I am working on a model upgrade which is currently using spark2 and now moving to spark 3, for this we are using manual jars.
The model is failing due to incompatible jars
Failure:
"Caused by: java.io.InvalidClassException: com.johnsnowlabs.nlp.util.regex.RuleFactory;local class incompatible: stream classdesc serialVersionUID = someserialnumber local class serialVersionUID = someserialnumber"
I am facing this error while using the below jars
These are the version used for upgrade(spark 3): |
____________________________________________________|
nlp --> 2.12-5.5.1
nlp-assembler -->2.5.5
Tensorflow -->1.15.5-1.5.5
Graphframes --> 0.6.0-spark2.3-s_2.11
parso -->2.0.14.jar
spark-sas7bat-2.1.0-s_2.11.jar
Python --> 3.9
Java --> 8
Existing Jar File present (spark2):
spark-nlp -->2.11-2.4.3.jar
spark-assembler --> 2.1.0-s_2.11.jar
parso-2.0.10.jar
spark-nlp-assembler-2.5.5.jar
tensorflow-1.13.1.jar
graphframes-0.6.0-spark2.3-s_2.11.jar
Please help in resolving this issue.
Kindly let me know if more information is required.
Here is the code were the jars are specified:
export spark_Exec="spark3-submit
--master yarn --queue ${queue_serv}
--conf spark.executorEnv.pyspark_python=$pyspark_python"
--conf spark.executorEnv.PYTHONPATH_PYTHON=$PYTHONPATH_PYTHON
--conf spark.yarn.appMasterEnv.PYSPARK_PYTHON=$PYSPARK_PYTHON
--driver-memory=8G
--executor-memory=8G
--conf spark.driver.maxResultSize=10G
--conf spark.mesos.executor.memoryOverhead=600
--jars ${JAR_DIR}/spark-nlp_2.12-5.5.1.jar,${JAR_DIR}/spark-sas7bdat-2.1.0-s_2.11.jar,
${JAR_DIR}/parso-2.0.14.jar,${JAR_DIR}/spark-nlp-assembly-2.5.5.jar,${JAR_DIR}/tensorflow-1.15.5.jar,
${JAR_DIR}/graphframes-0.6.0-spark2.3-s_2.11.jar"