Pyspark - 如何根据数据框 2 中的列值在数据框 1 中插入记录

Question

我需要根据另一个 table 中的记录数将记录插入 table1，比如说 table2，使用 pyspark 的 spark.sql()。目前可以通过加入获得一条记录，但我需要根据第二个 table.

将尽可能多的记录插入 table1

我在这里提供示例数据框：

df1= sqlContext.createDataFrame([("xxx1","81A01","TERR NAME 01"),("xxx1","81A01","TERR NAME 02"), ("xxx1","81A01","TERR NAME 03")], ["zip_code","zone_code","territory_name"])
df2= sqlContext.createDataFrame([("xxx1","81A01","","NY")], ["zip_code","zone_code","territory_name","state"])

df1.show()
+--------+--------------+--------------+
|zip_code|zone_code     |territory_name|
+--------+--------------+--------------+
|    xxx1|         81A01|  TERR NAME 01|
|    xxx1|         81A01|  TERR NAME 02|
|    xxx1|         81A01|  TERR NAME 03|
+---------------------------------------

# Print out information about this data
df2.show()
+--------+--------------+--------------+-----+
|zip_code|zone_code     |territory_name|state|
+--------+--------------+--------------+-----+     
|    xxx1|         81A01|  null        |   NY|
+---------------------------------------------

在上面的示例中，我需要根据 zip_code 将 df2 与 df1 连接起来，并在 df1 中获得与 territory_names 一样多的记录。

df2 中的预期结果是：

+--------+--------------+--------------+-----+
|zip_code|zone_code     |territory_name|state|
+--------+--------------+--------------+-----+     
|    xxx1|         81A01|  TERR NAME 01|   NY|
|    xxx1|         81A01|  TERR NAME 02|   NY|
|    xxx1|         81A01|  TERR NAME 03|   NY|
+---------------------------------------------

需要帮助，目前可以通过加入获得一条记录

Spark.sql query sample for getting one record:
    df1.createOrReplaceTempView('df1')
    df2.createOrReplaceTempView('df2')
    spark.sql("select a.zip_code,a.zone_code,b.territory_name,a.state from df1 a 
    left join df2 b on a.zip_code = b.zip_code where a.territory_name is null").createOrReplaceTempView('df2')

谢谢

Answer 1

想提供代码片段，也许对某些人有用。

df1= sqlContext.createDataFrame([("xxx1","81A01","TERR NAME 01"),("xxx1","81A01","TERR NAME 02"), ("xxx1","81A01","TERR NAME 03")], ["zip_code","zone_code","territory_name"])
df2= sqlContext.createDataFrame([("xxx1","","","NY"), ("xxx1","","TERR NAME 99","NY")], ["zip_code","zone_code","territory_name","state"])

df1.createOrReplaceTempView('df1')
df2.createOrReplaceTempView('df2')

spark.sql(“select * from df1”)
+--------+---------+--------------+ 
|zip_code|zone_code|territory_name| 
+--------+---------+--------------+ 
| xxx1   | 81A01   | TERR NAME 01 | 
| xxx1   | 81A01   | TERR NAME 02 | 
| xxx1   | 81A01   | TERR NAME 03 | 
+--------+---------+--------------+ 

spark.sql(“select * from df2”)
+--------+---------+--------------+-----+ 
|zip_code|zone_code|territory_name|state| 
+--------+---------+--------------+-----+ 
| xxx1   |         |              | NY  | 
| xxx1   |         | TERR NAME 99 | NY  | 
+--------+---------+--------------+-----+

spark.sql("""select a.zip_code, b.zone_code, b.territory_name, a.state from df2 a 
            left join df1 b 
            on a.zip_code = b.zip_code 
            where a.territory_name = ''
            UNION
            select a.zip_code, b.zone_code, a.territory_name, a.state from df2 a 
            left join df1 b 
            on a.zip_code = b.zip_code 
            where a.territory_name != ''
            """).createOrReplaceTempView('df3')


spark.sql(“select * from df3”)
+--------+---------+--------------+-----+ 
|zip_code|zone_code|territory_name|state| 
+--------+---------+--------------+-----+ 
| xxx1   | 81A01   | TERR NAME 03 | NY  | 
| xxx1   | 81A01   | TERR NAME 99 | NY  |  
| xxx1   | 81A01   | TERR NAME 01 | NY  | 
| xxx1   | 81A01   | TERR NAME 02 | NY  | 
+--------+---------+--------------+-----+

感谢帮助过的人

Pyspark - 如何根据数据框 2 中的列值在数据框 1 中插入记录

Pyspark - How to insert records in dataframe 1, based on a column value in dataframe2

python

pyspark-sql

pyspark-dataframes