将Spark RDD保存到Hive表 [英] Save Spark RDD to Hive Table
本文介绍了将Spark RDD保存到Hive表的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!
问题描述
$ b
线程main中的异常java.lang.NullPointerException
val products = sc.parallelize(evaluateProducts.toList);
//这里的产品是RDD [Product]
val productdf = hiveContext.createDataFrame(products,classOf [Product])
我正在使用Spark 1.5版本。如果你的产品是一个类(不是案例类),我建议你先将RDD转换为RDD [元组]创建DataFrame:
import org.apache.spark.sql.hive.HiveContext
val hiveContext = new HiveContext(sc)
import hiveContext.implicits._
$ b $ val productDF = products
.map({p:Product =>(p.getVal1,p.getVal2 ,...)})
.toDF(col1,col2,...)
使用这种方法,您将在DataFrame中将产品属性设置为列。然后,您可以创建一个临时表:
productDF.registerTempTable(table_name)
或物理表:
productDF.write.saveAsTable(table_name)
In spark I want to save RDD objects to hive table. I am trying to use createDataFrame but that is throwing
Exception in thread "main" java.lang.NullPointerException
val products=sc.parallelize(evaluatedProducts.toList);
//here products are RDD[Product]
val productdf = hiveContext.createDataFrame(products, classOf[Product])
I am using Spark 1.5 version.
解决方案
If your Product is a class (not a case class), I suggest you transform your rdd to RDD[Tuple] before creating the DataFrame:
import org.apache.spark.sql.hive.HiveContext
val hiveContext = new HiveContext(sc)
import hiveContext.implicits._
val productDF = products
.map({p: Product => (p.getVal1, p.getVal2, ...)})
.toDF("col1", "col2", ...)
With this approach, you will have the Product attributes as columns in the DataFrame.
Then you can create a temp table with:
productDF.registerTempTable("table_name")
or a physical table with:
productDF.write.saveAsTable("table_name")
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