ServiceConfigurationError running spark 3.2

Question

I am trying to update code written with spark 2.4 and doing some tests with spark 3.2. I am able to create a spark session:

spark = (
    SparkSession.builder
        .config('spark.jars.packages', 'org.apache.hadoop:hadoop-azure:3.2.0,com.crealytics:spark-excel_2.11:0.13.1')
        .config('spark.hadoop.fs.azure', "org.apache.hadoop.fs.azure.NativeAzureFileSystem")
        .config("spark.hadoop.fs.azure.account.key." + storage_account + ".blob.core.windows.net", storage_account_key)
        .config("spark.driver.memory", "32G")
        .master("local[*]")
        .appName("Dev")
        .getOrCreate()
)
spark.sparkContext._jsc.hadoopConfiguration().set("fs.wasbs.impl", "org.apache.hadoop.fs.azure.NativeAzureFileSystem")

but when I try to read something with

spark.read.parquet(some_parquet_somewhere)

I get the following errors:

Py4JJavaError: An error occurred while calling o104.parquet.
: java.util.ServiceConfigurationError: org.apache.spark.sql.sources.DataSourceRegister: Provider org.apache.spark.sql.delta.sources.DeltaDataSource could not be instantiated
    at java.util.ServiceLoader.fail(ServiceLoader.java:232)
    at java.util.ServiceLoader.access$100(ServiceLoader.java:185)
    at java.util.ServiceLoader$LazyIterator.nextService(ServiceLoader.java:384)
    at java.util.ServiceLoader$LazyIterator.next(ServiceLoader.java:404)
    at java.util.ServiceLoader$1.next(ServiceLoader.java:480)
    at scala.collection.convert.Wrappers$JIteratorWrapper.next(Wrappers.scala:46)
    at scala.collection.Iterator.foreach(Iterator.scala:943)
    at scala.collection.Iterator.foreach$(Iterator.scala:943)
    at scala.collection.AbstractIterator.foreach(Iterator.scala:1431)
    at scala.collection.IterableLike.foreach(IterableLike.scala:74)
    at scala.collection.IterableLike.foreach$(IterableLike.scala:73)
    at scala.collection.AbstractIterable.foreach(Iterable.scala:56)
    at scala.collection.TraversableLike.filterImpl(TraversableLike.scala:303)
    at scala.collection.TraversableLike.filterImpl$(TraversableLike.scala:297)
    at scala.collection.AbstractTraversable.filterImpl(Traversable.scala:108)
    at scala.collection.TraversableLike.filter(TraversableLike.scala:395)
    at scala.collection.TraversableLike.filter$(TraversableLike.scala:395)
    at scala.collection.AbstractTraversable.filter(Traversable.scala:108)
    at org.apache.spark.sql.execution.datasources.DataSource$.lookupDataSource(DataSource.scala:652)
    at org.apache.spark.sql.execution.datasources.DataSource$.lookupDataSourceV2(DataSource.scala:720)
    at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:210)
    at org.apache.spark.sql.DataFrameReader.parquet(DataFrameReader.scala:596)
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:498)
    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.ClientServerConnection.waitForCommands(ClientServerConnection.java:182)
    at py4j.ClientServerConnection.run(ClientServerConnection.java:106)
    at java.lang.Thread.run(Thread.java:748)
Caused by: java.lang.NoClassDefFoundError: org/apache/spark/internal/Logging$class
    at org.apache.spark.sql.delta.sources.DeltaDataSource.<init>(DeltaDataSource.scala:43)
    at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
    at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
    at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
    at java.lang.reflect.Constructor.newInstance(Constructor.java:423)
    at java.lang.Class.newInstance(Class.java:442)
    at java.util.ServiceLoader$LazyIterator.nextService(ServiceLoader.java:380)
    ... 31 more

I get that it is a configuration issue, but I'm not sure which one. I would really appreciate some help

Edit: I am getting these error trying to use pyspark in Jupyter Notebook, I tried using pyspark in the console and had no issues reading from Azure Blob Storage.

Because I get this message:

/opt/spark/python/pyspark/sql/readwriter.py in parquet(self, *paths, **options)
299                        int96RebaseMode=int96RebaseMode)
300 
--> 301         return self._df(self._jreader.parquet(_to_seq(self._spark._sc, paths)))
    302 
    303     def text(self, paths, wholetext=False, lineSep=None, pathGlobFilter=None,

~/.pyenv/versions/3.7.3/lib/python3.7/site-packages/py4j/java_gateway.py in __call__(self, *args)
   1320         answer = self.gateway_client.send_command(command)
   1321         return_value = get_return_value(
-> 1322             answer, self.gateway_client, self.target_id, self.name)
   1323 
   1324         for temp_arg in temp_args:

/opt/spark/python/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)

~/.pyenv/versions/3.7.3/lib/python3.7/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(

I thought maybe it was some problem with env variables so I tried using

export SPARK_HOME=spark/installation/folder

and

import findspark
findspark.init()

to no avail.

`NoClassDefFoundError: org/apache/spark/internal` ... Indicates that your Spark dependency versions do not align. — OneCricketeer, Dec 01 '21 at 16:43
Yes, the only problem is that I still don't know what dependencies are the problem :( — DatGuy, Dec 03 '21 at 22:41
It'd be great if you could show your entire sbt, pom, gradle or whatever you're using to build, but one example is that I don't think Spark 3 supports Scala 2.11, so spark-excel_2.11 isn't going to work, and so you'll have to verify that library also supports Spark 3... Since you're only reading parquet files, you don't need external jars outside of Azure — OneCricketeer, Dec 04 '21 at 15:33
Thanks. I have edited my question and removed the spark-excel_2.11 line but still the same error. Maybe it's some issue with hadoop? When checking the folder where spark is installed, there's one called 'spark-3.2.0-without-hadoop' or something like that — DatGuy, Dec 07 '21 at 00:02
Your error also says `DeltaDataSource could not be instantiated`, which means you need to add the Delta datalake packages... What version of those do you have? Note: They **just** released Spark 3.2 support a few days ago https://github.com/delta-io/delta/releases/tag/v1.1.0 — OneCricketeer, Dec 07 '21 at 00:28
As linked, that should be upgraded to the latest version that actually supports Spark 3.2 (and probably need to change the Scala version as well) — OneCricketeer, Dec 07 '21 at 00:49

score 1 · Answer 1 · answered Dec 07 '21 at 19:30

Ok so like OneCricketeer mentioned the problem was the Delta Lake version. Running:

pyspark --packages io.delta:delta-core_2.12:1.1.0 --conf "spark.sql.extensions=io.delta.sql.DeltaSparkSessionExtension" --conf "spark.sql.catalog.spark_catalog=org.apache.spark.sql.delta.catalog.DeltaCatalog"

solved it

ServiceConfigurationError running spark 3.2

1 Answers1