Python Spark数据帧更新值

Python Spark数据帧更新值,python,apache-spark,dataframe,pyspark,spark-dataframe,Python,Apache Spark,Dataframe,Pyspark,Spark Dataframe,我有3个数据帧: 1. Item dataframe: +-------+---------+ |id_item|item_code| +-------+---------+ | 991| A0049| | 992| C1248| | 993| C0860| | 994| C0757| | 995| C0682| +-------+---------+ 及 及 现在,id\u usn在StructType中,我想用用户数据帧中的us

我有3个数据帧:

1. Item dataframe:

+-------+---------+
|id_item|item_code|
+-------+---------+
|    991|    A0049|
|    992|    C1248|
|    993|    C0860|
|    994|    C0757|
|    995|    C0682|
+-------+---------+

现在,id\u usn在StructType中,我想用用户数据帧中的usn替换摘要数据帧中的id\u usn

我用的是火花

请帮我解决这个问题

希望有帮助

 from pyspark.sql import functions as F

 sdf1 = summarydf.select('id_item','summary',F.explode('summary').alias('col_summary')).select('*',F.col('col_summary').id_usn.alias('id_usn'),F.col('col_summary').rating.alias('rating')).drop('col_summary')
 df  = sdf1.join(itemdf,'id_item').join(userdf,'id_usn').select('item_code',F.struct('usn','rating').alias('tmpcol')).groupby('item_code').agg(F.collect_list('tmpcol').alias('summary'))
+---------+--------------------+
|item_code|             summary|
+---------+--------------------+
|    C1248|[[39063291,0.0010...|
|    A0049|[[39063291,0.5799...|
+---------+--------------------+

您是否尝试使用
join
后跟
select
?我担心这个问题太简单了,不可能成立,并试图找到值得穿上它的东西。我可以试试,但我的问题是替换id_usn,因为它在struct@JacekLaskowski:你对这个问题有什么想法吗?你可以分解阵列,将结构域作为单独的列并将它们连接起来。@Suresh:您能在答案中编写代码吗
3. Summary dataframe

+-------+--------------------+
|id_item|     summary        |
+-------+--------------------+
|    991|[[417567,0.579901...|
|    992|[[417567,0.001029...|
|    443|[[417585,0.219624...|
+-------+--------------------+

and schema of this dataFrame:

root
 |-- id_item: integer (nullable = true)
 |-- summary: array (nullable = true)
 |    |-- element: struct (containsNull = true)
 |    |    |-- id_usn: long (nullable = true)
 |    |    |-- rating: double (nullable = true)
 from pyspark.sql import functions as F

 sdf1 = summarydf.select('id_item','summary',F.explode('summary').alias('col_summary')).select('*',F.col('col_summary').id_usn.alias('id_usn'),F.col('col_summary').rating.alias('rating')).drop('col_summary')
 df  = sdf1.join(itemdf,'id_item').join(userdf,'id_usn').select('item_code',F.struct('usn','rating').alias('tmpcol')).groupby('item_code').agg(F.collect_list('tmpcol').alias('summary'))
+---------+--------------------+
|item_code|             summary|
+---------+--------------------+
|    C1248|[[39063291,0.0010...|
|    A0049|[[39063291,0.5799...|
+---------+--------------------+