PySpark isin function

Question

I am converting my legacy Python code to Spark using PySpark.

I would like to get a PySpark equivalent of:

usersofinterest = actdataall[actdataall['ORDValue'].isin(orddata['ORDER_ID'].unique())]['User ID']

Both, actdataall and orddata are Spark dataframes.

I don't want to use toPandas() function given the drawback associated with it.

Answer 1

• If both dataframes are big, you should consider using an inner join which will work as a filter:

  First let's create a dataframe containing the order IDs we want to keep:

  orderid_df = orddata.select(orddata.ORDER_ID.alias("ORDValue")).distinct()
  

  Now let's join it with our actdataall dataframe:

  usersofinterest = actdataall.join(orderid_df, "ORDValue", "inner").select('User ID').distinct()
  

• If your target list of order IDs is small then you can use the pyspark.sql isin function as mentioned in furianpandit's post, don't forget to broadcast your variable before using it (spark will copy the object to every node making their tasks a lot faster):

  orderid_list = orddata.select('ORDER_ID').distinct().rdd.flatMap(lambda x:x).collect()[0]
  sc.broadcast(orderid_list)