多节点 hadoop 集群中的 Apache Spark Sql 问题
Apache Spark Sql issue in multi node hadoop cluster
您好，我正在使用 Spark java api 从配置单元获取数据。此代码在 hadoop 单节点集群中工作。但是当我尝试在 hadoop 多节点集群中使用它时，它会抛出错误
org.apache.spark.SparkException: Detected yarn-cluster mode, but isn't running on a cluster. Deployment to YARN is not supported directly by SparkContext. Please use spark-submit.
注意：我已经使用 master 作为本地的单节点和 yarn-cluster 的多节点。
这是我的 java 代码
SparkConf sparkConf = new SparkConf().setAppName("Hive").setMaster("yarn-cluster");
JavaSparkContext ctx = new JavaSparkContext(sparkConf);
HiveContext sqlContext = new HiveContext(ctx.sc());
org.apache.spark.sql.Row[] result = sqlContext.sql("Select * from Tablename").collect();
我也曾尝试将 master 更改为本地，但现在它抛出了未知主机名异常。
谁能帮我解决这个问题？
已更新
错误日志
15/08/05 11:30:25 INFO Query: Reading in results for query "org.datanucleus.store.rdbms.query.SQLQuery@0" since the connection used is closing
15/08/05 11:30:25 INFO ObjectStore: Initialized ObjectStore
15/08/05 11:30:25 INFO HiveMetaStore: Added admin role in metastore
15/08/05 11:30:25 INFO HiveMetaStore: Added public role in metastore
15/08/05 11:30:25 INFO HiveMetaStore: No user is added in admin role, since config is empty
15/08/05 11:30:25 INFO SessionState: No Tez session required at this point. hive.execution.engine=mr.
15/08/05 11:30:25 INFO HiveMetaStore: 0: get_table : db=default tbl=activity
15/08/05 11:30:25 INFO audit: ugi=labuser ip=unknown-ip-addr cmd=get_table : db=default tbl=activity
15/08/05 11:30:25 WARN HiveConf: DEPRECATED: hive.metastore.ds.retry.* no longer has any effect. Use hive.hmshandler.retry.* instead
15/08/05 11:30:25 INFO deprecation: mapred.map.tasks is deprecated. Instead, use mapreduce.job.maps
15/08/05 11:30:26 INFO MemoryStore: ensureFreeSpace(399000) called with curMem=0, maxMem=1030823608
15/08/05 11:30:26 INFO MemoryStore: Block broadcast_0 stored as values in memory (estimated size 389.6 KB, free 982.7 MB)
15/08/05 11:30:26 INFO MemoryStore: ensureFreeSpace(34309) called with curMem=399000, maxMem=1030823608
15/08/05 11:30:26 INFO MemoryStore: Block broadcast_0_piece0 stored as bytes in memory (estimated size 33.5 KB, free 982.7 MB)
15/08/05 11:30:26 INFO BlockManagerInfo: Added broadcast_0_piece0 in memory on 172.16.100.7:61775 (size: 33.5 KB, free: 983.0 MB)
15/08/05 11:30:26 INFO SparkContext: Created broadcast 0 from collect at Hive.java:29
Exception in thread "main" java.lang.IllegalArgumentException: java.net.UnknownHostException: hadoopcluster
at org.apache.hadoop.security.SecurityUtil.buildTokenService(SecurityUtil.java:373)
at org.apache.hadoop.hdfs.NameNodeProxies.createNonHAProxy(NameNodeProxies.java:258)
at org.apache.hadoop.hdfs.NameNodeProxies.createProxy(NameNodeProxies.java:153)
at org.apache.hadoop.hdfs.DFSClient.<init>(DFSClient.java:602)
at org.apache.hadoop.hdfs.DFSClient.<init>(DFSClient.java:547)
at org.apache.hadoop.hdfs.DistributedFileSystem.initialize(DistributedFileSystem.java:139)
at org.apache.hadoop.fs.FileSystem.createFileSystem(FileSystem.java:2591)
at org.apache.hadoop.fs.FileSystem.access0(FileSystem.java:89)
at org.apache.hadoop.fs.FileSystem$Cache.getInternal(FileSystem.java:2625)
at org.apache.hadoop.fs.FileSystem$Cache.get(FileSystem.java:2607)
