val jobConf = new JobConf(hbaseConf)
jobConf.setOutputFormat(classOf[TableOutputFormat])
jobConf.set(TableOutputFormat.OUTPUT_TABLE, tablename)
val indataRDD = sc.makeRDD(Array("1,jack,15","2,Lily,16","3,mike,16"))
indataRDD.map(_.split(','))
val rdd = indataRDD.map(_.split(',')).map{arr=>{
val put = new Put(Bytes.toBytes(arr(0).toInt))
put.add(Bytes.toBytes("cf"),Bytes.toBytes("name"),Bytes.toBytes(arr(1)))
put.add(Bytes.toBytes("cf"),Bytes.toBytes("age"),Bytes.toBytes(arr(2).toInt))
(new ImmutableBytesWritable, put)
}}
rdd.saveAsHadoopDataset(jobConf)
当我运行hadoop或spark作业时,我经常遇到错误:
Exception in thread "main" java.lang.NoSuchMethodError: org.apache.hadoop.mapred.TaskID.<init>(Lorg/apache/hadoop/mapreduce/JobID;Lorg/apache/hadoop/mapreduce/TaskType;I)V
at org.apache.spark.SparkHadoopWriter.setIDs(SparkHadoopWriter.scala:158)
at org.apache.spark.SparkHadoopWriter.preSetup(SparkHadoopWriter.scala:60)
at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopDataset$1.apply$mcV$sp(PairRDDFunctions.scala:1188)
at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopDataset$1.apply(PairRDDFunctions.scala:1161)
at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopDataset$1.apply(PairRDDFunctions.scala:1161)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:358)
at org.apache.spark.rdd.PairRDDFunctions.saveAsHadoopDataset(PairRDDFunctions.scala:1161)
at com.iteblog.App$.main(App.scala:62)
at com.iteblog.App.main(App.scala)`
在开始时,我想,是罐子冲突,但我仔细检查了罐子:没有其他罐子。 spark和hadoop版本是:
<groupId>org.apache.spark</groupId>
<artifactId>spark-core_2.11</artifactId>
<version>2.0.1</version>`
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-core</artifactId>
<version>2.6.0-mr1-cdh5.5.0</version>
我发现TaskID和TaskType都在 hadoop-core jar中,但不在同一个包中。为什么mapred.TaskID可以引用mapreduce.TaskType?
答案 0 :(得分:1)
哦,我已经解决了这个问题,添加了maven依赖
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-mapreduce-client-core</artifactId>
<version>2.6.0-cdh5.5.0</version>
</dependency>
错误消失了!
答案 1 :(得分:0)