火花卡桑德拉连接器：无法打开卡桑德拉本机连接 [英] Spark-Cassandra Connector : Failed to open native connection to Cassandra

问题描述

我是新来的星火和卡桑德拉。在尝试提交火花的工作，同时连接到卡桑德拉我得到一个错误。

I am new to Spark and Cassandra. On trying to submit a spark job, I am getting an error while connecting to Cassandra.

详细内容：

版本：

Spark : 1.3.1 (build for hadoop 2.6 or later : spark-1.3.1-bin-hadoop2.6)
Cassandra : 2.0
Spark-Cassandra-Connector: 1.3.0-M1
scala : 2.10.5

Spark和Cassandra是一个虚拟集群
集群详细信息：

Spark and Cassandra is on a virtual cluster Cluster details:

Spark Master : 192.168.101.13
Spark Slaves : 192.168.101.11 and 192.168.101.12
Cassandra Nodes: 192.168.101.11 (seed node) and 192.168.101.12

我想通过我的客户机（笔记本）提交作业 - 172.16.0.6。
谷歌搜索这个错误之后，我确信，我可以ping从客户端计算机集群上的所有机器：火花主/从站和卡桑德拉节点，也被禁止在所有机器上的防火墙。但我是
还是与此错误挣扎。

I am trying to submit a job through my client machine (laptop) - 172.16.0.6. After googling for this error, I have made sure that I can ping all the machines on the cluster from the client machine : spark master/slaves and cassandra nodes and also disabled the firewall on all machines. But I am still struggling with this error.

Cassandra.yaml

Cassandra.yaml

listen_address: 192.168.101.11 (192.168.101.12 on other cassandra node)
start_native_transport: true
native_transport_port: 9042
start_rpc: true
rpc_address: 192.168.101.11 (192.168.101.12 on other cassandra node)
rpc_port: 9160

我试图运行最小样本作业

I am trying to run a minimal sample job

import org.apache.spark.SparkContext
import org.apache.spark.SparkContext._
import org.apache.spark.SparkConf
import org.apache.spark.rdd.RDD
import com.datastax.spark.connector._

val rdd = sc.cassandraTable("test", "words")
rdd.toArray.foreach(println)

要提交作业，我用火花外壳（：粘贴火花壳code）：

To submit the job, I use spark-shell (:paste the code in spark shell):

    spark-shell --jars "/home/ameya/.m2/repository/com/datastax/spark/spark-cassandra-connector_2.10/1.3.0-M1/spark-cassandra-connector_2.10-1.3.0-M1.jar","/home/ameya/.m2/repository/com/datastax/cassandra/cassandra-driver-core/2.1.5/cassandra-driver-core-2.1.5.jar","/home/ameya/.m2/repository/com/google/collections/google-collections/1.0/google-collections-1.0.jar","/home/ameya/.m2/repository/io/netty/netty/3.8.0.Final/netty-3.8.0.Final.jar","/home/ameya/.m2/repository/com/google/guava/guava/14.0.1/guava-14.0.1.jar","/home/ameya/.m2/repository/io/dropwizard/metrics/metrics-core/3.1.0/metrics-core-3.1.0.jar","/home/ameya/.m2/repository/org/slf4j/slf4j-api/1.7.10/slf4j-api-1.7.10.jar","/home/ameya/.m2/repository/com/google/collections/google-collections/1.0/google-collections-1.0.jar","/home/ameya/.m2/repository/io/netty/netty/3.8.0.Final/netty-3.8.0.Final.jar","/home/ameya/.m2/repository/com/google/guava/guava/14.0.1/guava-14.0.1.jar","/home/ameya/.m2/repository/org/apache/cassandra/cassandra-clientutil/2.1.5/cassandra-clientutil-2.1.5.jar","/home/ameya/.m2/repository/joda-time/joda-time/2.3/joda-time-2.3.jar","/home/ameya/.m2/repository/org/apache/cassandra/cassandra-thrift/2.1.3/cassandra-thrift-2.1.3.jar","/home/ameya/.m2/repository/org/joda/joda-convert/1.2/joda-convert-1.2.jar","/home/ameya/.m2/repository/org/apache/thrift/libthrift/0.9.2/libthrift-0.9.2.jar","/home/ameya/.m2/repository/org/apache/thrift/libthrift/0.9.2/libthrift-0.9.2.jar" --master spark://192.168.101.13:7077 --conf spark.cassandra.connection.host=192.168.101.11 --conf spark.cassandra.auth.username=cassandra --conf spark.cassandra.auth.password=cassandra

