还是关于导入hbase的问题。。

本帖最后由 remarkzhao 于 2017-8-28 13:26 编辑

如何从sqlserver里把数据导入到hbase里，这个问题纠结了我一个月，各种方法的取舍，以及判断还是有点迷糊，目前想尝试以下方法还是有点问题望
各位大神指教一下

方案：从sqlserver里拉去dataframe，再保存为RDD，然后在用RDD导入hbase的api进行hbase的数据导入

目前遇到的问题：

   1. scala代码编写之后打成jar进行提交的时候出现下标越界异常

   2. 打jar的时候有时候会遇到错误：找不到spark-parent_2.11-2.2.0.jar
      在idea开发的时候错误是这样的：SBT project import: [error] Server access Error: Connection timed out: connect url=http://maven.ibiblio.org/maven2/org/apache/spark/spark-parent_2.11/2.2.0/spark-parent_2.11-2.2.0.jar，但是很奇怪，在linux下直接 sbt/sbt pacage 有时候就可以有时候就不可以。

   3. 有没有scala的算子直接把sqlserver里拉出的dataframe 保存为rdd  或者拉出来的就是RDD 不是dataframe ，我这个是先dataframe以保存rdd的形式到本地再用textFile拿出来。

代码如下，望各位大神指点：

import org.apache.hadoop.conf.Configuration
import org.apache.hadoop.hbase._
import org.apache.hadoop.hbase.client._
import org.apache.hadoop.hbase.mapreduce.TableInputFormat
import org.apache.hadoop.hbase.util.Bytes
import org.apache.spark.SparkContext
import org.apache.spark.SparkContext._
import org.apache.spark.SparkConf

object ImportToHBase{

def main(args: Array[String]){

   val conf = HBaseConfiguration.create()
   val sc = new SparkContext(new SparkConf())

   val readFile = sc.textFile("file:///root/tools/spark/mycode/DC_EXAM_RESULT.txt").map(x => x.split(","))  //DC_EXAM_RESULT.txt 是我从sqlserver拉出来dataframe进行 .rdd.saveAsTexFile之后的目录，目录下的问part-00000是csv文件，以逗号为分隔符
val tableName = "Document"
readFile.foreachPartition{
  x=> {
val myConf = HBaseConfiguration.create()
myConf.set("hbase.zookeeper.quorum", "hadoop001,hadoop002,hadoop003")
myConf.set("hbase.zookeeper.property.clientPort", "2181")
myConf.set("hbase.defaults.for.version.skip", "true")
val myTable = new HTable(myConf, TableName.valueOf(tableName))
myTable.setAutoFlush(false, false)
myTable.setWriteBufferSize(5*1024*1024)
x.foreach { y => {
   val p = new Put(Bytes.toBytes(y(3))) // csv的第4列为rowkey
   p.add("Family".getBytes, "qualifier".getBytes, Bytes.toBytes(y(45))) //csv的第46列为列族的列的内容，只有一个列族，一个列。
   myTable.put(p)
}
}
myTable.flushCommits()

