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Slow engine creation - only when using FastAPI

Aperta
#422 3 commenti 0 reazioni 0 assegnatari Vedi su GitHub

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Valutazione

Difficoltà
4/5
Tempo stimato
3-5 giorni
Idoneità per principianti
25/100
Tipo di issue
Bug
Chiarezza
Abbastanza chiara
Stato di attività
Ferma
Stack tecnologico
fastapi, python, sql, sqlalchemy
Ambito
api, databases

Direzione di ricerca

Inizia con la riproduzione FastAPI in main.py e test_route.py, quindi confronta il relativo percorso create_engine con l’esempio di connessione autonomo di databricks.sql. Esegui il profiling dell’importazione e dell’esecuzione di databricks/sql/thrift_api/TCLIService/ttypes.py con le versioni fissate in requirements.txt. Il lavoro sarà completato quando sarà stata stabilita la causa del ritardo esclusivo di FastAPI e sarà stato dimostrato un rimedio supportato senza modificare manualmente il file generato.

Scritto dal modello di indicizzazione a partire dal testo della issue.

Descrizione

Hello,

I am currently working on a FastAPI application which calls Databricks using databricks-sql-connector, however the code appears to slow down massively on the engine creation stage.

I've narrowed the issue down to .venv\Lib\site-packages\databricks\sql\thrift_api\TCLIService\ttypes.py, where when running in debug mode the script is loaded incredibly slowly (around 5-10 minutes). However when the exact same code is run outside of a FastAPI function (ie, in a standalone script, notebook, etc) it runs almost instantly and the engine is created in under 1 second.

The details of my test application are:

main.py:

from fastapi import FastAPI
from fastapi.responses import RedirectResponse
import uvicorn
from routes import test_route


app = FastAPI(
     title="TestAPI",
     version="1.0",
     description="Test API",
     )

@app.get("/", include_in_schema=False)
async def docs_redirect():
     return RedirectResponse(url='/docs')

app.include_router(test_route.router)

if __name__ == '__main__':
     uvicorn.run('main:app', host='0.0.0.0', port=8000)

test_route.py:

import fastapi
from fastapi import APIRouter

from sqlalchemy import create_engine
from sqlalchemy import text

router = APIRouter(tags=["Test"])

@router.post("/test_route", description="Test")
async def test():
    import time

    print("Connecting to engine....")
    startT = time.time()
    engine = create_engine(
        url = f"databricks://token:<<TOKEN>>@<<HOST>>?http_path=/sql/1.0/warehouses/<<WAREHOUSE>>&catalog=<<CATALOG>>&schema=<<SCHEMA>>"
    )
    print("Engine Connected!")
    print(f"Time taken: {time.time() - startT} seconds.")

    with engine.connect() as connection:
        result = connection.execute(text("SELECT * from range(10)"))
        for row in result:
            print(row)

    print(f"Execution time: {time.time() - startT} seconds.")
    pass

    return "Ok."

requirements.txt:

fastapi==0.111.1
uvicorn==0.30.3
databricks-sql-connector[SQLAlchemy]==3.3.0

The same issue occurs when using:

from databricks import sql

connection = sql.connect(
                        server_hostname = <HOST>,
                        http_path = <HTTP>
                        access_token = <TOKEN>)

cursor = connection.cursor()

cursor.execute("SELECT * from range(10)")
print(cursor.fetchall())

cursor.close()
connection.close()

but given it all goes to create_engine under the hood I was trying to simplify my test case.

As mentioned, the call stack points to .venv\Lib\site-packages\databricks\sql\thrift_api\TCLIService\ttypes.py taking all of this extra time. This can be fixed through editing ttypes.py directly and removing all rows which begin None, #. However this directly violates the warning given at the top of ttypes.py about not editing. Removing these rows reduces the file from ~100,000 lines to ~10,000, and completely solves the time delay issue when using FastAPI.

So my main questions are:

  • Why does this delay in engine creation only occur in a FastAPI app (is it something to do with it being asynchronous?).
  • How can this delay be remedied?
  • Can ttypes.py be safely edited to remove all "None" rows or is this not a viable solution?

Thanks!

Lingua principale
Python
Stelle
233
Fork
152
Merge medio
21h 5m
PR unite (30g)
10

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