Detected Guava issue #1635 which indicates that a

问题:

I am running spark job on emr and using datastax connector to connect to cassandra cluster. I am facing issues with the guava jar please find the details as below I am using below cassandra deps

cqlsh 5.0.1 | Cassandra 3.0.1 | CQL spec 3.3.1 

Running spark job on EMR 4.4 with below maven deps

org.apache.spark spark-streaming_2.10 1.5.0

<dependency>
    <groupId>org.apache.spark</groupId>
    <artifactId>spark-core_2.10</artifactId>
    <version>1.5.0</version>
</dependency>

<dependency>
    <groupId>org.apache.spark</groupId><dependency>
    <groupId>com.datastax.spark</groupId>
    <artifactId>spark-cassandra-connector_2.10</artifactId>
    <version>1.5.0</version>
</dependency>

    <artifactId>spark-streaming-kinesis-asl_2.10</artifactId>
    <version>1.5.0</version>
</dependency>

facing issues when i submit spark job as below

ava.lang.ExceptionInInitializerError
       at com.datastax.spark.connector.cql.DefaultConnectionFactory$.clusterBuilder(CassandraConnectionFactory.scala:35)
       at com.datastax.spark.connector.cql.DefaultConnectionFactory$.createCluster(CassandraConnectionFactory.scala:87)
       at com.datastax.spark.connector.cql.CassandraConnector$.com$datastax$spark$connector$cql$CassandraConnector$$createSession(CassandraConnector.scala:153)
       at com.datastax.spark.connector.cql.CassandraConnector$$anonfun$2.apply(CassandraConnector.scala:148)
       at com.datastax.spark.connector.cql.CassandraConnector$$anonfun$2.apply(CassandraConnector.scala:148)
       at com.datastax.spark.connector.cql.RefCountedCache.createNewValueAndKeys(RefCountedCache.scala:31)
      at com.datastax.spark.connector.cql.RefCountedCache.acquire(RefCountedCache.scala:56)
       at com.datastax.spark.connector.cql.CassandraConnector.openSession(CassandraConnector.scala:81)
       at ampush.event.process.core.CassandraServiceManagerImpl.getAdMetaInfo(CassandraServiceManagerImpl.java:158)
       at ampush.event.config.metric.processor.ScheduledEventAggregator$4.call(ScheduledEventAggregator.java:308)
       at ampush.event.config.metric.processor.ScheduledEventAggregator$4.call(ScheduledEventAggregator.java:290)
       at org.apache.spark.api.java.JavaRDDLike$$anonfun$foreachPartition$1.apply(JavaRDDLike.scala:222)
       at org.apache.spark.api.java.JavaRDDLike$$anonfun$foreachPartition$1.apply(JavaRDDLike.scala:222)
       at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1$$anonfun$apply$29.apply(RDD.scala:902)
       at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1$$anonfun$apply$29.apply(RDD.scala:902)
       at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1850)
       at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1850)
       at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
       at org.apache.spark.scheduler.Task.run(Task.scala:88)
       at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
       at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
       at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
       at java.lang.Thread.run(Thread.java:745)
Caused by: java.lang.IllegalStateException: Detected Guava issue #1635 which indicates that a version of Guava less than 16.01 is in use.  This introduces codec resolution issues and potentially other incompatibility issues in the driver.  Please upgrade to Guava 16.01 or later.
       at com.datastax.driver.core.SanityChecks.checkGuava(SanityChecks.java:62)
       at com.datastax.driver.core.SanityChecks.check(SanityChecks.java:36)
       at com.datastax.driver.core.Cluster.<clinit>(Cluster.java:67)
       ... 23 more

please let me know how to manage guava deps here ?

Thanks

回答1:

Another solution, Go to directory

spark/jars

. Rename guava-14.0.1.jar then copy guava-19.0.jar like this picture:

回答2:

Just add in your POM's <dependencies> block something like this:

<dependency>
    <groupId>com.google.guava</groupId>
    <artifactId>guava</artifactId>
    <version>19.0</version>
</dependency>

(or any version > 16.0.1 that you prefer)

回答3:

I've had the same problem, and resolved it by using the maven Shade plugin to shade the guava version that the Cassandra connector brings in.

I needed to exclude the Optional, Present and Absent classes explicitly because I was running into issues with Spark trying to cast from the non-shaded Guava Present type to the shaded Optional type. I'm not sure if this will cause any problems later on, but it seems to be working for me for now.

