pySpark and py4j: NoClassDefFoundError when upgrading a jar
We developed a Scala library to run on spark called FV. We also built wrappers in python for its public API using py4j as in spark. For example, the main object is instantiated like this
self._java_obj = self._new_java_obj("com.example.FV", self.uid)
and the methods on the object are called in this way
def add(self, r):
self._java_obj.add(r)
We are experiencing an annoying issue when running pyspark with this external library. We use to run the pyspark shell like this
pyspark --repositories <our-own-maven-release-repo> --packages <com.example.FV:latest.release>
When we release a new version and we have some change in the Scala API, things start to randomly break for some users. For example, in version 0.44 we had a class DateUtils (used by class Utils, which is used by class FV in method add) that was dropped in version 0.45. When version 0.45 was released and a user called the method add in python API we got
java.lang.NoClassDefFoundError: Could not initialize class DateUtils
Basically, the python API is running the method add which contains a reference to class DateUtils (v0.44) but when it is actually going to load the needed class it doesn't find it, because the loaded jar is the v0.45 (as the ivy log shows when starting up the shell)
Do you have any idea of what the problem might be? Does maybe py4j cache something so that when upgrading the classes we get this error?
apache-spark pyspark classloader py4j
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We developed a Scala library to run on spark called FV. We also built wrappers in python for its public API using py4j as in spark. For example, the main object is instantiated like this
self._java_obj = self._new_java_obj("com.example.FV", self.uid)
and the methods on the object are called in this way
def add(self, r):
self._java_obj.add(r)
We are experiencing an annoying issue when running pyspark with this external library. We use to run the pyspark shell like this
pyspark --repositories <our-own-maven-release-repo> --packages <com.example.FV:latest.release>
When we release a new version and we have some change in the Scala API, things start to randomly break for some users. For example, in version 0.44 we had a class DateUtils (used by class Utils, which is used by class FV in method add) that was dropped in version 0.45. When version 0.45 was released and a user called the method add in python API we got
java.lang.NoClassDefFoundError: Could not initialize class DateUtils
Basically, the python API is running the method add which contains a reference to class DateUtils (v0.44) but when it is actually going to load the needed class it doesn't find it, because the loaded jar is the v0.45 (as the ivy log shows when starting up the shell)
Do you have any idea of what the problem might be? Does maybe py4j cache something so that when upgrading the classes we get this error?
apache-spark pyspark classloader py4j
add a comment |
We developed a Scala library to run on spark called FV. We also built wrappers in python for its public API using py4j as in spark. For example, the main object is instantiated like this
self._java_obj = self._new_java_obj("com.example.FV", self.uid)
and the methods on the object are called in this way
def add(self, r):
self._java_obj.add(r)
We are experiencing an annoying issue when running pyspark with this external library. We use to run the pyspark shell like this
pyspark --repositories <our-own-maven-release-repo> --packages <com.example.FV:latest.release>
When we release a new version and we have some change in the Scala API, things start to randomly break for some users. For example, in version 0.44 we had a class DateUtils (used by class Utils, which is used by class FV in method add) that was dropped in version 0.45. When version 0.45 was released and a user called the method add in python API we got
java.lang.NoClassDefFoundError: Could not initialize class DateUtils
Basically, the python API is running the method add which contains a reference to class DateUtils (v0.44) but when it is actually going to load the needed class it doesn't find it, because the loaded jar is the v0.45 (as the ivy log shows when starting up the shell)
Do you have any idea of what the problem might be? Does maybe py4j cache something so that when upgrading the classes we get this error?
apache-spark pyspark classloader py4j
We developed a Scala library to run on spark called FV. We also built wrappers in python for its public API using py4j as in spark. For example, the main object is instantiated like this
self._java_obj = self._new_java_obj("com.example.FV", self.uid)
and the methods on the object are called in this way
def add(self, r):
self._java_obj.add(r)
We are experiencing an annoying issue when running pyspark with this external library. We use to run the pyspark shell like this
pyspark --repositories <our-own-maven-release-repo> --packages <com.example.FV:latest.release>
When we release a new version and we have some change in the Scala API, things start to randomly break for some users. For example, in version 0.44 we had a class DateUtils (used by class Utils, which is used by class FV in method add) that was dropped in version 0.45. When version 0.45 was released and a user called the method add in python API we got
java.lang.NoClassDefFoundError: Could not initialize class DateUtils
Basically, the python API is running the method add which contains a reference to class DateUtils (v0.44) but when it is actually going to load the needed class it doesn't find it, because the loaded jar is the v0.45 (as the ivy log shows when starting up the shell)
Do you have any idea of what the problem might be? Does maybe py4j cache something so that when upgrading the classes we get this error?
apache-spark pyspark classloader py4j
apache-spark pyspark classloader py4j
edited Dec 30 '18 at 19:13
alexlipa
asked Dec 29 '18 at 10:48
alexlipaalexlipa
7718
7718
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