spark与hbase怎么用

小编给大家分享一下spark与hbase怎么用，希望大家阅读完这篇文章之后都有所收获，下面让我们一起去探讨吧！

package hgs.spark.hbase
import org.apache.spark.SparkConf
import org.apache.spark.SparkContext
import org.apache.hadoop.conf.Configuration
import org.apache.hadoop.hbase.HBaseConfiguration
import org.apache.spark.rdd.NewHadoopRDD
import org.apache.hadoop.hbase.mapreduce.TableInputFormat
object HbaseTest {
  def main(args: Array[String]): Unit = {
    val conf = new SparkConf
    
    conf.setMaster("local").setAppName("local")
    
    val context = new SparkContext(conf)
    
    val hadoopconf = new HBaseConfiguration
    hadoopconf.set("hbase.zookeeper.quorum", "bigdata01:2181,bigdata02:2181,bigdata03:2181")
    hadoopconf.set("hbase.zookeeper.property.clientPort", "2181")
    val tableName = "test1"
    hadoopconf.set(TableInputFormat.INPUT_TABLE, tableName)
    hadoopconf.set(TableInputFormat.SCAN_ROW_START, "h")
    hadoopconf.set(TableInputFormat.SCAN_ROW_STOP, "x")
    hadoopconf.set(TableInputFormat.SCAN_COLUMN_FAMILY, "cf1")
    hadoopconf.set(TableInputFormat.SCAN_COLUMNS, "cf1:col1,cf1:col2")
    
    /*val startrow = "h"
    val stoprow = "w"
    
    val scan = new Scan
    scan.setStartRow(startrow.getBytes)
    scan.setStartRow(stoprow.getBytes)
    
    val proto = ProtobufUtil.toScan(scan)
    val scanToString = Base64.encodeBytes(proto.toByteArray())
    println(scanToString)
    hadoopconf.set(TableInputFormat.SCAN, scanToString)
    */
    val hbaseRdd = context.newAPIHadoopRDD(hadoopconf, 
        classOf[TableInputFormat], 
        classOf[org.apache.hadoop.hbase.io.ImmutableBytesWritable],
        classOf[org.apache.hadoop.hbase.client.Result])
        
        hbaseRdd.foreach(x=>{
         val vale =  x._2.getValue("cf1".getBytes, "col1".getBytes)
         val val2 = x._2.getValue("cf1".getBytes, "col2".getBytes)
          println(new String(vale),new String(val2))
        })
    context.stop()    
  }
}

package hgs.spark.hbase
import org.apache.spark.SparkConf
import org.apache.spark.SparkContext
import org.apache.hadoop.hbase.HBaseConfiguration
import org.apache.hadoop.hbase.mapred.TableOutputFormat
import org.apache.hadoop.mapred.JobConf
import org.apache.hadoop.hbase.client.Put
import org.apache.hadoop.hbase.io.ImmutableBytesWritable
object SparkToHbase {
  def main(args: Array[String]): Unit = {
    val conf = new SparkConf
    
    conf.setMaster("local").setAppName("local")
    
    val context = new SparkContext(conf)
    
    val rdd = context.parallelize(List(("aaaaaaa","aaaaaaa"),("bbbbb","bbbbb")), 2)
    val hadoopconf = new HBaseConfiguration
    hadoopconf.set("hbase.zookeeper.quorum", "bigdata01:2181,bigdata02:2181,bigdata03:2181")
    hadoopconf.set("hbase.zookeeper.property.clientPort", "2181")
    hadoopconf.set(TableOutputFormat.OUTPUT_TABLE, "test1")
    //hadoopconf.set(TableOutputFormat., "test1")
    
    val jobconf  = new JobConf(hadoopconf,this.getClass)
    jobconf.set(TableOutputFormat.OUTPUT_TABLE, "test1")
    jobconf.setOutputFormat(classOf[TableOutputFormat])
    
    val exterrdd = rdd.map(x=>{
      
      val put = new Put(x._1.getBytes)
      put.add("cf1".getBytes, "col1".getBytes, x._2.getBytes)
      (new ImmutableBytesWritable,put)
    })
    
    exterrdd.saveAsHadoopDataset(jobconf)
    
    context.stop()
    
    
    
  }
}

看完了这篇文章，相信你对“spark与hbase怎么用”有了一定的了解，如果想了解更多相关知识，欢迎关注亿速云行业资讯频道，感谢各位的阅读！