Spark操作HBase

Spark写HBase

　　要通过Spark向 HBase 写入数据，我们需要用到PairRDDFunctions.saveAsHadoopDataset的方式。

package cn.com.win

import org.apache.hadoop.hbase.HBaseConfiguration
import org.apache.hadoop.hbase.client.Put
import org.apache.hadoop.hbase.io.ImmutableBytesWritable
import org.apache.hadoop.hbase.mapred.TableOutputFormat
import org.apache.hadoop.hbase.util.Bytes
import org.apache.hadoop.mapred.JobConf
import org.apache.log4j.Logger
import org.apache.spark.{SparkConf, SparkContext}

object TestHbase {

  def main(args: Array[String]) {

    val log = Logger.getLogger("TestHbase")
    //初始化Spark
    val conf = new SparkConf().setMaster("local[2]").setAppName("testHbase")
    val sc = new SparkContext(conf)

　　 // 定义HBase 的配置
    val hconf = HBaseConfiguration.create()
    val jobConf = new JobConf(hconf, this.getClass)
　　 // 指定输出格式和输出的表名
    jobConf.setOutputFormat(classOf[TableOutputFormat])
    jobConf.set(TableOutputFormat.OUTPUT_TABLE, "wifiTarget")

    val arr = Array(("tjiloaB#3#20190520", 10, 11), ("tjiloaB#3#20190521", 12, 22), ("tjiloaB#3#20190522", 13, 42))
    val rdd = sc.parallelize(arr)
    val localData = rdd.map(convert)

    localData.saveAsHadoopDataset(jobConf)

    sc.stop()
  }
　

  // 定义函数 RDD -> RDD[(ImmutableBytesWritable,Put)]
  def convert(triple: (String, Int, Int)) = {
    val p = new Put(Bytes.toBytes(triple._1))
    p.addColumn(Bytes.toBytes("wifiTargetCF"), Bytes.toBytes("inNum"), Bytes.toBytes(triple._2))
    p.addColumn(Bytes.toBytes("wifiTargetCF"), Bytes.toBytes("outNum"), Bytes.toBytes(triple._3))
    (new ImmutableBytesWritable, p)
  }
}

　　执行结果：

　　

 Spark读取HBase

　　Spark读取HBase，我们主要使用SparkContext 提供的newAPIHadoopRDDAPI将表的内容以 RDDs 的形式加载到 Spark 中。

指定列：

import org.apache.hadoop.hbase.HBaseConfiguration
import org.apache.hadoop.hbase.client.Scan
import org.apache.hadoop.hbase.filter.PrefixFilter
import org.apache.hadoop.hbase.mapreduce.{TableInputFormat, TableOutputFormat}
import org.apache.hadoop.hbase.protobuf.ProtobufUtil
import org.apache.hadoop.hbase.util.{Base64, Bytes}
import org.apache.spark.{SparkConf, SparkContext}

/**
  * AUTHOR Guozy
  * DATE   2020/2/7-0:33
  **/
object TestHbase2 {
  def main(args: Array[String]): Unit = {

    //初始化Spark
    val conf = new SparkConf().setMaster("local[2]").setAppName("testHbase")
    conf.set("spark.serializer", "org.apache.spark.serializer.KryoSerializer")
    val sc = new SparkContext(conf)

    val scan = new Scan()
    val filter = new PrefixFilter("tjiloaB#3#20190520".getBytes())
    scan.setFilter(filter)
    val hconf = HBaseConfiguration.create()
    hconf.set(TableInputFormat.INPUT_TABLE, "wifiTarget")
    hconf.set(TableInputFormat.SCAN, convertScanToString(scan))

    val dataRdd = sc.newAPIHadoopRDD(hconf, classOf[TableInputFormat],
      classOf[org.apache.hadoop.hbase.io.ImmutableBytesWritable],
      classOf[org.apache.hadoop.hbase.client.Result])

    val count = dataRdd.count()
    println("dataRdd Count is " + count)
    dataRdd.cache()

    dataRdd.map(_._2).filter(!_.isEmpty).take(20).foreach { result =>
      val key = Bytes.toString(result.getRow)
      val innum = Bytes.toInt(result.getValue(Bytes.toBytes("wifiTargetCF"), Bytes.toBytes("inNum")))
      val outnum = Bytes.toInt(result.getValue(Bytes.toBytes("wifiTargetCF"), Bytes.toBytes("outNum")))
      println(s"key:${key},inNum:${innum},outNum:${outnum}")
    }
    sc.stop()
  }

  /**
    * 将Scan转换为String
    */
  def convertScanToString(scan: Scan): String = {
    val proto = ProtobufUtil.toScan(scan);
    Base64.encodeBytes(proto.toByteArray());
  }

运行结果：

循环遍历列：

import org.apache.hadoop.hbase.HBaseConfiguration
import org.apache.hadoop.hbase.client.Scan
import org.apache.hadoop.hbase.filter.PrefixFilter
import org.apache.hadoop.hbase.mapreduce.{TableInputFormat, TableOutputFormat}
import org.apache.hadoop.hbase.protobuf.ProtobufUtil
import org.apache.hadoop.hbase.util.{Base64, Bytes}
import org.apache.spark.{SparkConf, SparkContext}

/**
  * AUTHOR Guozy
  * DATE   2020/2/7-0:33
  **/
object TestHbase2 {
  def main(args: Array[String]): Unit = {

    //初始化Spark
    val conf = new SparkConf().setMaster("local[2]").setAppName("testHbase")
    conf.set("spark.serializer", "org.apache.spark.serializer.KryoSerializer")
    val sc = new SparkContext(conf)

    val scan = new Scan()
    val filter = new PrefixFilter("tjiloaB#3#20190520".getBytes())
    scan.setFilter(filter)
    val hconf = HBaseConfiguration.create()
    hconf.set(TableInputFormat.INPUT_TABLE, "wifiTarget")
    hconf.set(TableInputFormat.SCAN, convertScanToString(scan))

    val dataRdd = sc.newAPIHadoopRDD(hconf, classOf[TableInputFormat],
      classOf[org.apache.hadoop.hbase.io.ImmutableBytesWritable],
      classOf[org.apache.hadoop.hbase.client.Result])

    val count = dataRdd.count()
    println("dataRdd Count is " + count)
    dataRdd.cache()

    dataRdd.map(_._2).filter(!_.isEmpty).take(20).foreach { result =>
      val key = Bytes.toString(result.getRow)
      val cells = result.listCells().iterator()
         while (cells.hasNext) {
           val cell = cells.next()
           val innum = Bytes.toInt(cell.getValueArray, cell.getValueOffset, cell.getValueLength)
           val outnum = Bytes.toInt(result.getValue(Bytes.toBytes("wifiTargetCF"), Bytes.toBytes("outNum")))
           println(s"key:${key},inNum:${innum},outNum:${outnum}")
         }
    }
    sc.stop()
  }

  /**
    * 将Scan转换为String
    */
  def convertScanToString(scan: Scan): String = {
    val proto = ProtobufUtil.toScan(scan);
    Base64.encodeBytes(proto.toByteArray());
  }

运行结果

注意：在导入包的时候，TableInputFormat对应的包是 org.apache.hadoop.hbase.mapreduce,而不是 org.apache.hadoop.hbase.maped