}

}

  }
}

以下是异常：

  [Stage 0:>                                                       (0 + 1) / 36]15711 [Executor task launch worker for task 0] ERROR org.apache.spark.executor.Executor  - Exception in task 0.0 in stage 0.0 (TID 0)
java.lang.ArrayIndexOutOfBoundsException: 45
      at ImportToHBase$$anonfun$main$1$$anonfun$apply$1.apply(ImportToHBase.scala:30)
      at ImportToHBase$$anonfun$main$1$$anonfun$apply$1.apply(ImportToHBase.scala:28)
      at scala.collection.Iterator$class.foreach(Iterator.scala:893)
      at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
      at ImportToHBase$$anonfun$main$1.apply(ImportToHBase.scala:28)
      at ImportToHBase$$anonfun$main$1.apply(ImportToHBase.scala:20)
      at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1$$anonfun$apply$29.apply(RDD.scala:926)
      at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1$$anonfun$apply$29.apply(RDD.scala:926)
      at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2062)
      at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2062)
      at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
      at org.apache.spark.scheduler.Task.run(Task.scala:108)
      at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:335)
      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:748)
16114 [task-result-getter-0] ERROR org.apache.spark.scheduler.TaskSetManager  - Task 0 in stage 0.0 failed 1 times; aborting job
Exception in thread "main" org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 0.0 failed 1 times, most recent failure: Lost task 0.0 in stage 0.0 (TID 0, localhost, executor driver): java.lang.ArrayIndexOutOfBoundsException: 45
      at ImportToHBase$$anonfun$main$1$$anonfun$apply$1.apply(ImportToHBase.scala:30)
      at ImportToHBase$$anonfun$main$1$$anonfun$apply$1.apply(ImportToHBase.scala:28)
      at scala.collection.Iterator$class.foreach(Iterator.scala:893)
      at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
      at ImportToHBase$$anonfun$main$1.apply(ImportToHBase.scala:28)
      at ImportToHBase$$anonfun$main$1.apply(ImportToHBase.scala:20)
      at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1$$anonfun$apply$29.apply(RDD.scala:926)
      at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1$$anonfun$apply$29.apply(RDD.scala:926)
      at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2062)
      at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2062)
      at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
      at org.apache.spark.scheduler.Task.run(Task.scala:108)
      at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:335)
      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:748)

Driver stacktrace:
      at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1499)
      at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1487)
      at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1486)
      at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
      at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
      at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1486)
      at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:814)
      at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:814)
      at scala.Option.foreach(Option.scala:257)
      at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:814)
      at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1714)
      at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1669)
      at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1658)
      at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
      at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:630)
      at org.apache.spark.SparkContext.runJob(SparkContext.scala:2022)
      at org.apache.spark.SparkContext.runJob(SparkContext.scala:2043)
      at org.apache.spark.SparkContext.runJob(SparkContext.scala:2062)
      at org.apache.spark.SparkContext.runJob(SparkContext.scala:2087)
      at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1.apply(RDD.scala:926)
      at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1.apply(RDD.scala:924)
      at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
      at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
      at org.apache.spark.rdd.RDD.withScope(RDD.scala:362)
      at org.apache.spark.rdd.RDD.foreachPartition(RDD.scala:924)
      at ImportToHBase$.main(ImportToHBase.scala:19)
      at ImportToHBase.main(ImportToHBase.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:498)
      at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:755)
      at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:180)
      at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:205)
      at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:119)
      at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Caused by: java.lang.ArrayIndexOutOfBoundsException: 45
      at ImportToHBase$$anonfun$main$1$$anonfun$apply$1.apply(ImportToHBase.scala:30)
      at ImportToHBase$$anonfun$main$1$$anonfun$apply$1.apply(ImportToHBase.scala:28)
      at scala.collection.Iterator$class.foreach(Iterator.scala:893)
      at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
      at ImportToHBase$$anonfun$main$1.apply(ImportToHBase.scala:28)
      at ImportToHBase$$anonfun$main$1.apply(ImportToHBase.scala:20)
      at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1$$anonfun$apply$29.apply(RDD.scala:926)
      at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1$$anonfun$apply$29.apply(RDD.scala:926)
      at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2062)
      at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2062)
      at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
      at org.apache.spark.scheduler.Task.run(Task.scala:108)
      at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:335)
      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:748)
16608 [Thread-2] INFO  org.spark_project.jetty.server.AbstractConnector  - Stopped Spark@431a7c26{HTTP/1.1,[http/1.1]}{0.0.0.0:4041}

sstutu · 发表于 2017-8-28 13:21:25

个人观点仅供参考：
1. scala代码编写之后打成jar进行提交的时候出现下标越界异常
越界，里面没有发现数组，不知道是不是spark里面造成的。对于main函数，这个Array楼主输入的什么。这个也需要看看。
def main(args: Array[String])

2. 打jar的时候有时候会遇到错误：找不到spark-parent_2.11-2.2.0.jar
在idea开发的时候错误是这样的：SBT project import: [error] Server access Error: Connection timed out: connect url=http://maven.ibiblio.org/maven2/org/apache/spark/spark-parent_2.11/2.2.0/spark-parent_2.11-2.2.0.jar，但是很奇怪，在linux下直接 sbt/sbt pacage 有时候就可以有时候就不可以。
这个最好下载到本地库，很可能是因为网络的原因造成的

