.Series(items)
with open(classifier_path,'rb') as fp:
classifier = pickle.load(fp)
print(classifier)
return items
result=spdf.rdd.map(lambda row:clusterCreation(row,classifier_path=path)).collect()
print(result)
我遇到了包含C:\\C:\\
的文件路徑的相同問題。 我在https://github.com/Ibotta/sk-dist/issues/30中發現了一個討論,它表明這可能是scikit-learn
中使用的pytest
的問題。 scikit-learn
版本 0.21.3 中報告了該問題。 我將我的scikit-learn
包升級到 0.22.1(通過升級到 Anaconda 2020.02),錯誤消失了。
我的環境是 Windows 10、Spark 2.4.5、Anaconda 2020.02(其中包含 scikit-learn 0.22.1)。 請注意,較舊的 Anaconda 版本 2019.10 包含scikit-learn
版本 0.21.3。
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