I have a jar file that contains some Scala (and Java) code that I run using the following spark-submit command:
spark-submit
--verbose
--class mycompany.MyClass
--conf spark.driver.extraJavaOptions=-Dconfig.resource=dev-test.conf
--conf "spark.executor.extraJavaOptions=-Dconfig.resource=dev-test.conf -verbose:class"
--conf 'spark.driver.extraJavaOptions=-verbose:class'
--master yarn
--driver-library-path /usr/lib/hadoop-lzo/lib/native/
--jars /home/hadoop/mydir/spark-utils-1.1.0-SNAPSHOT.jar,/usr/lib/phoenix/phoenix-client-hbase-2.4-5.1.2.jar,/usr/lib/hadoop-lzo/lib/hadoop-lzo.jar,/usr/lib/hadoop/lib/commons-compress-1.18.jar,/usr/lib/hadoop/hadoop-aws-3.2.1-amzn-5.jar,/usr/share/aws/aws-java-sdk/aws-java-sdk-bundle-1.12.31.jar
--files /home/hadoop/mydir/dev-test.conf
--queue default /home/hadoop/mydir/spark-utils-1.1.0-SNAPSHOT.jar
<<args to MyClass>>
When I run it, I get an error message - “IAMInstanceCredentialsProvider not found”, which is caused by a version mismatch. It seems IAMInstanceCredentialsProvider was added to hadoop-aws in version 3.3.0 and we want to use 3.2.1. I've gone through our maven dependencies and feel confident that we are not trying to use 3.3.x anywhere.
I've attempted to debug the problem by adding some "verbose" arguments to the command, and I've also added some debug code to MyClass to print out the classpath in effect, following the instructions from here.
When I look at the output, the classpath in effect when we run the spark-submit command includes a lot of jars included with Python, including /usr/local/lib/python3.7/site-packages/pyspark/jars/hadoop-client-api-3.3.1.jar. Thus far, I've been unable to figure out why we are loading jars from /usr/local/lib/python3.7.
Can anybody explain to me where those dependencies are coming from, or suggest a way that I could debug where those dependencies come from? I thought the python might be a result of some environment variable setting, but if so, it doesn't seem to be set at the top level:
set|grep -i python
doesn't return anything.
Related
Need this jar for listening to metrics data for streaming query. The jar works when passed from file system using --jars, but gives "unresolved dependency" error passed as --packages when read from remote repo (jfrog). But, all other dependencies works like abris, kafka etc.
EDIT- previously asked question with no conclusion: How to use custom jars in spark-submit --packages
I built a fat jar and I am trying to run it with spark-submit on an EMR or locally. here is the command:
spark-submit \
--deploy-mode client \
--class com.stash.data.omni.source.Runner myJar.jar \
<arguments>
I keep getting an error related to akka configurations:
Exception in thread "main" com.typesafe.config.ConfigException$Missing: No configuration setting found for key 'akka.version'
It seems like the jar cannot find the reference.confs for akka at all. Has anyone dealt with this? I am able to run it without spark-submit on my local machine.
I think the issue is bundling into a jar with all it's dependencies, which causes problems with Akka, as described in the documentation:
Akka’s configuration approach relies heavily on the notion of every
module/jar having its own reference.conf file. All of these will be
discovered by the configuration and loaded. Unfortunately this also
means that if you put/merge multiple jars into the same jar, you need
to merge all the reference.conf files as well: otherwise all defaults
will be lost.
You can follow this documentation to package your application and process to merge the reference.conf resources while bundling.It talks about packaging using sbt, maven, and gradle.
Let me know if it helps!!
it was my merge strategy. i had a catch all case _ => MergeStrategy.first. i changed it to case x => MergeStrategy.defaultMergeStrategy(x) and it worked.
I have used maven project in Scala. I have used all dependencies in pom.
Still I am getting ClassNotFoundException when I run spark-submit command.
clean compile assembly:single is the Maven goal which I used.
Following is the spark submit command I have used.
spark-submit --class com.SimpleScalaApp.SimpleApp --master local /location/file.jar
Unfortunately there is no useful comment on the question in my opinion. The ClassNotFoundException mostly is thrown when version of your dependencies are not match together.
First of all it's better to check if all your dependencies are matched by checking those dependencies' pom files and consequently their usage order in the main project pom file.
A short description about the best practice of running the program on spark cluster is using shaded or assembly build form.
I am attempting to run a spark job that accesses dynamodb and the old way of instantiating a dynamoDb client has been deprecated and it is now recommended to use the client builder.
