Optimising python-gremlin for fastApi
PS: Please give me some rope here as I am new to gremlin-python!
I have a fastAPI which is serving some Rest API calls based on the data that I am fetching from a Neptune instance. I am using gremlin-python library to make the queries to graph instance.
Some points to note:
1. I'm using Uvicorn workers with fastapi. You can consider a single worker for any stats I share.
2. There may be multiple graph calls in a single API request.
3. Currently getting around 8-10 RPS.
Now having worked on a lot of fastApi services, I know that this RPS is way too low. I have done lots of optimisations in the past by moving towards asyncio "native" libraries like AioHttp, AioRedis, etc. Achieving a considerable 90-100 RPS in some instances on each worker.
I have scourged through the gremlin-python source code, and am confused about a couple of things.
1. Even though the library is creating a separate loop, while doing any I/O, the coroutines are being used in a blocking manner by calling
2. I have tried exploring other libraries like
3. Is the main event being blocked when I am running the queries, For example
If the main fastapi event loop is indeed being blocked, what can I do to unblock the same when making the gremlin queries??
Any suggestions to increase the throughput on each worker are highly appreciated!!
I have a fastAPI which is serving some Rest API calls based on the data that I am fetching from a Neptune instance. I am using gremlin-python library to make the queries to graph instance.
Some points to note:
1. I'm using Uvicorn workers with fastapi. You can consider a single worker for any stats I share.
2. There may be multiple graph calls in a single API request.
3. Currently getting around 8-10 RPS.
Now having worked on a lot of fastApi services, I know that this RPS is way too low. I have done lots of optimisations in the past by moving towards asyncio "native" libraries like AioHttp, AioRedis, etc. Achieving a considerable 90-100 RPS in some instances on each worker.
I have scourged through the gremlin-python source code, and am confused about a couple of things.
1. Even though the library is creating a separate loop, while doing any I/O, the coroutines are being used in a blocking manner by calling
loop.run_until_complete2. I have tried exploring other libraries like
aiogremlinaiogoblin3. Is the main event being blocked when I am running the queries, For example
If the main fastapi event loop is indeed being blocked, what can I do to unblock the same when making the gremlin queries??
Any suggestions to increase the throughput on each worker are highly appreciated!!
