I was thinking of using spark and redis together with SBT.
It runs fine if I comment out the spark dependency, if I include the spark dependency I get:
Exception in thread "main" java.lang.NoSuchMethodError: akka.actor.ActorSystem.dispatcher()Lscala/concurrent/ExecutionContextExecutor;
at redis.RedisClientActorLike.<init>(Redis.scala:31)
at redis.RedisClient.<init>(Redis.scala:69)
I have no issues when I do not include "redisscala". When I do include redisscala, then I get weird errors about Akka.
How do I get around this?
It appears that those versions of Spark and rediscala are using incompatible versions of Akka. Spark 1.1.0 is using Akka 2.2.3, and rediscala 1.3.1 is using Akka 2.3.4. There are some changes between Akka 2.2.x and 2.3.x that are causing issues, and your project currently has both as transient dependencies.
You either need to downgrade rediscala to 1.2 (which uses Akka 2.2.x), or upgrade Spark to 1.2-snapshot (which uses Akka 2.3.x).
Related
I am trying to run a Flink (v 1.13.1) application on EMR ( v
5.34.0).
My Flink application uses Scallop(v 4.1.0) to parse the arguments passed.
Scala version used for Flink application is
2.12.7.
I keep getting below error when I submit the flink application to the cluster. Any clue or help is highly appreciated.
java.lang.NoSuchMethodError: scala.Product.$init$(Lscala/Product;)V
at org.rogach.scallop.Scallop.<init>(Scallop.scala:63)
at org.rogach.scallop.Scallop$.apply(Scallop.scala:13)
Resolved the issue by downgrading Scala to 2.11. Flink 1.13.1 Scala shell REPL on EMR mentioned scala version 2.11.12 hence downgraded to that version of Scala and this problem has disappeared.
We have several Spark applications running on production developed using Spark 2.4.1 (Scala 2.11.12).
For couple of our new Spark jobs,we are considering utilizing features of DeltaLake.For this we need to use Spark 2.4.2 (or higher).
My questions are:
If we upgrade our Spark cluster to 3.0.0, can our 2.4.1 applications still run on the new cluster (without recompile)?
If we need to recompile our previous Spark jobs with Spark 3, are they source compatible or do they need any migration?
There are some breaking changes in Spark 3.0.0, including source incompatible change and binary incompatible changes. See https://spark.apache.org/releases/spark-release-3-0-0.html. And there are also some source and binary incompatible changes between Scala 2.11 and 2.12, so you may also need to update codes because of Scala version change.
However, only do Delta Lake 0.7.0 and above require Spark 3.0.0. If upgrading to Spark 3.0.0 requires a lot of work, you can use Delta Lake 0.6.x or below. You just need to upgrade Spark to 2.4.2 or above in 2.4.x line. They should be source and binary compatible.
You can cross compile projects Spark 2.4 projects with Scala 2.11 and Scala 2.12. The Scala 2.12 JARs should generally work for Spark 3 applications. There are edge cases when using a Spark 2.4/Scala 2.12 JAR won't work properly on a Spark 3 cluster.
It's best to make a clean migration to Spark 3/Scala 2.12 and cut the cord with Spark 2/Scala 2.11.
Upgrading can be a big pain, especially if your project has a lot of dependencies. For example, suppose your project depends on spark-google-spreadsheets, a project that's not built with Scala 2.12. With this dependency, you won't be able to easily upgrade your project to Scala 2.12. You'll need to either compile spark-google-spreadsheets with Scala 2.12 yourself or drop the dependency. See here for more details on how to migrate to Spark 3.
I am new to 'Spark NLP' and I got stuck in version compatibility issues only. That may seems to be silly but still I request you to help me in this:
‘Spark NLP’ is built on top of Apache Spark 2.4.0 and such is the only supported release (mentioned on https://nlp.johnsnowlabs.com/docs/en/quickstart)
Spark 2.4.3 uses Scala 2.12 (mentioned on https://spark.apache.org/docs/latest/)
But maven repo repository just have spark_nlp libararies for scala 2.11 only not after that (see https://repo1.maven.org/maven2/com/johnsnowlabs/nlp/, only spark-nlp_2.11 is present and not spark-nlp_2.12)
Please help
i got this error. I'm not sure why this is the case because there is a coalesce method in org.apache.spark.rdd.RDD.