You can add this to the <plugins> section in your pom.xml:

<plugin>
    <groupId>org.apache.maven.plugins</groupId>
    <artifactId>maven-shade-plugin</artifactId>
    <version>2.4.3</version>
    <executions>
        <execution>
            <phase>package</phase>
            <goals>
                <goal>
                    shade
                </goal>
            </goals>
        </execution>
    </executions>

    <configuration>
        <minimizeJar>true</minimizeJar>
        <shadedArtifactAttached>true</shadedArtifactAttached>
        <shadedClassifierName>fat</shadedClassifierName>

        <relocations>
            <relocation>
                <pattern>com.google</pattern>
                <shadedPattern>shaded.guava</shadedPattern>
                <includes>
                    <include>com.google.**</include>
                </includes>

                <excludes>
                    <exclude>com.google.common.base.Optional</exclude>
                    <exclude>com.google.common.base.Absent</exclude>
                    <exclude>com.google.common.base.Present</exclude>
                </excludes>
            </relocation>
        </relocations>

        <filters>
            <filter>
                <artifact>*:*</artifact>
                <excludes>
                    <exclude>META-INF/*.SF</exclude>
                    <exclude>META-INF/*.DSA</exclude>
                    <exclude>META-INF/*.RSA</exclude>
                </excludes>
            </filter>
        </filters>

    </configuration>
</plugin>

回答4:

I was able to get around this by adding the guava 16.0.1 jar externally and then specifying the class-path on Spark submit with help of below configuration values:

--conf "spark.driver.extraClassPath=/guava-16.0.1.jar" --conf "spark.executor.extraClassPath=/guava-16.0.1.jar"

Hope this helps someone with similar error !

回答5:

Thanks Adrian for your response.

I am on a little of a different architecture than everybody else on the thread but the Guava problem is still the same. I am using spark 2.2 with mesosphere. In our development environment we use sbt-native-packager to produce our docker images to pass into mesos.

Turns out, we needed to have a different guava for the spark submit executors than we need for the code that we run on the driver. This worked for me.

build.sbt

....
libraryDependencies ++= Seq(
  "com.google.guava" % "guava" % "19.0" force(),
  "org.apache.hadoop" % "hadoop-aws" % "2.7.3" excludeAll (
    ExclusionRule(organization = "org.apache.hadoop", name = "hadoop-common"), //this is for s3a
    ExclusionRule(organization = "com.google.guava",  name= "guava" )),
  "org.apache.spark" %% "spark-core" % "2.1.0"   excludeAll (
    ExclusionRule("org.glassfish.jersey.bundles.repackaged", name="jersey-guava"),
    ExclusionRule(organization = "com.google.guava",  name= "guava" )) ,
  "com.github.scopt" %% "scopt" % "3.7.0"  excludeAll (
    ExclusionRule("org.glassfish.jersey.bundles.repackaged", name="jersey-guava"),
    ExclusionRule(organization = "com.google.guava",  name= "guava" )) ,
  "com.datastax.spark" %% "spark-cassandra-connector" % "2.0.6",
...
dockerCommands ++= Seq(
...
  Cmd("RUN rm /opt/spark/dist/jars/guava-14.0.1.jar"),
  Cmd("RUN wget -q http://central.maven.org/maven2/com/google/guava/guava/23.0/guava-23.0.jar  -O /opt/spark/dist/jars/guava-23.0.jar")
...

When I tried to replace guava 14 on the executors with guava 16.0.1 or 19, it still wouldn't work. Spark submit just died. My fat jar which is actually the guava that is in use for my application in the driver I forced to be 19, but my spark submit executor I had to replace to be 23. I did try replacing to 16 and 19, but spark just died there too.

Sorry for diverting, but every time after all my google searches this one came up every time. I hope this helps other SBT/mesos folks too.

回答6:

I was facing the the same issue while retrieving records from Cassandra table using Spark (java) on Spark submit.

Please check your guava jar version used by Hadoop and Spark in cluster using find command and change it accordingly.

find / -name "guav*.jar"

Otherwise add guava jar externally during spark-submit for driver and executer spark.driver.extraClassPath and spark.executor.extraClassPath respectively.

spark-submit --class com.my.spark.MySparkJob --master local --conf 'spark.yarn.executor.memoryOverhead=2048' --conf 'spark.cassandra.input.consistency.level=ONE' --conf 'spark.cassandra.output.consistency.level=ONE' --conf 'spark.dynamicAllocation.enabled=false' --conf "spark.driver.extraClassPath=lib/guava-19.0.jar" --conf "spark.executor.extraClassPath=lib/guava-19.0.jar" --total-executor-cores 15 --executor-memory 15g  --jars $(echo lib/*.jar | tr ' ' ',') target/my-sparkapp.jar

It's working for me. Hope you can try it.