如何使用Scala在Spark中联接两个Hbase表

Question

我需要使用scala将HBase中的两个表连接起来。 这些表是使用sqoop从Oracle导入的，可在Hue数据浏览器中查询

使用Spark 1.5，Scala 2.10.4。

我正在从这里使用HBase数据连接器： https : //github.com/nerdammer/spark-hbase-connector

import it.nerdammer.spark.hbase._
import org.apache.hadoop.hbase.client.{ HBaseAdmin, Result }
import org.apache.hadoop.hbase.{ HBaseConfiguration, HTableDescriptor }
import org.apache.hadoop.hbase.mapreduce.TableInputFormat
import org.apache.hadoop.hbase.io.ImmutableBytesWritable
import org.apache.spark._
import it.nerdammer.spark.hbase.conversion.{ FieldReader, FieldWriter }
import org.apache.hadoop.hbase.util.Bytes

case class Artist(id: String,
                 name: String,
                 age: Int);

case class Cd(id: String,
              artistId: String,
              title: String,
              year: Int);

case class ArtistCd(id: String,
                    name: String,
                    title: String,
                    year: Int);

implicit def artistReader: FieldReader[Artist] = new FieldReader[Artist] {

    override def map(data: HBaseData): Artist = Artist(

        id = Bytes.toString(data.head.get),
        name = Bytes.toString(data.drop(1).head.get),
        age = Bytes.toInt(data.drop(2).head.get));

    override def columns = Seq("NAME", "AGE");

};

implicit def cdReader: FieldReader[Cd] = new FieldReader[Cd] {

    override def map(data: HBaseData): Cd = Cd(

        id = Bytes.toString(data.head.get),
        artistId = Bytes.toString(data.drop(1).head.get),
        title = Bytes.toString(data.drop(2).head.get),
        year = Bytes.toInt(data.drop(3).head.get));

    override def columns = Seq("ARTIST_ID", "TITLE", "YEAR");

};

implicit def artistCdWriter: FieldWriter[ArtistCd] = new FieldWriter[ArtistCd] {
    override def map(data: ArtistCd): HBaseData =
        Seq(
            Some(Bytes.toBytes(data.id)),
            Some(Bytes.toBytes(data.name)),
            Some(Bytes.toBytes(data.title)),
            Some(Bytes.toBytes(data.year)));

    override def columns = Seq("NAME", "TITLE", "YEAR");
};

val conf = new SparkConf().setAppName("HBase Join").setMaster("spark://localhost:7337")
val sc = new SparkContext(conf)

val artistRDD = sc.hbaseTable[Artist]("ARTISTS").inColumnFamily("cf")
val cdRDD = sc.hbaseTable[Cd]("CDS").inColumnFamily("cf")

val artistById = artistRDD.keyBy(f => f.id)
val cdById = cdRDD.keyBy(f => f.artistId)

val artistcd = artistById.join(cdById)

val artistCdRDD = artistcd.map(f => new ArtistCd(f._2._1.id, f._2._2.title, f._2._1.name, f._2._2.year))
artistCdRDD.toHBaseTable("ARTIST_CD").inColumnFamily("cf").save()
System.exit(1)

运行此命令时，出现以下异常

16/01/22 14:27:04 WARN TaskSetManager: Lost task 0.0 in stage 5.0 (TID 3, localhost): org.apache.hadoop.hbase.client.RetriesExhaustedWithDetailsException: Failed 2068 actions: ARTIST_CD: 2068 times,
        at org.apache.hadoop.hbase.client.AsyncProcess$BatchErrors.makeException(AsyncProcess.java:227)
        at org.apache.hadoop.hbase.client.AsyncProcess$BatchErrors.access$1700(AsyncProcess.java:207)
        at org.apache.hadoop.hbase.client.AsyncProcess.waitForAllPreviousOpsAndReset(AsyncProcess.java:1663)
        at org.apache.hadoop.hbase.client.BufferedMutatorImpl.backgroundFlushCommits(BufferedMutatorImpl.java:208)
        at org.apache.hadoop.hbase.client.BufferedMutatorImpl.doMutate(BufferedMutatorImpl.java:141)
        at org.apache.hadoop.hbase.client.BufferedMutatorImpl.mutate(BufferedMutatorImpl.java:98)
        at org.apache.hadoop.hbase.mapreduce.TableOutputFormat$TableRecordWriter.write(TableOutputFormat.java:129)
        at org.apache.hadoop.hbase.mapreduce.TableOutputFormat$TableRecordWriter.write(TableOutputFormat.java:85)
        at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsNewAPIHadoopDataset$1$$anonfun$12$$anonfun$apply$4.apply$mcV$sp(PairRDDFunctions.scala:1036)
        at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsNewAPIHadoopDataset$1$$anonfun$12$$anonfun$apply$4.apply(PairRDDFunctions.scala:1034)
        at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsNewAPIHadoopDataset$1$$anonfun$12$$anonfun$apply$4.apply(PairRDDFunctions.scala:1034)
        at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1206)
        at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsNewAPIHadoopDataset$1$$anonfun$12.apply(PairRDDFunctions.scala:1042)
        at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsNewAPIHadoopDataset$1$$anonfun$12.apply(PairRDDFunctions.scala:1014)
        at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
        at org.apache.spark.scheduler.Task.run(Task.scala:88)
        at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
        at java.lang.Thread.run(Thread.java:745)

如果有人对此有任何经验，我将非常感谢您的帮助

我在这里看到了两个解决方案， 如何在Hbase中联接两个表以及如何在hbase中联接表 ，不幸的是，这两个方案都不适合我

Answer 1

弄清楚了-首先，新表必须已经存在。 我以为save（）命令可以创建它，但是没有。 另外，新表必须具有要保存到的列族-这里是“ cf”

Answer 2

例子1）

spark-shell --driver-class-path= {put apache lib path}:  {put hbase lib path}

spark-shell --driver-class-path=/usr/local/Cellar/apache-spark/2.4.0/libexec/jars/* :/usr/local/Cellar/hbase-1.4.9/lib/*

示例2）

spark-shell --driver-class-path=$SPARK_HOME:$(hbase classpath)