最近项目中用频繁使用spark从hbase中读数据和向hbase中写数据,下面总结了一些简单demo, 在此基础上可以通过hbaseAPI进行各种复杂查询与写操作 希望能帮助到你
向Hbase中写数据方案一:
package utils
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.spark.SparkConf
import org.apache.spark.SparkContext
import org.apache.spark.rdd.RDD
import org.apache.spark.rdd.RDD.rddToPairRDDFunctions
/*
将数据写入到hbase中
*/
object HbaseTestWrite01 {
def main(args: Array[String]): Unit = {
val sparkConf = new SparkConf().setAppName("HBaseTest").setMaster("local")
val sc = new SparkContext(sparkConf)
val conf = HBaseConfiguration.create()
//设置zooKeeper集群地址,也可以通过将hbase-site.xml导入classpath,但是建议在程序里这样设置
conf.set("hbase.zookeeper.quorum","node-1,node-2,node-3")
//设置zookeeper连接端口,默认2181
conf.set("hbase.zookeeper.property.clientPort", "2181")
val tablename = "test"
//初始化jobconf,TableOutputFormat必须是org.apache.hadoop.hbase.mapred包下的!
val jobConf = new JobConf(conf)
jobConf.setOutputFormat(classOf[TableOutputFormat])
jobConf.set(TableOutputFormat.OUTPUT_TABLE, tablename)
val indataRDD: RDD[String] = sc.makeRDD(Array("1,jack,15","2,Lily,16","3,mike,16"))
val rdd = indataRDD.map(_.split(',')).map{arr=>{
/*一个Put对象就是一行记录,在构造方法中指定主键
* 所有插入的数据必须用org.apache.hadoop.hbase.util.Bytes.toBytes方法转换
* Put.add方法接收三个参数:列族,列名,数据
*/
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))
//转化成RDD[(ImmutableBytesWritable,Put)]类型才能调用saveAsHadoopDataset
(new ImmutableBytesWritable, put)
}}
rdd.saveAsHadoopDataset(jobConf)
sc.stop()
}
}
向Hbase中写数据方案二:
package utils
import org.apache.hadoop.hbase.mapreduce.TableOutputFormat
import org.apache.spark._
import org.apache.hadoop.mapreduce.Job
import org.apache.hadoop.hbase.io.ImmutableBytesWritable
import org.apache.hadoop.hbase.client.Result
import org.apache.hadoop.hbase.client.Put
import org.apache.hadoop.hbase.util.Bytes
object HbaseTestWrite02 {
def main(args: Array[String]): Unit = {
val sparkConf = new SparkConf().setAppName("HBaseTest").setMaster("local")
val sc = new SparkContext(sparkConf)
val tablename = "test"
sc.hadoopConfiguration.set("hbase.zookeeper.quorum","node-1,node-2,node-3")
sc.hadoopConfiguration.set("hbase.zookeeper.property.clientPort", "2181")
sc.hadoopConfiguration.set(TableOutputFormat.OUTPUT_TABLE, tablename)
val job = new Job(sc.hadoopConfiguration)
job.setOutputKeyClass(classOf[ImmutableBytesWritable])
job.setOutputValueClass(classOf[Result])
job.setOutputFormatClass(classOf[TableOutputFormat[ImmutableBytesWritable]])
val indataRDD = sc.makeRDD(Array("1,jack,15","2,Lily,16","3,mike,16"))
val rdd = indataRDD.map(_.split(',')).map{arr=>{
val put = new Put(Bytes.toBytes(arr(0)))
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.saveAsNewAPIHadoopDataset(job.getConfiguration())
}
}
从Hbase中读数据:
package utils
import org.apache.hadoop.hbase.{HBaseConfiguration, HTableDescriptor, TableName}
import org.apache.hadoop.hbase.client.HBaseAdmin
import org.apache.hadoop.hbase.mapreduce.TableInputFormat
import org.apache.spark._
import org.apache.hadoop.hbase.util.Bytes
object HbaseTestRead {
def main(args: Array[String]): Unit = {
val sparkConf = new SparkConf().setAppName("HBaseTest").setMaster("local")
val sc = new SparkContext(sparkConf)
val tablename = "test"
val conf = HBaseConfiguration.create()
//设置zooKeeper集群地址,也可以通过将hbase-site.xml导入classpath,但是建议在程序里这样设置
conf.set("hbase.zookeeper.quorum","node-1,node-2,node-3")
//设置zookeeper连接端口,默认2181
conf.set("hbase.zookeeper.property.clientPort", "2181")
conf.set(TableInputFormat.INPUT_TABLE, tablename)
// 如果表不存在则创建表
val admin = new HBaseAdmin(conf)
if (!admin.isTableAvailable(tablename)) {
val tableDesc = new HTableDescriptor(TableName.valueOf(tablename))
admin.createTable(tableDesc)
}
//读取数据并转化成rdd
val hBaseRDD = sc.newAPIHadoopRDD(conf, classOf[TableInputFormat],
classOf[org.apache.hadoop.hbase.io.ImmutableBytesWritable],
classOf[org.apache.hadoop.hbase.client.Result])
val count = hBaseRDD.count()
println(count)
hBaseRDD.foreach{case (_,result) =>{
//获取行键
val key = Bytes.toString(result.getRow)
//通过列族和列名获取列
val name = Bytes.toString(result.getValue("cf".getBytes,"name".getBytes))
val age = Bytes.toInt(result.getValue("cf".getBytes,"age".getBytes))
println("Row key:"+key+" Name:"+name+" Age:"+age)
}}
sc.stop()
admin.close()
}
}