3. 有scala的算子直接把sqlserver里拉出的dataframe 保存为rdd 或者拉出来的就是RDD 不是dataframe （这个问题好像有点low）
楼主的代码应该用的就是rdd，而非DataFrame
推荐参考spark小知识总结
http://www.aboutyun.com/forum.php?mod=viewthread&tid=20920

remarkzhao · 发表于 2017-8-28 13:30:46

sstutu 发表于 2017-8-28 13:21
个人观点仅供参考：
1. scala代码编写之后打成jar进行提交的时候出现下标越界异常
越界，里面没有发现 ...

恩恩。明白。。

spark 提交的语句是这句： spark-submit --driver-class-path /root/tools/spark/jars/hbase/*:/root/tools/spark/jars/*:/root/tools/hbase/conf --class ImportToHBase /root/tools/spark/mycode/hbase/target/scala-2.11/simple-project_2.11-1.0.jar

异常里提示的下标越界是指我scala代码中写的 28行跟30行有问题。所以应该不会在main函数里有错误。

spark_parent 那个jar我找过maven 跟ali的镜像居然没找到这个jar包，也是醉了。

我scala代码中用的是rdd ，我原先用scala从sqlserver里拉过来保存到本地的。

无论如何多谢了。

还有大神指点一下吗？？求助ING。

nextuser · 发表于 2017-8-28 13:44:41

remarkzhao 发表于 2017-8-28 13:30
恩恩。明白。。

spark 提交的语句是这句： spark-submit --driver-class-path /root/tools/spark/jars ...

越界的代码行，贴出来看下

remarkzhao · 发表于 2017-8-28 13:46:18

nextuser 发表于 2017-8-28 13:44
越界的代码行，贴出来看下

恩恩。。。来了。。object ImportToHBase{

def main(args: Array[String]){

   val conf = HBaseConfiguration.create()
   val sc = new SparkContext(new SparkConf())

   val readFile = sc.textFile("file:///root/tools/spark/mycode/DC_EXAM_RESULT.txt").map(x => x.split(","))  //DC_EXAM_RESULT.txt 是我从sqlserver拉出来dataframe进行 .rdd.saveAsTexFile之后的目录，目录下的问part-00000是csv文件，以逗号为分隔符
val tableName = "Document"
readFile.foreachPartition{
  x=> {
val myConf = HBaseConfiguration.create()
myConf.set("hbase.zookeeper.quorum", "hadoop001,hadoop002,hadoop003")
myConf.set("hbase.zookeeper.property.clientPort", "2181")
myConf.set("hbase.defaults.for.version.skip", "true")
val myTable = new HTable(myConf, TableName.valueOf(tableName))
myTable.setAutoFlush(false, false)
myTable.setWriteBufferSize(5*1024*1024)
x.foreach { y => {
  val p = new Put(Bytes.toBytes(y(3))) // csv的第4列为rowkey
   p.add("Family".getBytes, "qualifier".getBytes, Bytes.toBytes(y(45))) //csv的第46列为列族的列的内容，只有一个列族，一个列。
   myTable.put(p)
}
}
myTable.flushCommits()

}

}

  }
}

nextuser · 发表于 2017-8-28 13:57:48

remarkzhao 发表于 2017-8-28 13:46
恩恩。。。来了。。object ImportToHBase{

def main(args: Array[String]){

val p = new Put(Bytes.toBytes(y(3))) // csv的第4列为rowkey

rowkey 最大为64KB。看看是不有的超过了。
来自：
hbase cell最大字节数多少
http://www.aboutyun.com/forum.php?mod=viewthread&tid=10413

remarkzhao · 发表于 2017-8-28 14:06:41

nextuser 发表于 2017-8-28 13:57
val p = new Put(Bytes.toBytes(y(3))) // csv的第4列为rowkey

rowkey 最大为64KB。看看是不 ...

rowkey也没多大啊固定长度跟格式： 10_00048113_020161224150834

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