Hi all
We have Spark 2.0 (*) installed from the Cloudera parcel on our cluster (CDH 5.9.0).
When running a quite simple App which just reads in some csv files and does a groupBy I always receive errors.
The App is submitted with:
spark2-submit --class my_class myapp-1.0-SNAPSHOT.jar
And I receive the following error message:
java.io.InvalidClassException: org.apache.commons.lang3.time.FastDateFormat; local class incompatible: stream classdesc serialVersionUID = 2, local class serialVersionUID = 1
I figured out that there are multiple versions of lang3 installed with the Cloudera release and modified the spark2-submit to:
spark2-submit --conf spark.driver.userClassPathFirst=true --conf spark.executor.userClassPathFirst=true --jars /var/opt/teradata/cloudera/parcels/CDH/jars/commons-lang3-3.3.2.jar --class my_class myapp-1.0-SNAPSHOT.jar
This way I cloud get rid of the first error message, but now I get:
java.lang.ClassCastException: cannot assign instance of org.apache.commons.lang3.time.FastDateFormat to field org.apache.spark.sql.execution.datasources.csv.CSVOptions.dateFormat of type org.apache.commons.lang3.time.FastDateFormat in instance of org.apache.spark.sql.execution.datasources.csv.CSVOptions
The App was written in Scala and compiled using Maven. The source code (**) and the maven pom file (***) are attached at the bottom of this post.
Does anybody have an idea on solving this issue?
Any help is highly appreciated!
Thanks a lot in advance!
Kind Regards
(*)
$spark2-submit --version
Welcome to
____ __
/ __/__ ___ _____/ /__
_\ \/ _ \/ _ `/ __/ '_/
/___/ .__/\_,_/_/ /_/\_\ version 2.0.0.cloudera1
/_/
Branch HEAD
Compiled by user jenkins on 2016-12-06T18:34:13Z
Revision 2389f44e0185f33969d782ed09b41ae45fe30324(**)
import org.apache.spark.sql.SparkSession
object my_class {
def main(args: Array[String]): Unit = {
val spark = SparkSession
.builder
.appName("myapp")
.getOrCreate()
val csv = spark.read.option("header", value = false).csv("/path/to/folder/with/some/csv/files/")
val pivot = csv.groupBy("_c0").count()
csv.take(10).foreach(println)
pivot.take(10).foreach(println)
spark.stop()
}
}(***)
<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<groupId>de.lht.datalab.ingestion</groupId>
<artifactId>myapp</artifactId>
<version>1.0-SNAPSHOT</version>
<properties>
<scala.version.base>2.11</scala.version.base>
<scala.version>${scala.version.base}.8</scala.version>
<spark.version>2.0.0.cloudera1</spark.version>
</properties>
<repositories>
<repository>
<id>cloudera</id>
<url>https://repository.cloudera.com/artifactory/cloudera-repos/</url>
</repository>
</repositories>
<dependencies>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-sql_${scala.version.base}</artifactId>
<version>${spark.version}</version>
</dependency>
</dependencies>
<build>
<plugins>
<plugin>
<groupId>org.scala-tools</groupId>
<artifactId>maven-scala-plugin</artifactId>
<version>2.15.2</version>
<executions>
<execution>
<goals>
<goal>compile</goal>
<goal>testCompile</goal>
</goals>
</execution>
</executions>
</plugin>
</plugins>
</build>
</project>