Well, this works fine locally, but when I deploy to EMR i'm getting this error:
Exception in thread "main" java.lang.IllegalAccessError: tried to access class com.amazonaws.services.dynamodbv2.AmazonDynamoDBClientConfigurationFactory from class com.amazonaws.services.dynamodbv2.AmazonDynamoDBAsyncClientBuilder
My code that causes this is:
val dynamoDbClient = AmazonDynamoDBAsyncClientBuilder
.standard()
.withRegion(Regions.US_EAST_1)
.build()
my build.sbt contains:
libraryDependencies += "com.amazonaws" % "aws-java-sdk" % "1.11.114"
and my spark-submit command looks like this:
spark-submit --conf spark.eventLog.enabled=false --packages com.typesafe.play:play-json_2.11:2.5.9,com.github.traviscrawford:spark-dynamodb:0.0.6,com.amazonaws:aws-java-sdk:1.11.114 --master yarn --deploy-mode cluster --class Main application.jar
Does anyone have any ideas? Am I overlooking something basic?
Update
I noticed that EMR was running OpenJDK 1.8 and my local system was running Oracle Java 1.8. I changed the EMR cluster to match the java I was running, but there was still no change.
I dont have a perfect answer here but I'm struggling with a similar problem with a fat jar build Spark Driver running on EMR. So I drop my recent tour.
Try to run spark-submit with option -v and look into the logs about class paths and so forth. As I can see EMR is loading an aws-java-sdk as well. Its not clear to me which version of aws-java-sdk EMR is running? EMR release 4.7.0 states "Upgraded the AWS SDK for Java to 1.10.75" (http://docs.aws.amazon.com/emr/latest/ReleaseGuide/emr-whatsnew.html).
Then add another argument --conf spark.driver.userClassPathFirst=true
to load the aws-java-sdk version your driver specifies.
Unfortunately the last step raises yarn errors like: Unable to load YARN support ... (some discussion on that: https://community.cloudera.com/t5/Advanced-Analytics-Apache-Spark/spark-submit-fails-after-setting-userClassPathFirst-to-true/td-p/46778)
Some discussion from the aws-java-sdk github repos: https://github.com/aws/aws-sdk-java/issues/1094
Conclusion: For now use apis of aws-java-sdk version 1.10.75
Please note that I am better dataminer than programmer.
I am trying to run examples from book "Advanced analytics with Spark" from author Sandy Ryza (these code examples can be downloaded from "https://github.com/sryza/aas"),
and I run into following problem.
When I open this project in Intelij Idea and try to run it, I get error "Exception in thread "main" java.lang.NoClassDefFoundError: org/apache/spark/rdd/RDD"
Does anyone know how to solve this issue ?
Does this mean i am using wrong version of spark ?
First when I tried to run this code, I got error "Exception in thread "main" java.lang.NoClassDefFoundError: scala/product", but I solved it by setting scala-lib to compile in maven.
I use Maven 3.3.9, Java 1.7.0_79 and scala 2.11.7 , spark 1.6.1. I tried both Intelij Idea 14 and 15 different versions of java (1.7), scala (2.10) and spark, but to no success.
I am also using windows 7.
My SPARK_HOME and Path variables are set, and i can execute spark-shell from command line.
The examples in this book will show a --master argument to sparkshell, but you will need to specify arguments as appropriate for your environment. If you don’t have Hadoop installed you need to start the spark-shell locally. To execute the sample you can simply pass paths to local file reference (file:///), rather than a HDFS reference (hdfs://)
The author suggest an hybrid development approach:
Keep the frontier of development in the REPL, and, as pieces of code
harden, move them over into a compiled library.
Hence the samples code are considered as compiled libraries rather than standalone application. You can make the compiled JAR available to spark-shell by passing it to the --jars property, while maven is used for compiling and managing dependencies.
In the book the author describes how the simplesparkproject can be executed:
use maven to compile and package the project
cd simplesparkproject/
mvn package
start the spark-shell with the jar dependencies
spark-shell --master local[2] --driver-memory 2g --jars ../simplesparkproject-0.0.1.jar ../README.md
Then you can access you object within the spark-shell as follows:
val myApp = com.cloudera.datascience.MyApp
However if you want to execute the sample code as Standalone application and execute it within idea you need to modify the pom.xml.
Some of dependencies are required for compilation, but are available in an spark runtime environment. Therefore these dependencies are marked with scope provided in the pom.xml.
<!--<scope>provided</scope>-->
you can remake the provided scope, than you will be able to run the samples within idea. But you can not provide this jar as dependency for the spark shell anymore.
Note: using maven 3.0.5 and Java 7+. I had problems with maven 3.3.X version with the plugin versions.