at org.apache.hadoop.fs.FileSystem.get(FileSystem.java:368)
at org.apache.hadoop.fs.Path.getFileSystem(Path.java:296)
at org.apache.hadoop.mapred.FileInputFormat.singleThreadedListStatus(FileInputFormat.java:256)
at org.apache.hadoop.mapred.FileInputFormat.listStatus(FileInputFormat.java:228)
at org.apache.hadoop.mapred.FileInputFormat.getSplits(FileInputFormat.java:313)
at org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:207)
at org.apache.spark.rdd.RDD$$anonfun$partitions.apply(RDD.scala:219)
at org.apache.spark.rdd.RDD$$anonfun$partitions.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.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:32)
at org.apache.spark.rdd.RDD$$anonfun$partitions.apply(RDD.scala:219)
at org.apache.spark.rdd.RDD$$anonfun$partitions.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.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:32)
at org.apache.spark.rdd.RDD$$anonfun$partitions.apply(RDD.scala:219)
at org.apache.spark.rdd.RDD$$anonfun$partitions.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.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:32)
at org.apache.spark.rdd.RDD$$anonfun$partitions.apply(RDD.scala:219)
at org.apache.spark.rdd.RDD$$anonfun$partitions.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:1783)
at org.apache.spark.rdd.RDD$$anonfun$collect.apply(RDD.scala:885)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:148)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:109)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:286)
at org.apache.spark.rdd.RDD.collect(RDD.scala:884)
at org.apache.spark.sql.execution.SparkPlan.executeCollect(SparkPlan.scala:105)
at org.apache.spark.sql.DataFrame.collect(DataFrame.scala:1255)
at com.Hive.main(Hive.java:29)
Caused by: java.net.UnknownHostException: hadoopcluster
... 44 more
如异常所示，yarn-cluster 模式不能直接从 SparkContext 使用。但是您可以使用 SparkContext 在独立的多节点集群上 运行 它。首先，您必须启动独立的 spark 集群，然后设置 sparkConf.setMaster("spark://HOST:PORT")，其中 HOST:PORT 是您的 spark 集群的 URL。我希望这能解决你的问题。
您好，我正在使用 Spark java api 从配置单元获取数据。此代码在 hadoop 单节点集群中工作。但是当我尝试在 hadoop 多节点集群中使用它时，它会抛出错误
org.apache.spark.SparkException: Detected yarn-cluster mode, but isn't running on a cluster. Deployment to YARN is not supported directly by SparkContext. Please use spark-submit.
注意：我已经使用 master 作为本地的单节点和 yarn-cluster 的多节点。
这是我的 java 代码
SparkConf sparkConf = new SparkConf().setAppName("Hive").setMaster("yarn-cluster");
JavaSparkContext ctx = new JavaSparkContext(sparkConf);
HiveContext sqlContext = new HiveContext(ctx.sc());
org.apache.spark.sql.Row[] result = sqlContext.sql("Select * from Tablename").collect();
我也曾尝试将 master 更改为本地，但现在它抛出了未知主机名异常。
谁能帮我解决这个问题？
已更新
错误日志
15/08/05 11:30:25 INFO Query: Reading in results for query "org.datanucleus.store.rdbms.query.SQLQuery@0" since the connection used is closing
15/08/05 11:30:25 INFO ObjectStore: Initialized ObjectStore
15/08/05 11:30:25 INFO HiveMetaStore: Added admin role in metastore
15/08/05 11:30:25 INFO HiveMetaStore: Added public role in metastore
15/08/05 11:30:25 INFO HiveMetaStore: No user is added in admin role, since config is empty
15/08/05 11:30:25 INFO SessionState: No Tez session required at this point. hive.execution.engine=mr.
