[英]Advanced join two dataframe spark scala
我必須加入兩個數據框。
示例:Dataframe1看起來像這樣
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
結果數據框我想得到這樣的結果
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
實現這種加入的最佳方法是什么?
我已經更新了下面的代碼
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
您只需要拆分這些值並通過展開它來生成多行,然后與另一個數據框合並。
您可以參考此鏈接, 如何將以管道分隔的列拆分為多行?
我為連接使用了spark sql,這是代碼的一部分;
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)
我使用spark scala數據框來實現所需的輸出。
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
需求輸出
+--------+--------+--------+
|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|
+--------+--------+--------+
根據您的要求重命名列。
這里是運行代碼的屏幕截圖
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