Apache Spark-Cassandra Guava不兼容 [英] Apache spark - Cassandra Guava incompatibility

问题描述

我正在使用Apache Spark 2.1.0，Apache Spark连接器2.0.0-M3和Cassandra驱动程序核心3.0.0
尝试执行程序时出现以下错误：

I am using Apache spark 2.1.0, Apache Spark connector 2.0.0-M3 and Cassandra driver core 3.0.0 I get the following error when I try to execute the program:

17/01/19 10:38:27 WARN TaskSetManager: Lost task 1.0 in stage 1.0 (TID 5, 10.10.10.51, executor 1): java.lang.NoClassDefFoundError: Could not initialize class com.datastax.driver.core.Cluster
    at com.datastax.spark.connector.cql.DefaultConnectionFactory$.clusterBuilder(CassandraConnectionFactory.scala:35)
    at com.datastax.spark.connector.cql.DefaultConnectionFactory$.createCluster(CassandraConnectionFactory.scala:92)
    at com.datastax.spark.connector.cql.CassandraConnector$.com$datastax$spark$connector$cql$CassandraConnector$$createSession(CassandraConnector.scala:154)
    at com.datastax.spark.connector.cql.CassandraConnector$$anonfun$3.apply(CassandraConnector.scala:149)
    at com.datastax.spark.connector.cql.CassandraConnector$$anonfun$3.apply(CassandraConnector.scala:149)
    at com.datastax.spark.connector.cql.RefCountedCache.createNewValueAndKeys(RefCountedCache.scala:31)
    at com.datastax.spark.connector.cql.RefCountedCache.acquire(RefCountedCache.scala:56)
    at com.datastax.spark.connector.cql.CassandraConnector.openSession(CassandraConnector.scala:82)
    at com.datastax.spark.connector.rdd.CassandraTableScanRDD.compute(CassandraTableScanRDD.scala:326)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
    at org.apache.spark.rdd.RDD$$anonfun$8.apply(RDD.scala:336)
    at org.apache.spark.rdd.RDD$$anonfun$8.apply(RDD.scala:334)
    at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator$1.apply(BlockManager.scala:957)
    at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator$1.apply(BlockManager.scala:948)
    at org.apache.spark.storage.BlockManager.doPut(BlockManager.scala:888)
    at org.apache.spark.storage.BlockManager.doPutIterator(BlockManager.scala:948)
    at org.apache.spark.storage.BlockManager.getOrElseUpdate(BlockManager.scala:694)
    at org.apache.spark.rdd.RDD.getOrCompute(RDD.scala:334)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:285)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
    at org.apache.spark.scheduler.Task.run(Task.scala:99)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:282)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
    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)

我已经阅读到spark-cassandra-connector解决了番石榴与spark问题的兼容性：

I have read that spark-cassandra-connector solves the guava compatibility with spark problem:

https://groups.google.com/a/lists.datastax.com/forum/#!topic / spark-connector-user / aIpytzBAen4

我正在使用带有JettyRun和ClusterMode的SparkMaster api 7077执行。我将cassandra驱动程序和spark-cassandra连接器的jar传递给spark conf（setJars）

I am executing with SparkMaster api 7077 with JettyRun and ClusterMode. I pass the jars of the cassandra driver and spark-cassandra connector to the spark conf (setJars)

有时，如果我重新启动它，它会起作用，但有几次，我必须尝试

Some times if I restart it works, but several times I have to try and try and never works.

我尝试了一些答案，例如将Spark番石榴罐重命名为19版本，但总是遇到相同的问题。

I tried some answers like rename the Spark guava jar to 19 version but always got the same problem.

发生了什么事？

推荐答案

https：// github.com/datastax/spark-cassandra-connector/blob/master/doc/FAQ.md#how-do-i-fix-guava-classpath-errors

此处的关键点是

1. 仅使用带阴影的罐子，这是Spark Cassandra连接器2.0.0-中的默认设置M3


2. 不包括对Cassandra Java驱动程序的任何依赖关系。这样做将重新引入番石榴版本。

这篇关于Apache Spark-Cassandra Guava不兼容的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！