Firestore 数据库读取/写入非常慢

Question

OS: Mac OS Catalina v 10.15.1

Python version: Python 3.7.1

Firestore pip package version: google-cloud-firestore 1.6.1

I'm testing simple database reads and writes on a very simple Firestore database. I'm looking at a single collection with a single document containing 1 data item (a string); however, when I try to write (as shown below), the timer I have (also in the below code) shows that the first write takes over 30 seconds . This same behavior is present for reads.

However, this is only present for the first write/read in this python script. All subsequent writes/reads are timed at roughly 100ms (still slow for such a tiny database). I have not been able to find this issue replicated on the internet, and there is no mention of behavior like this in the Firestore Python SDK documentation. I am running the below code locally on my machine.

import firebase_admin
from firebase_admin import credentials
from firebase_admin import firestore
import datetime

cred = credentials.Certificate("./path/to/adminsdk.json")
firebase_admin.initialize_app(cred)
db = firestore.client()

start = datetime.datetime.now()

#the below write takes >30 seconds to execute
doc_ref = db.collection(u'test_collection').document(u'test_document')
doc_ref.set({u'test_field':'data'})

time_after_first = datetime.datetime.now()
print(time_after_first - start)

#The below read takes 80 ms to execute
doc_data = doc_ref.get()
print(doc_data.get('test_field'))

print(datetime.datetime.now()-time_after_first)

print("done")

I found a suggestion on another StackOverflow post suggesting to use on_snapshot instead of get ; however, the problem persists (the DocumentSnapshot is only received after roughly 30 seconds). Additionally, the problem is not unique to get , but for set , update , etc. as well.

Any tips would be appreciated!

Answer 1

You should think of your connection performance. I have implemented this code on my side and here are effects. It never reached 0.5s. Seems Firestore performance is very good. I hope this will help you solve it...