How to obtain the output of the pipeline and perform read&write to Cloud Firestore - google-cloud-firestore

Question

I am using Apache Beam to take log from Pub/Sub which contains information of pageview traffic. Each page contains unique ID and when one log of pageview traffic come from the Pub/Sub, Cloud Dataflow will collect them in a constant windowed manner and count them. At the end of combiner, we will get something like this:
12345, 2
12456, 1
15213, 1
...
As I know, ParDo is a Beam transform for generic parallel processing. After combine, I wish to implement a transform that write query to Cloud Firestore to get the existing pageview ID, take the current view count, perform addition on it and perform write operating to update the view count one by one from the combined output as shown above. Any suggestion?
Below is my code so far for the UpdateViewCount. When I get the query, it seems impossible to have a for loop to get the query (it will be only one row of query since the pageview is unique tho)
class UpdateIntoFireStore(beam.DoFn):
def process(self, element):
listingid, count = element
doc_ref = db.collection('listings').where('listingid', u'==', '12345')
try:
docs = doc_ref.get()
for doc in docs:
print doc
except NotFound:
print(u'No such document!')

Answer 1

I solved it. There is no need to put a loop to retrieve the data and I should retrieve the particular ID with document name.
doc_ref = db.collection(u'listings').document(listingid)
try:
doc = doc_ref.get()
doc_dict = doc.to_dict()
self.cur_count = doc_dict[u'count']
doc_ref.update({
u'count': self.cur_count + count
})
except NotFound:
doc_ref.set({'count': count})