我得到的错误：

warning: there were 1 deprecation warning(s); re-run with -deprecation for details
**java.io.IOException: Failed to open native connection to Cassandra at {192.168.101.11}:9042**
    at com.datastax.spark.connector.cql.CassandraConnector$.com$datastax$spark$connector$cql$CassandraConnector$$createSession(CassandraConnector.scala:181)
    at com.datastax.spark.connector.cql.CassandraConnector$$anonfun$2.apply(CassandraConnector.scala:167)
    at com.datastax.spark.connector.cql.CassandraConnector$$anonfun$2.apply(CassandraConnector.scala:167)
    at com.datastax.spark.connector.cql.RefCountedCache.createNewValueAndKeys(RefCountedCache.scala:31)
    at com.datastax.spark.connector.cql.RefCountedCache.acquire(RefCountedCache.scala:56)
    at com.datastax.spark.connector.cql.CassandraConnector.openSession(CassandraConnector.scala:76)
    at com.datastax.spark.connector.cql.CassandraConnector.withSessionDo(CassandraConnector.scala:104)
    at com.datastax.spark.connector.cql.CassandraConnector.withClusterDo(CassandraConnector.scala:115)
    at com.datastax.spark.connector.cql.Schema$.fromCassandra(Schema.scala:243)
    at com.datastax.spark.connector.rdd.CassandraTableRowReaderProvider$class.tableDef(CassandraTableRowReaderProvider.scala:49)
    at com.datastax.spark.connector.rdd.CassandraTableScanRDD.tableDef$lzycompute(CassandraTableScanRDD.scala:59)
    at com.datastax.spark.connector.rdd.CassandraTableScanRDD.tableDef(CassandraTableScanRDD.scala:59)
    at com.datastax.spark.connector.rdd.CassandraTableRowReaderProvider$class.verify(CassandraTableRowReaderProvider.scala:148)
    at com.datastax.spark.connector.rdd.CassandraTableScanRDD.verify(CassandraTableScanRDD.scala:59)
    at com.datastax.spark.connector.rdd.CassandraTableScanRDD.getPartitions(CassandraTableScanRDD.scala:118)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:219)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:217)
    at scala.Option.getOrElse(Option.scala:120)
    at org.apache.spark.rdd.RDD.partitions(RDD.scala:217)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:1512)
    at org.apache.spark.rdd.RDD.collect(RDD.scala:813)
    at org.apache.spark.rdd.RDD.toArray(RDD.scala:833)
    at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:33)
    at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:38)
    at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:40)
    at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:42)
    at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:44)
    at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:46)
    at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:48)
    at $iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:50)
    at $iwC$$iwC$$iwC$$iwC.<init>(<console>:52)
    at $iwC$$iwC$$iwC.<init>(<console>:54)
    at $iwC$$iwC.<init>(<console>:56)
    at $iwC.<init>(<console>:58)
    at <init>(<console>:60)
    at .<init>(<console>:64)
    at .<clinit>(<console>)
    at .<init>(<console>:7)
    at .<clinit>(<console>)
    at $print(<console>)
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:497)
    at org.apache.spark.repl.SparkIMain$ReadEvalPrint.call(SparkIMain.scala:1065)
    at org.apache.spark.repl.SparkIMain$Request.loadAndRun(SparkIMain.scala:1338)
    at org.apache.spark.repl.SparkIMain.loadAndRunReq$1(SparkIMain.scala:840)
    at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:871)
    at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:819)
    at org.apache.spark.repl.SparkILoop.reallyInterpret$1(SparkILoop.scala:856)
    at org.apache.spark.repl.SparkILoop.interpretStartingWith(SparkILoop.scala:901)
    at org.apache.spark.repl.SparkILoop.command(SparkILoop.scala:813)
    at org.apache.spark.repl.SparkILoop.processLine$1(SparkILoop.scala:656)
    at org.apache.spark.repl.SparkILoop.innerLoop$1(SparkILoop.scala:664)
    at org.apache.spark.repl.SparkILoop.org$apache$spark$repl$SparkILoop$$loop(SparkILoop.scala:669)
    at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply$mcZ$sp(SparkILoop.scala:996)
    at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply(SparkILoop.scala:944)
    at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply(SparkILoop.scala:944)
    at scala.tools.nsc.util.ScalaClassLoader$.savingContextLoader(ScalaClassLoader.scala:135)
    at org.apache.spark.repl.SparkILoop.org$apache$spark$repl$SparkILoop$$process(SparkILoop.scala:944)
    at org.apache.spark.repl.SparkILoop.process(SparkILoop.scala:1058)
    at org.apache.spark.repl.Main$.main(Main.scala:31)
    at org.apache.spark.repl.Main.main(Main.scala)
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:497)
    at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:569)
    at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:166)
    at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:189)
    at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:110)
    at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
**Caused by: com.datastax.driver.core.exceptions.NoHostAvailableException: All host(s) tried for query failed (tried: /192.168.101.11:9042 (com.datastax.driver.core.TransportException: [/192.168.101.11:9042] Connection has been closed))**
    at com.datastax.driver.core.ControlConnection.reconnectInternal(ControlConnection.java:223)
    at com.datastax.driver.core.ControlConnection.connect(ControlConnection.java:78)
    at com.datastax.driver.core.Cluster$Manager.init(Cluster.java:1236)
    at com.datastax.driver.core.Cluster.getMetadata(Cluster.java:333)
    at com.datastax.spark.connector.cql.CassandraConnector$.com$datastax$spark$connector$cql$CassandraConnector$$createSession(CassandraConnector.scala:174)
    ... 71 more

任何人都可以指出我在做什么错在这里？

Can anyone point out what am I doing wrong here ?

推荐答案

这个问题解决了。这是由于一些陷入困境的依赖关系。我建有依赖关系的罐子，并通过它来引发提交，而不是分别指定相关的罐子。

The issue resolved. It was due to some mess up with the dependencies. I built a jar with dependencies and passed it to spark-submit, instead of specifying dependent jars separately.

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