高级连接两个数据框Spark Scala

Question

我必须加入两个数据框。

示例：Dataframe1看起来像这样

df1_col1      df1_col2
   a            ex1
   b            ex4
   c            ex2
   d            ex6
   e            ex3

Dataframe2

df2_col1      df2_col2
   1           a,b,c
   2           d,c,e
   3           a,e,c

结果数据框我想得到这样的结果

res_col1      res_col2       res_col3
    a           ex1             1
    a           ex1             3
    b           ex4             1
    c           ex2             1
    c           ex2             2
    c           ex2             3
    d           ex6             2
    e           ex3             2
    e           ex3             3

实现这种加入的最佳方法是什么？

Answer 1

我已经更新了下面的代码

val df1 = sc.parallelize(Seq(("a","ex1"),("b","ex4"),("c","ex2"),("d","ex6"),("e","ex3")))
val df2 = sc.parallelize(Seq(List(("1","a,b,c"),("2","d,c,e")))).toDF
df2.withColumn("df2_col2_explode", explode(split($"_2", ","))).select($"_1".as("df2_col1"),$"df2_col2_explode").join(df1.select($"_1".as("df1_col1"),$"_2".as("df1_col2")), $"df1_col1"===$"df2_col2_explode","inner").show

您只需要拆分这些值并通过展开它来生成多行，然后与另一个数据框合并。

您可以参考此链接， 如何将以管道分隔的列拆分为多行？

Answer 2

我为连接使用了spark sql，这是代码的一部分；

df1.createOrReplaceTempView("temp_v_df1")
df2.createOrReplaceTempView("temp_v_df2")
val df_result = spark.sql("""select 
                    |   b.df1_col1 as res_col1, 
                    |   b.df1_col2 as res_col2, 
                    |   a.df2_col1 as res_col3  
                    |   from (select df2_col1, exp_col 
                    |         from temp_v_df2 
                    |        lateral view explode(split(df2_col2,",")) dummy as exp_col) a
                    |   join temp_v_df1 b on a.exp_col = b.df1_col1""".stripMargin)

Answer 3

我使用spark scala数据框来实现所需的输出。

val df1 = sc.parallelize(Seq(("a","ex1"),("b","ex4"),("c","ex2"),("d","ex6"),("e","ex3"))).toDF("df1_col1","df1_col2") 

val df2 = sc.parallelize(Seq((1,("a,b,c")),(2,("d,c,e")),(3,("a,e,c")))).toDF("df2_col1","df2_col2") 

df2.withColumn("_tmp", explode(split($"df2_col2", "\\,"))).as("temp").join (df1,$"temp._tmp"===df1("df1_col1"),"inner").drop("_tmp","df2_col2").show

需求输出

+--------+--------+--------+
|df2_col1|df1_col1|df1_col2|
+--------+--------+--------+
|       2|       e|     ex3|
|       3|       e|     ex3|
|       2|       d|     ex6|
|       1|       c|     ex2|
|       2|       c|     ex2|
|       3|       c|     ex2|
|       1|       b|     ex4|
|       1|       a|     ex1|
|       3|       a|     ex1|
+--------+--------+--------+

根据您的要求重命名列。

这里是运行代码的屏幕截图

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