Any ideas?
Am I running a incompatible version of Spark and org.apache.spark.rdd.RDD?
Exception in thread "main" java.lang.NoSuchMethodError: org.apache.spark.rdd.RDD.coalesce$default$3(IZ)Lscala/math/Ordering;
It was because some part of your code or project dependencies called old version(spark version before 2.0.0) spark API 'coalesce' while in new version spark this API has been removed and replaced by 'repartition'.
To fix this problem, you could either downgrade your spark run environment to below version 2.0.0, or you can upgrade your SDK spark version to above 2.0.0 and upgrade project dependencies version to be compatible with spark 2.0.0 or above.
For more details please see this thread:
https://github.com/twitter/algebird/issues/549
https://github.com/EugenCepoi/algebird/commit/0dc7d314cba3be588897915c8dcfb14964933c31
As I suspected, this is a library compatibility issue. Everything works (no code change) after downgrading Spark alone.
Before:
scala 2.11.8
spark 2.0.1
Java 1.8.0_92
After
scala 2.11.8
spark 1.6.2
Java 1.8.0_92
OS: OSX 10.11.6
I am experimenting with Spark Kafka integration. And I want to test the code from my eclipse IDE. However, I got below error:
java.lang.NoClassDefFoundError: scala/collection/GenTraversableOnce$class
at kafka.utils.Pool.<init>(Pool.scala:28)
at kafka.consumer.FetchRequestAndResponseStatsRegistry$.<init>(FetchRequestAndResponseStats.scala:60)
at kafka.consumer.FetchRequestAndResponseStatsRegistry$.<clinit>(FetchRequestAndResponseStats.scala)
at kafka.consumer.SimpleConsumer.<init>(SimpleConsumer.scala:39)
at org.apache.spark.streaming.kafka.KafkaCluster.connect(KafkaCluster.scala:52)
at org.apache.spark.streaming.kafka.KafkaCluster$$anonfun$org$apache$spark$streaming$kafka$KafkaCluster$$withBrokers$1.apply(KafkaCluster.scala:345)
at org.apache.spark.streaming.kafka.KafkaCluster$$anonfun$org$apache$spark$streaming$kafka$KafkaCluster$$withBrokers$1.apply(KafkaCluster.scala:342)
at scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
at scala.collection.mutable.WrappedArray.foreach(WrappedArray.scala:35)
at org.apache.spark.streaming.kafka.KafkaCluster.org$apache$spark$streaming$kafka$KafkaCluster$$withBrokers(KafkaCluster.scala:342)
at org.apache.spark.streaming.kafka.KafkaCluster.getPartitionMetadata(KafkaCluster.scala:125)
at org.apache.spark.streaming.kafka.KafkaCluster.getPartitions(KafkaCluster.scala:112)
at org.apache.spark.streaming.kafka.KafkaUtils$.createDirectStream(KafkaUtils.scala:403)
at org.apache.spark.streaming.kafka.KafkaUtils$.createDirectStream(KafkaUtils.scala:532)
at org.apache.spark.streaming.kafka.KafkaUtils.createDirectStream(KafkaUtils.scala)
at com.capiot.platform.spark.SparkTelemetryReceiverFromKafkaStream.executeStreamingCalculations(SparkTelemetryReceiverFromKafkaStream.java:248)
at com.capiot.platform.spark.SparkTelemetryReceiverFromKafkaStream.main(SparkTelemetryReceiverFromKafkaStream.java:84)
UPDATE:
The versions that I am using are:
scala - 2.11
spark-streaming-kafka- 1.4.1
spark - 1.4.1
Can any one resolve the issue? Thanks in advance.
You have the wrong version of Scala. You need 2.10.x per
https://spark.apache.org/docs/1.4.1/
"For the Scala API, Spark 1.4.1 uses Scala 2.10."
Might be late to help OP, but when using kafka streaming with spark, you need to make sure that you use the right jar file.
For example, in my case, I have scala 2.11 (the minimum required for spark 2.0 which im using), and given that kafka spark requires the version 2.0.0 I have to use the artifact spark-streaming-kafka-0-8-assembly_2.11-2.0.0-preview.jar
Notice my scala version and the artifact version can be seen at 2.11-2.0.0
Hope this helps (someone)
Hope that helps.