Spark2.x读Hbase1-2.x
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import org.apache.hadoop.hbase.HBaseConfiguration import org.apache.hadoop.hbase.mapreduce.TableInputFormat import org.apache.hadoop.hbase.util.Bytes import org.apache.spark.{SparkConf, SparkContext} /** * 读取HBase表数据 */ object SparkOperateHBase { def main(args: Array[String]): Unit = { val conf = HBaseConfiguration.create() val sc = new SparkContext(new SparkConf()) conf.set(TableInputFormat.INPUT_TABLE,"student") val stuRDD = sc.newAPIHadoopRDD(conf, classOf[TableInputFormat], classOf[org.apache.hadoop.hbase.io.ImmutableBytesWritable], classOf[org.apache.hadoop.hbase.client.Result]) stuRDD.cache() val count = stuRDD.count() println("Students RDDCount: " + count) //读取HBase表数据并打印出来 stuRDD.foreach({case (_,result) => val key = Bytes.toString(result.getRow) val name = Bytes.toString(result.getValue("info".getBytes,"name".getBytes())) val gender = Bytes.toString(result.getValue("info".getBytes,"gender".getBytes())) val age = Bytes.toString(result.getValue("info".getBytes,"age".getBytes())) println("Row key:" + key + " Name: " + name + " Gender: " + gender + " Age: " + age) }) //读取HBase表数据并转为RDD val resRDD = stuRDD.map(res => { val key = Bytes.toString(res._2.getRow) val name = Bytes.toString(res._2.getValue("info".getBytes,"name".getBytes())) val gender = Bytes.toString(res._2.getValue("info".getBytes,"gender".getBytes())) val age = Bytes.toString(res._2.getValue("info".getBytes,"age".getBytes())) (key, name, gender, age) }) } }
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