Dataflow GCS to BigQuery - How to output multiple

Currently I am using the gcs-text-to-bigquery google provided template and feeding in a transform function to transform my jsonl file. The jsonl is pretty nested and i wanted to be able to output multiple rows per one row of the newline delimited json by doing some transforms.

For example:

{'state': 'FL', 'metropolitan_counties':[{'name': 'miami dade', 'population':100000}, {'name': 'county2', 'population':100000}…], 'rural_counties':{'name': 'county1', 'population':100000}, {'name': 'county2', 'population':100000}….{}], 'total_state_pop':10000000,….}

There will obviously be more counties than 2 and each state will have one of these lines. The output my boss wants is:

When i do the gcs-to-bq text transform, i end up only getting one line per state (so I'll get miami dade county from FL, and then whatever the first county is in my transform for the next state). I read a little bit and i think this is because of the mapping in the template that expects one output per jsonline. It seems I can do a pardo(DoFn ?) not sure what that is, or there is a similar option with beam.Map in python. There is some business logic in the transforms (right now it's about 25 lines of code as the json has more columns than i showed but those are pretty simple).

Any suggestions on this? data is coming in tonight/tomorrow, and there will be hundreds of thousands of rows in a BQ table.

the template i am using is currently in java, but i can translate it to python pretty easily as there are a lot of examples online in python. i know python better and i think its easier given the different types (sometimes a field can be null) and it seems less daunting given the examples i saw look simpler, however, open to either

Solving that in Python is somewhat straightforward. Here's one possibility (not fully tested):

from __future__ import absolute_import                                                               

import ast                                                                      

import apache_beam as beam                                                      
from apache_beam.io import ReadFromText                                            
from apache_beam.io import WriteToText                                             

from apache_beam.options.pipeline_options import PipelineOptions                   

import os                                                                       
os.environ['GOOGLE_APPLICATION_CREDENTIALS'] = '/path/to/service_account.json'      

pipeline_args = [                                                                  
    '--job_name=test'                                                              
]                                                                                  

pipeline_options = PipelineOptions(pipeline_args)                                  


def jsonify(element):                                                              
    return ast.literal_eval(element)                                               


def unnest(element):                                                            
    state = element.get('state')                                                
    state_pop = element.get('total_state_pop')                                  
    if state is None or state_pop is None:                                                   
        return                                                                  
    for type_ in ['metropolitan_counties', 'rural_counties']:                   
        for e in element.get(type_, []):                                        
            name = e.get('name')                                                
            pop = e.get('population')                                           
            county_type = (                                                     
                'Metropolitan' if type_ == 'metropolitan_counties' else 'Rural' 
            )                                                                   
            if name is None or pop is None:                                     
                continue                                                        
            yield {                                                             
                'State': state,                                                 
                'County_Type': county_type,                                     
                'County_Name': name,                                            
                'County_Pop': pop,                                              
                'State_Pop': state_pop                                          
            }

with beam.Pipeline(options=pipeline_options) as p:                              
    lines = p | ReadFromText('gs://url to file')                                        

    schema = 'State:STRING,County_Type:STRING,County_Name:STRING,County_Pop:INTEGER,State_Pop:INTEGER'                                                                      

    data = (                                                                    
        lines                                                                   
        | 'Jsonify' >> beam.Map(jsonify)                                        
        | 'Unnest' >> beam.FlatMap(unnest)                                      
        | 'Write to BQ' >> beam.io.Write(beam.io.BigQuerySink(                  
            'project_id:dataset_id.table_name', schema=schema,                     
            create_disposition=beam.io.BigQueryDisposition.CREATE_IF_NEEDED,    
            write_disposition=beam.io.BigQueryDisposition.WRITE_APPEND)       
        )                                                                       
    )

This will only succeed if you are working with batch data. If you have streaming data then just change beam.io.Write(beam.io.BigquerySink(...)) to beam.io.WriteToBigQuery.