15/08/05 11:30:25 INFO HiveMetaStore: 0: get_table : db=default tbl=activity
15/08/05 11:30:25 INFO audit: ugi=labuser ip=unknown-ip-addr cmd=get_table : db=default tbl=activity
15/08/05 11:30:25 WARN HiveConf: DEPRECATED: hive.metastore.ds.retry.* no longer has any effect. Use hive.hmshandler.retry.* instead
15/08/05 11:30:25 INFO deprecation: mapred.map.tasks is deprecated. Instead, use mapreduce.job.maps
15/08/05 11:30:26 INFO MemoryStore: ensureFreeSpace(399000) called with curMem=0, maxMem=1030823608
15/08/05 11:30:26 INFO MemoryStore: Block broadcast_0 stored as values in memory (estimated size 389.6 KB, free 982.7 MB)
15/08/05 11:30:26 INFO MemoryStore: ensureFreeSpace(34309) called with curMem=399000, maxMem=1030823608
15/08/05 11:30:26 INFO MemoryStore: Block broadcast_0_piece0 stored as bytes in memory (estimated size 33.5 KB, free 982.7 MB)
15/08/05 11:30:26 INFO BlockManagerInfo: Added broadcast_0_piece0 in memory on 172.16.100.7:61775 (size: 33.5 KB, free: 983.0 MB)
15/08/05 11:30:26 INFO SparkContext: Created broadcast 0 from collect at Hive.java:29
Exception in thread "main" java.lang.IllegalArgumentException: java.net.UnknownHostException: hadoopcluster
at org.apache.hadoop.security.SecurityUtil.buildTokenService(SecurityUtil.java:373)
at org.apache.hadoop.hdfs.NameNodeProxies.createNonHAProxy(NameNodeProxies.java:258)
at org.apache.hadoop.hdfs.NameNodeProxies.createProxy(NameNodeProxies.java:153)
at org.apache.hadoop.hdfs.DFSClient.<init>(DFSClient.java:602)
at org.apache.hadoop.hdfs.DFSClient.<init>(DFSClient.java:547)
at org.apache.hadoop.hdfs.DistributedFileSystem.initialize(DistributedFileSystem.java:139)
at org.apache.hadoop.fs.FileSystem.createFileSystem(FileSystem.java:2591)
at org.apache.hadoop.fs.FileSystem.access0(FileSystem.java:89)
at org.apache.hadoop.fs.FileSystem$Cache.getInternal(FileSystem.java:2625)
at org.apache.hadoop.fs.FileSystem$Cache.get(FileSystem.java:2607)
at org.apache.hadoop.fs.FileSystem.get(FileSystem.java:368)
at org.apache.hadoop.fs.Path.getFileSystem(Path.java:296)
at org.apache.hadoop.mapred.FileInputFormat.singleThreadedListStatus(FileInputFormat.java:256)
at org.apache.hadoop.mapred.FileInputFormat.listStatus(FileInputFormat.java:228)
at org.apache.hadoop.mapred.FileInputFormat.getSplits(FileInputFormat.java:313)
at org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:207)
at org.apache.spark.rdd.RDD$$anonfun$partitions.apply(RDD.scala:219)
at org.apache.spark.rdd.RDD$$anonfun$partitions.apply(RDD.scala:217)
at scala.Option.getOrElse(Option.scala:120)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:217)
at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:32)
at org.apache.spark.rdd.RDD$$anonfun$partitions.apply(RDD.scala:219)
at org.apache.spark.rdd.RDD$$anonfun$partitions.apply(RDD.scala:217)
at scala.Option.getOrElse(Option.scala:120)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:217)
at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:32)
at org.apache.spark.rdd.RDD$$anonfun$partitions.apply(RDD.scala:219)
at org.apache.spark.rdd.RDD$$anonfun$partitions.apply(RDD.scala:217)
at scala.Option.getOrElse(Option.scala:120)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:217)
at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:32)
at org.apache.spark.rdd.RDD$$anonfun$partitions.apply(RDD.scala:219)
at org.apache.spark.rdd.RDD$$anonfun$partitions.apply(RDD.scala:217)
at scala.Option.getOrElse(Option.scala:120)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:217)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1783)
at org.apache.spark.rdd.RDD$$anonfun$collect.apply(RDD.scala:885)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:148)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:109)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:286)
at org.apache.spark.rdd.RDD.collect(RDD.scala:884)
at org.apache.spark.sql.execution.SparkPlan.executeCollect(SparkPlan.scala:105)
at org.apache.spark.sql.DataFrame.collect(DataFrame.scala:1255)
at com.Hive.main(Hive.java:29)
Caused by: java.net.UnknownHostException: hadoopcluster
... 44 more
如异常所示，yarn-cluster 模式不能直接从 SparkContext 使用。但是您可以使用 SparkContext 在独立的多节点集群上 运行 它。首先，您必须启动独立的 spark 集群，然后设置 sparkConf.setMaster("spark://HOST:PORT")，其中 HOST:PORT 是您的 spark 集群的 URL。我希望这能解决你的问题。