本文介绍Spark如何访问EMR HBase集群数据。

Spark访问HBase示例

重要 计算集群需要和HBase集群处于一个安全组内，否则网络无法打通。在E-Mapreduce控制台创建计算集群时，请选择HBase集群所在的安全组。
  • Java代码
    JavaSparkContext jsc = new JavaSparkContext(sparkConf);

try {
  List<byte[]> list = new ArrayList<>();
  list.add(Bytes.toBytes("1"));
  ...
  list.add(Bytes.toBytes("5"));

  JavaRDD<byte[]> rdd = jsc.parallelize(list);
  Configuration conf = HBaseConfiguration.create();

  JavaHBaseContext hbaseContext = new JavaHBaseContext(jsc, conf);

  hbaseContext.foreachPartition(rdd,
      new VoidFunction<Tuple2<Iterator<byte[]>, Connection>>() {
   public void call(Tuple2<Iterator<byte[]>, Connection> t)
        throws Exception {
    Table table = t._2().getTable(TableName.valueOf(tableName));
    BufferedMutator mutator = t._2().getBufferedMutator(TableName.valueOf(tableName));
    while (t._1().hasNext()) {
      byte[] b = t._1().next();
      Result r = table.get(new Get(b));
      if (r.getExists()) {
       mutator.mutate(new Put(b));
      }
    }

    mutator.flush();
    mutator.close();
    table.close();
   }
  });
} finally {
  jsc.stop();
}
  • Scala代码
    val sc = new SparkContext("local", "test")
val config = new HBaseConfiguration()

...

val hbaseContext = new HBaseContext(sc, config)

rdd.hbaseForeachPartition(hbaseContext, (it, conn) => {
  val bufferedMutator = conn.getBufferedMutator(TableName.valueOf("t1"))
  it.foreach((putRecord) => {
   . val put = new Put(putRecord._1)
   . putRecord._2.foreach((putValue) => put.addColumn(putValue._1, putValue._2, putValue._3))
   . bufferedMutator.mutate(put)
 })
  bufferedMutator.flush()
  bufferedMutator.close()
})

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