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Posted to issues@spark.apache.org by "Alexandru Barbulescu (JIRA)" <ji...@apache.org> on 2019/05/02 15:11:00 UTC
[jira] [Commented] (SPARK-27623) Provider
org.apache.spark.sql.avro.AvroFileFormat could not be instantiated
[ https://issues.apache.org/jira/browse/SPARK-27623?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16831684#comment-16831684 ]
Alexandru Barbulescu commented on SPARK-27623:
----------------------------------------------
The problem might be related to the fact that in Spark 2.4.2, the pre-built convenience binaries are compiled for Scala 2.12. And the spark-cassandra-connector, that I also included, currently only supports 2.11.
> Provider org.apache.spark.sql.avro.AvroFileFormat could not be instantiated
> ---------------------------------------------------------------------------
>
> Key: SPARK-27623
> URL: https://issues.apache.org/jira/browse/SPARK-27623
> Project: Spark
> Issue Type: Bug
> Components: PySpark
> Affects Versions: 2.4.2
> Reporter: Alexandru Barbulescu
> Priority: Critical
>
> After updating to spark 2.4.2 when using the
> {code:java}
> spark.read.format().options().load()
> {code}
>
> chain of methods, regardless of what parameter is passed to "format" we get the following error related to avro:
>
> {code:java}
> - .options(**load_options)
> - File "/opt/spark/python/lib/pyspark.zip/pyspark/sql/readwriter.py", line 172, in load
> - File "/opt/spark/python/lib/py4j-0.10.7-src.zip/py4j/java_gateway.py", line 1257, in __call__
> - File "/opt/spark/python/lib/pyspark.zip/pyspark/sql/utils.py", line 63, in deco
> - File "/opt/spark/python/lib/py4j-0.10.7-src.zip/py4j/protocol.py", line 328, in get_return_value
> - py4j.protocol.Py4JJavaError: An error occurred while calling o69.load.
> - : java.util.ServiceConfigurationError: org.apache.spark.sql.sources.DataSourceRegister: Provider org.apache.spark.sql.avro.AvroFileFormat 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:44)
> - at scala.collection.Iterator.foreach(Iterator.scala:941)
> - at scala.collection.Iterator.foreach$(Iterator.scala:941)
> - at scala.collection.AbstractIterator.foreach(Iterator.scala:1429)
> - at scala.collection.IterableLike.foreach(IterableLike.scala:74)
> - at scala.collection.IterableLike.foreach$(IterableLike.scala:73)
> - at scala.collection.AbstractIterable.foreach(Iterable.scala:56)
> - at scala.collection.TraversableLike.filterImpl(TraversableLike.scala:250)
> - at scala.collection.TraversableLike.filterImpl$(TraversableLike.scala:248)
> - at scala.collection.AbstractTraversable.filterImpl(Traversable.scala:108)
> - at scala.collection.TraversableLike.filter(TraversableLike.scala:262)
> - at scala.collection.TraversableLike.filter$(TraversableLike.scala:262)
> - at scala.collection.AbstractTraversable.filter(Traversable.scala:108)
> - at org.apache.spark.sql.execution.datasources.DataSource$.lookupDataSource(DataSource.scala:630)
> - at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:194)
> - at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:167)
> - at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> - at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
> - at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> - at java.lang.reflect.Method.invoke(Method.java:498)
> - at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
> - at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
> - at py4j.Gateway.invoke(Gateway.java:282)
> - at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
> - at py4j.commands.CallCommand.execute(CallCommand.java:79)
> - at py4j.GatewayConnection.run(GatewayConnection.java:238)
> - at java.lang.Thread.run(Thread.java:748)
> - Caused by: java.lang.NoClassDefFoundError: org/apache/spark/sql/execution/datasources/FileFormat$class
> - at org.apache.spark.sql.avro.AvroFileFormat.<init>(AvroFileFormat.scala:44)
> - 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$LazyIterator.nextService(ServiceLoader.java:380)
> - ... 29 more
> - Caused by: java.lang.ClassNotFoundException: org.apache.spark.sql.execution.datasources.FileFormat$class
> - at java.net.URLClassLoader.findClass(URLClassLoader.java:382)
> - at java.lang.ClassLoader.loadClass(ClassLoader.java:424)
> - at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:349)
> - at java.lang.ClassLoader.loadClass(ClassLoader.java:357)
> - ... 36 more
> {code}
>
> The code we run looks like this:
>
> {code:java}
> spark_session = (
> SparkSession.builder
> .appName(APPLICATION_NAME)
> .master(MASTER_URL)
> .config('spark.cassandra.connection.host', SERVER_IP_ADDRESS)
> .config('spark.cassandra.auth.username', CASSANDRA_USERNAME)
> .config('spark.cassandra.auth.password', CASSANDRA_PASSWORD)
> .config('spark.sql.shuffle.partitions', 16)
> .config('parquet.enable.summary-metadata', 'true')
> .getOrCreate())
> load_options = {
> 'keyspace': CASSANDRA_KEYSPACE,
> 'table': TABLE_NAME,
> 'spark.cassandra.input.fetch.size_in_rows': '150' }
> df = (spark_session.read.format('org.apache.spark.sql.cassandra')
> .options(**load_options)
> .load())
> {code}
>
> We get the exact same error when trying to read a local .avro file instead of from Cassandra.
> Up to now we included the .jar file for Spark-Avro using the spark-submit --jars option. The version of Spark-Avro that we used, and worked with Spark 2.4.1, was Spark-Avro 2.4.0.
> In an attempt to fix this problem we tried updating the .jar file version. We also tried using the --packages option, with different version combinations, but none of these solutions worked. The same error shows up every time.
> When rolling back to Spark 2.4.1 with the exact same setup and code, the error doesn't show up and everything works fine.
> Any ideas on what could be causing this?
>
>
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