Firebase Cloud Functions 上的 Firestore 查询性能问题

Question

I am facing timeout issues on a firebase https function so I decided to optimize each line of code and realized that a single query is taking about 10 seconds to complete.

let querySnapshot = await admin.firestore()
    .collection("enrollment")
    .get()

The enrollment collection has about 23k documents, totaling approximately 6MB.

To my understanding, since the https function is running on a cloud function stateless server, it should not suffer from the query result size. Both Firestore and Cloud Functions are running on the same region (us-central). Yet 10 seconds is indeed a high interval of time for executing such a simple query that results in a small snapshot size.

An interesting fact is that later in the code I update those 23k documents back with a new field using Bulk Writter and it takes less than 3 seconds to run bulkWriter.commit().

Another fact is that the https function is not returning any of the query results to the client, so there shouldn't be any "downloading" time affecting the function performance.

Why on earth does it take 3x longer to read values from a collection than writing to it? I always thought Firestore architecture was meant for apps with high reading rates rather than writing.

Is there anything you would propose to optimize this?

Answer 1

When we perform the get(), a query is created to all document snapshots and the results are returned . These results are fetched sequentially within a single execution, ie the list is returned and parsed sequentially until all documents have been listed.

While the data may be small, are there any subcollections? This may add some additional latency as the API fetches and parses subcollections.

Updating the fields with a bulk writer update is over 3x the speed because the bulkwriter operation is performed in parallel and is queued based upon Promises. This allows many more operations per second.

The best way to optimize listing all documents is summarised in this link , and Google's recommendation follows the same guideline being to use an index for faster queries and to use multiple readers that fetch the documents in parallel.