I've a "ner_clinical_large" model error on Spark NLP for Healthcare.

[JustHeroo]

I tried to use "ner_clinical_large" model. But I encountered a problem, the error message is as follows.

---

Py4JJavaError Traceback (most recent call last)
in
1 # NER model trained on i2b2 (sampled from MIMIC) dataset
----> 2 clinical_ner = MedicalNerModel.pretrained("ner_clinical_large","en","clinical/models")
3 .setInputCols(["sentence","token","embeddings"])
4 .setOutputCol("ner")

~\Miniconda3\envs\SparkNLP\lib\site-packages\sparknlp_jsl\annotator.py in pretrained(name, lang, remote_loc)
1845 from sparknlp.pretrained import ResourceDownloader
1846 return ResourceDownloader.downloadModel(MedicalNerModel, name, lang, remote_loc,
-> 1847 j_dwn='InternalsPythonResourceDownloader')

~\Miniconda3\envs\SparkNLP\lib\site-packages\sparknlp\pretrained.py in downloadModel(reader, name, language, remote_loc, j_dwn)
39 t1.start()
40 try:
---> 41 j_obj = _internal._DownloadModel(reader.name, name, language, remote_loc, j_dwn).apply()
42 finally:
43 stop_threads = True

~\Miniconda3\envs\SparkNLP\lib\site-packages\sparknlp\internal.py in init(self, reader, name, language, remote_loc, validator)
174 class _DownloadModel(ExtendedJavaWrapper):
175 def init(self, reader, name, language, remote_loc, validator):
--> 176 super(_DownloadModel, self).init("com.johnsnowlabs.nlp.pretrained."+validator+".downloadModel", reader, name, language, remote_loc)
177
178

~\Miniconda3\envs\SparkNLP\lib\site-packages\sparknlp\internal.py in init(self, java_obj, *args)
127 super(ExtendedJavaWrapper, self).init(java_obj)
128 self.sc = SparkContext._active_spark_context
--> 129 self._java_obj = self.new_java_obj(java_obj, *args)
130 self.java_obj = self._java_obj
131

~\Miniconda3\envs\SparkNLP\lib\site-packages\sparknlp\internal.py in new_java_obj(self, java_class, *args)
137
138 def new_java_obj(self, java_class, *args):
--> 139 return self._new_java_obj(java_class, *args)
140
141 def new_java_array(self, pylist, java_class):

~\Miniconda3\envs\SparkNLP\lib\site-packages\pyspark\ml\wrapper.py in _new_java_obj(java_class, *args)
64 java_obj = getattr(java_obj, name)
65 java_args = [_py2java(sc, arg) for arg in args]
---> 66 return java_obj(*java_args)
67
68 @staticmethod

~\Miniconda3\envs\SparkNLP\lib\site-packages\py4j\java_gateway.py in call(self, *args)
1303 answer = self.gateway_client.send_command(command)
1304 return_value = get_return_value(
-> 1305 answer, self.gateway_client, self.target_id, self.name)
1306
1307 for temp_arg in temp_args:

~\Miniconda3\envs\SparkNLP\lib\site-packages\pyspark\sql\utils.py in deco(*a, **kw)
109 def deco(*a, **kw):
110 try:
--> 111 return f(*a, **kw)
112 except py4j.protocol.Py4JJavaError as e:
113 converted = convert_exception(e.java_exception)

~\Miniconda3\envs\SparkNLP\lib\site-packages\py4j\protocol.py in get_return_value(answer, gateway_client, target_id, name)
326 raise Py4JJavaError(
327 "An error occurred while calling {0}{1}{2}.\n".
--> 328 format(target_id, ".", name), value)
329 else:
330 raise Py4JError(

Py4JJavaError: An error occurred while calling z:com.johnsnowlabs.nlp.pretrained.InternalsPythonResourceDownloader.downloadModel.
: java.lang.NoClassDefFoundError: Could not initialize class com.johnsnowlabs.nlp.pretrained.InternalsPythonResourceDownloader$
at com.johnsnowlabs.nlp.pretrained.InternalsPythonResourceDownloader.downloadModel(InternalsPythonResourceDownloader.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(Unknown Source)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(Unknown Source)
at 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:238)
at java.lang.Thread.run(Unknown Source)

I use the following code to load --->

Spark = SparkSession.builder
.appName("Spark NLP Licensed")
.master("local[*]")
.config("spark.driver.memory", "16G")
.config("spark.serializer",
"org.apache.spark.serializer.KryoSerializer")
.config("spark.kryoserializer.buffer.max", "2000M")
.config("spark.jars", ~/spark-nlp-jsl-3.0.2.jar)
.getOrCreate()

[JustHeroo]

Please check the version of spark/pyspark. Such an error can occur if you are using spark 2.x with a spark-nlp-jsl jar compiled for spark 3.x