使用 Apache Spark 查询多个 Hive 存储 [英] Querying on multiple Hive stores using Apache Spark

问题描述

我有一个 spark 应用程序，它将成功连接到 hive 并使用 spark 引擎查询 hive 表.

为了构建它，我只是将 hive-site.xml 添加到应用程序的类路径中，spark 将读取 hive-site.xml 以连接到它的 Metastore.这个方法是在spark的邮件列表中推荐的.

到目前为止一切顺利.现在我想连接到两个 hive 存储，我认为在我的类路径中添加另一个 hive-site.xml 不会有帮助.我参考了很多文章和 Spark 邮件列表，但找不到任何人这样做.

有人可以建议我如何实现这一目标吗?

谢谢.

引用的文档:

• 我还没有尝试过的东西

  环境 1 使用 HiveContext，环境 2 使用 SqlContext

  希望这会有用.

  I have a spark application which will successfully connect to hive and query on hive tables using spark engine.

  To build this, I just added hive-site.xml to classpath of the application and spark will read the hive-site.xml to connect to its metastore. This method was suggested in spark's mailing list.

  So far so good. Now I want to connect to two hive stores and I don't think adding another hive-site.xml to my classpath will be helpful. I referred quite a few articles and spark mailing lists but could not find anyone doing this.

  Can someone suggest how I can achieve this?

  Thanks.

  Docs referred:

  • Hive on Spark

  • Spak docs

  • HiveContext

  解决方案

  I think this is possible by making use of Spark SQL capability of connecting and reading data from remote databases using JDBC.

  After an exhaustive R & D, I was successfully able to connect to two different hive environments using JDBC and load the hive tables as DataFrames into Spark for further processing.

  Environment details

  hadoop-2.6.0

  apache-hive-2.0.0-bin

  spark-1.3.1-bin-hadoop2.6

  Code Sample HiveMultiEnvironment.scala

  import org.apache.spark.SparkConf
  import org.apache.spark.sql.SQLContext
  import org.apache.spark.SparkContext
  object HiveMultiEnvironment {
    def main(args: Array[String]) {
      var conf = new SparkConf().setAppName("JDBC").setMaster("local")
      var sc = new SparkContext(conf)
      var sqlContext = new SQLContext(sc)
  
      // load hive table (or) sub-query from Environment 1
  
      val jdbcDF1 = sqlContext.load("jdbc", Map(
        "url" -> "jdbc:hive2://<host1>:10000/<db>",
        "dbtable" -> "<db.tablename or subquery>",
        "driver" -> "org.apache.hive.jdbc.HiveDriver",
        "user" -> "<username>",
        "password" -> "<password>"))
      jdbcDF1.foreach { println }
        
      // load hive table (or) sub-query from Environment 2
  
      val jdbcDF2 = sqlContext.load("jdbc", Map(
        "url" -> "jdbc:hive2://<host2>:10000/<db>",
        "dbtable" -> "<db.tablename> or <subquery>",
        "driver" -> "org.apache.hive.jdbc.HiveDriver",
        "user" -> "<username>",
        "password" -> "<password>"))
      jdbcDF2.foreach { println }
    }
    // todo: business logic
  }
  

  Other parameters can also be set during load using SqlContext such as setting partitionColumn. Details found under 'JDBC To Other Databases' section in Spark reference doc: https://spark.apache.org/docs/1.3.0/sql-programming-guide.html

  Build path from Eclipse:

  What I Haven't Tried

  Use of HiveContext for Environment 1 and SqlContext for environment 2

  Hope this will be useful.

  这篇关于使用 Apache Spark 查询多个 Hive 存储的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！