import asyncio
import aioboto3
import json
import time
import uuid
import random

# Configuration
QUEUE_URL = '<https://sqs.ap-northeast-2.amazonaws.com/200148130345/user-event-queue>'
REGION_NAME = 'ap-northeast-2'
MESSAGES_PER_BATCH = 500
DELAY_SECONDS = 1  # 두 번째 전송 전 대기 시간

def generate_fake_event():
    return {
        "id": str(uuid.uuid4()),
        "timestamp": time.time(),
        "action": random.choice(["create", "update", "delete"]),
        "user": f"user{random.randint(1, 100)}"
    }

async def send_message(sqs, message):
    await sqs.send_message(
        QueueUrl=QUEUE_URL,
        MessageBody=json.dumps(message)
    )

async def send_batch(batch_number, session):
    async with session.client("sqs", region_name=REGION_NAME) as sqs:
        tasks = [
            send_message(sqs, generate_fake_event())
            for _ in range(MESSAGES_PER_BATCH)
        ]
        await asyncio.gather(*tasks)
        print(f"[Batch {batch_number}] Sent {MESSAGES_PER_BATCH} messages.")

async def main():
    session = aioboto3.Session()
    await send_batch(1, session)
    await asyncio.sleep(DELAY_SECONDS)
    await send_batch(2, session)

if __name__ == "__main__":
    asyncio.run(main())

pip install aioboto3

python3 spike_producer.py

• Query

• concurrent 44개를 가지고 for문 내에서 1000개의 데이터를 놓치지 않고 sqs에서 받아와서 처리 했다는 걸 확인할 수 있다.