Python dictionary key value into dataframe where clause in Pyspark

Question

How can I pass a Python dictionary key value into dataframe where clause in Pyspark ...

Python dictionary as below ...

column_dict= { 'email': 'customer_email_addr' ,
               'addr_bill': 'crq_st_addr' ,
               'addr_ship': 'ship_to_addr' ,
               'zip_bill': 'crq_zip_cd' ,
               'zip_ship':  'ship_to_zip' ,
               'phone_bill': 'crq_cm_phone' ,
               'phone_ship' : 'ship_to_phone'}

I've a spark dataframe with around 3 billion records. Dataframe as follows ...

source_sql= ("select cust_id, customer_email_addr, crq_st_addr, ship_to_addr,
 crq_zip_cd,ship_to_zip,crq_cm_phone,ship_to_phone from odl.cust_master  where
 trans_dt >= '{}' and trans_dt <= '{}' ").format('2017-11-01','2018-10-31')

cust_id_m = hiveCtx.sql(source_sql)
cust_id.cache()

My intention to find out distinct valid customer's for Email, Addr, Zip and Phone and run in loop for above dictionary keys. For this when I test spark shell for one key value as below ...

>>> cust_id_risk_m=cust_id_m.selectExpr("cust_id").where( 
("cust_id_m.'{}'").format(column_dict['email'])  != ''  ).distinct()

I'm getting error ... Need experts assistance in resolving this.

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/opt/mapr/spark/spark-2.1.0/python/pyspark/sql/dataframe.py", line 1026, in filter
    raise TypeError("condition should be string or Column")
TypeError: condition should be string or Column

Vikrant Singh Rana · Accepted Answer · 2018-12-14 14:51:23Z

Can you try using get method on your dictionary? I have tested this with below dataframe as:

df =spark.sql("select emp_id, emp_name, emp_city,emp_salary from udb.emp_table  where emp_joining_date >= '{}' ".format(2018-12-05))

>>> df.show(truncate=False)
+------+----------------------+--------+----------+
|emp_id|emp_name              |emp_city|emp_salary|
+------+----------------------+--------+----------+
|1     |VIKRANT SINGH RANA    |NOIDA   |10000     |
|3     |GOVIND NIMBHAL        |DWARKA  |92000     |
|2     |RAGHVENDRA KUMAR GUPTA|GURGAON |50000     |
+------+----------------------+--------+----------+

thedict={"CITY":"NOIDA"}

>>> newdf = df.selectExpr("emp_id").where("emp_city ='{}'".format(thedict.get('CITY'))).distinct()
>>> newdf.show();
+------+
|emp_id|
+------+
|     1|
+------+

or you can share your sample data for your dataframe?

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