spark3.0.1版本查询Hbase数据库例子

需求背景

现有需求，需要采用spark查询hbase数据库的数据同步到中间分析库，记录spark集成hbase的简单例子代码

import org.apache.hadoop.hbase.HBaseConfiguration
import org.apache.hadoop.hbase.client.{ConnectionFactory, Scan}
import org.apache.hadoop.hbase.util.Bytes
import org.apache.spark.sql.SparkSession

object ReadHBaseData {
  def main(args: Array[String]): Unit = {
    // 创建SparkSession
    val spark = SparkSession.builder()
      .appName("ReadHBaseData")
      .master("local")
      .getOrCreate()
      
    // 创建HBase配置
    val conf = HBaseConfiguration.create()

    // 设置HBase连接参数
    conf.set("hbase.zookeeper.quorum", "localhost")
    conf.set("hbase.zookeeper.property.clientPort", "2181")

    // 创建HBase连接
    val connection = ConnectionFactory.createConnection(conf)

    // 创建HBase表
    val tableName = "my_table"
    val table = connection.getTable(TableName.valueOf(tableName))

    // 创建HBase扫描对象
    val scan = new Scan()

    // 设置要读取的列族和列
    scan.addColumn(Bytes.toBytes("cf"), Bytes.toBytes("column1"))
    scan.addColumn(Bytes.toBytes("cf"), Bytes.toBytes("column2"))

    // 执行HBase扫描
    val scanner = table.getScanner(scan)

    // 遍历扫描结果并将结果转换为RDD
    val rdd = spark.sparkContext.parallelize(scanner.iterator().asScala.map(result => {
      val rowKey = Bytes.toString(result.getRow)
      val value1 = Bytes.toString(result.getValue(Bytes.toBytes("cf"), Bytes.toBytes("column1")))
      val value2 = Bytes.toString(result.getValue(Bytes.toBytes("cf"), Bytes.toBytes("column2")))
      (rowKey, value1, value2)
    }).toList)

    // 将RDD转换为DataFrame
    val df = spark.createDataFrame(rdd).toDF("rowKey", "value1", "value2")

    // 显示DataFrame内容
    df.show()

    // 关闭HBase连接
    scanner.close()
    table.close()
    connection.close()

    // 关闭SparkSession
    spark.stop()
  }
}