Я получаю указанную ниже ошибку при попытке создать DataFrame из файла csv, используя следующую команду:
val auctionDataFrame=spark.read.format("csv")
.option("inferSchema",true)
.load("/apps/auctiondata.csv")
.toDF("auctionid","bid","bidtime","bidder","bidderrate","openbid","price","item","daystolive")`
20/05/06 15:27:14 WARN ZKDataRetrieval: Can not get children of /services/resourcemanager/master with error: KeeperErrorCode = NoNode for /services/resourcemanager/master
20/05/06 15:27:14 ERROR MapRZKRMFinderUtils: Unable to determine ResourceManager service address from Zookeeper at node1:5181,node2:5181,node3:5181
java.lang.RuntimeException: Unable to determine ResourceManager service address from Zookeeper at node1:5181,node2:5181,node3:5181
at org.apache.hadoop.yarn.client.MapRZKRMFinderUtils.mapRZkBasedRMFinder(MapRZKRMFinderUtils.java:121)
at org.apache.hadoop.yarn.client.MapRZKBasedRMAddressFinder.getRMAddress(MapRZKBasedRMAddressFinder.java:43)
at org.apache.hadoop.yarn.conf.HAUtil.getCurrentRMAddress(HAUtil.java:72)
at org.apache.hadoop.mapred.Master.getMasterAddress(Master.java:60)
at org.apache.hadoop.mapred.Master.getMasterPrincipal(Master.java:74)
at org.apache.hadoop.mapreduce.security.TokenCache.obtainTokensForNamenodesInternal(TokenCache.java:114)
at org.apache.hadoop.mapreduce.security.TokenCache.obtainTokensForNamenodesInternal(TokenCache.java:100)
at org.apache.hadoop.mapreduce.security.TokenCache.obtainTokensForNamenodes(TokenCache.java:80)
at org.apache.hadoop.mapred.FileInputFormat.listStatus(FileInputFormat.java:206)
at org.apache.hadoop.mapred.FileInputFormat.getSplits(FileInputFormat.java:317)
at org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:206)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:252)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:250)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:250)
at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:35)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:252)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:250)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:250)
at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:35)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:252)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:250)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:250)
at org.apache.spark.rdd.RDD$$anonfun$take$1.apply(RDD.scala:1333)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:362)
at org.apache.spark.rdd.RDD.take(RDD.scala:1327)
at org.apache.spark.rdd.RDD$$anonfun$first$1.apply(RDD.scala:1368)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:362)
at org.apache.spark.rdd.RDD.first(RDD.scala:1367)
at org.apache.spark.sql.execution.datasources.csv.CSVFileFormat.findFirstLine(CSVFileFormat.scala:206)
at org.apache.spark.sql.execution.datasources.csv.CSVFileFormat.inferSchema(CSVFileFormat.scala:60)
at org.apache.spark.sql.execution.datasources.DataSource$$anonfun$7.apply(DataSource.scala:184)
at org.apache.spark.sql.execution.datasources.DataSource$$anonfun$7.apply(DataSource.scala:184)
at scala.Option.orElse(Option.scala:289)
at org.apache.spark.sql.execution.datasources.DataSource.org$apache$spark$sql$execution$datasources$DataSource$$getOrInferFileFormatSchema(DataSource.scala:183)
at org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:387)
at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:152)
at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:135)
... 48 elided
Я запускаю spark-shell, используя: / opt / mapr / spark / spark-2.1.0 / bin / spark-shell
Не могли бы вы помочь мне, как исправить эту ошибку. Спасибо
Abir