我从spark nlp中保存了一个预先训练过的模型，然后我正在尝试使用anaconda env在pycharm中运行python脚本：
Model_path = "./xxx"
model = PipelineModel.load(Model_path)但是我得到了以下错误：（我尝试了pyspark 2.4.4&spark-nlp2.4.4，pyspark 2.4.4&spark-nlp2.5.4）得到了相同的错误：
21/02/05 13:31:21 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
Traceback (most recent call last):
File "C:/Users/xxxx/xxxxx.py", line 381, in <module>
model = PipelineModel.load(Model_path)
File "C:\Users\xxxxxxxx\anaconda3\envs\python3.7\lib\site-packages\pyspark\ml\util.py", line 362, in load
return cls.read().load(path)
File "C:\Users\\xxxxxxxx\anaconda3\envs\python3.7\lib\site-packages\pyspark\ml\pipeline.py", line 242, in load
return JavaMLReader(self.cls).load(path)
File "C:\Users\xxxxxxxx\anaconda3\envs\python3.7\lib\site-packages\pyspark\ml\util.py", line 300, in load
java_obj = self._jread.load(path)
File "C:\Users\xxxxxxxx\anaconda3\envs\python3.7\lib\site-packages\py4j\java_gateway.py", line 1257, in __call__
answer, self.gateway_client, self.target_id, self.name)
File "C:\Users\xxxxxxxx\anaconda3\envs\python3.7\lib\site-packages\pyspark\sql\utils.py", line 63, in deco
return f(*a,**kw)
File "C:\Users\xxxxxxxx\anaconda3\envs\python3.7\lib\site-packages\py4j\protocol.py", line 328, in get_return_value
format(target_id, ".", name), value)
py4j.protocol.Py4JJavaError: An error occurred while calling o314.load.
: java.lang.ClassNotFoundException: com.johnsnowlabs.nlp.DocumentAssembler我是pyspark和spark nlp的新手，有人能帮忙吗？
1条答案
按热度按时间ddarikpa1#
先来点背景。spark nlp库依赖于需要存在于spark类路径中的jar文件。根据在pyspark中如何启动上下文，有三种方法可以提供这个jar。a） 通过解释器启动python应用程序时，调用sparknlp.start（），jar将自动下载。
b） 使用--jars开关将jar传递给pyspark命令。在本例中，您从releases页面获取jar并手动下载它。
c） 启动pyspark并传递——包，这里需要传递一个maven坐标，例如，
请检查这里的文件，
https://github.com/johnsnowlabs/spark-nlp#usage
确保你选择了你想要的版本。