Spark:在安全集群中读取HBase

时间:2016-10-10 14:44:56

标签: apache-spark hbase kerberos

我有一个简单的任务:我想在Kerberos安全集群中读取HBase数据。 到目前为止,我尝试了两种方法:

  • sc.newAPIHadoopRDD():此处我不知道如何处理kerberos身份验证
  • 从HBase API创建一个HBase连接:这里我真的不知道如何将结果转换为RDD

此外,似乎有一些HBase-Spark连接器。但不知何故,我并没有真正找到它们作为Maven工件和/或它们需要一个固定的结果结构(但我只需要拥有HBase Result对象,因为我的数据中的列不是固定的)。 / p>

你有任何示例或教程或......? 我感谢任何帮助和提示。

提前致谢!

1 个答案:

答案 0 :(得分:1)

我假设你使用的是spark + scala + Hbase

import org.apache.spark._
import org.apache.spark.rdd.NewHadoopRDD
import org.apache.hadoop.hbase.{HBaseConfiguration, HTableDescriptor}
import org.apache.hadoop.hbase.client.HBaseAdmin
import org.apache.hadoop.hbase.mapreduce.TableInputFormat
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.hbase.HColumnDescriptor
import org.apache.hadoop.hbase.util.Bytes
import org.apache.hadoop.hbase.client.Put;
import org.apache.hadoop.hbase.client.HTable;


object SparkWithMyTable {
  def main(args: Array[String]) {
    //Initiate spark context with spark master URL. You can modify the URL per your environment. 
    val sc = new SparkContext("spark://ip:port", "MyTableTest")

    val tableName = "myTable" 

val conf = HBaseConfiguration.create()
conf.set("hbase.zookeeper.quorum", "list of cluster ip's")
conf.set("hbase.zookeeper"+ ".property.clientPort","2181");
conf.set("hbase.master", "masterIP:60000");
conf.set("hadoop.security.authentication", "kerberos");
conf.set("hbase.security.authentication", "kerberos");



UserGroupInformation.setConfiguration(conf);
UserGroupInformation.loginUserFromKeytab("user@---", keyTabPath);

    // Add local HBase conf
   // conf.addResource(new Path("file://hbase/hbase-0.94.17/conf/hbase-site.xml"))
    conf.set(TableInputFormat.INPUT_TABLE, tableName)

    // create my table with column family
    val admin = new HBaseAdmin(conf)
    if(!admin.isTableAvailable(tableName)) {
      print("Creating MyTable")
      val tableDesc = new HTableDescriptor(tableName)
      tableDesc.addFamily(new HColumnDescriptor("cf1".getBytes()));
      admin.createTable(tableDesc)
    }else{
      print("Table already exists!!")
      val columnDesc = new HColumnDescriptor("cf1");
      admin.disableTable(Bytes.toBytes(tableName));
      admin.addColumn(tableName, columnDesc);
      admin.enableTable(Bytes.toBytes(tableName));
    }

    //first put data into table
    val myTable = new HTable(conf, tableName);
    for (i <- 0 to 5) {
      var p = new Put();
      p = new Put(new String("row" + i).getBytes());
      p.add("cf1".getBytes(), "column-1".getBytes(), new String(
                        "value " + i).getBytes());
      myTable.put(p);
    }
    myTable.flushCommits();

    //how to create  rdd
    val hBaseRDD = sc.newAPIHadoopRDD(conf, classOf[TableInputFormat], 
      classOf[org.apache.hadoop.hbase.io.ImmutableBytesWritable],
      classOf[org.apache.hadoop.hbase.client.Result])

    //get the row count
    val count = hBaseRDD.count()
    print("HBase RDD count:"+count)
    System.exit(0)
  }
}

Maven神器

<dependency>
  <groupId>it.nerdammer.bigdata</groupId>
  <artifactId>spark-hbase-connector_2.10</artifactId>
  <version>1.0.3</version> // Version can be changed as per your Spark version, I am using Spark 1.6.x
</dependency>

还可以查看

相关问题