当前位置: 首页 > 知识库问答 >
问题:

阿帕奇火花-卡桑德拉番石榴不亲和性

蓬兴国
2023-03-14
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)

我正在用SparkMaster api 7077执行JettyRun和ClusterMode。我将cassandra驱动程序和spark-cassandra连接器的jar传递给spark conf(setjar)

有些时候,如果我重新启动,它是有效的,但有几次,我不得不尝试和尝试,从来没有工作。

我尝试了一些答案,比如将Spark番石榴罐子重命名为19版本,但总是遇到同样的问题。

怎么回事?

共有1个答案

窦哲彦
2023-03-14
    null
 类似资料:
  • 我的 Spark 版本是 2.2.0,它在本地工作,但在具有相同版本的 EMR 上,它给出了以下异常。

  • 全能的开发者们。我在Spark中运行一些基本的分析,在这里我查询多节点Cassandra。我正在运行的代码以及我正在处理的一些非链接代码是: Spark的版本是1.6.0,Cassandra v3。0.10,连接器也是1.6.0。键空间有,表有5列,实际上只有一行。如您所见,有两个节点(OracleVM中制作的虚拟Macine)。 我的问题是,当我测量从spark到cassandra的查询时间时,

  • 我使用的是datastax提供的spark-cassandra-connector 1.1.0。我注意到了interining问题,我不知道为什么会发生这样的事情:当我广播cassandra connector并试图在执行程序上使用它时,我重复了异常,这表明我的配置无效,无法在0.0.0连接到cassandra。 示例StackTrace:

  • 将现有应用程序从Spark 1.6移动到Spark 2.2*(最终)会导致错误“org.apache.spark.SparkExctive:任务不可序列化”。我过于简化了我的代码,以演示同样的错误。代码查询拼花文件以返回以下数据类型:“org.apache.spark.sql.数据集[org.apache.spark.sql.行]”我应用一个函数来提取字符串和整数,返回字符串。一个固有的问题与Sp

  • 我正在尝试了解这个位置的scala代码。(我来自java背景)。 https://github.com/apache/spark/blob/master/examples/src/main/scala/org/apache/spark/examples/GroupByTest.scala 我在下面的部分感觉完全迷失了 我知道并行化和平面映射的作用。我不明白arr1是如何初始化的。它是 int 类型

  • 我已经构建了Cassandra Server2.0.3,然后运行它。它开始,然后用消息停止: 我可以改变什么来运行它?