pipelining

What problem does it solve?

This Skill solves the problem of high latency and low throughput in networked systems by enabling pipelining, which allows multiple requests to be sent over a single connection without waiting for each response.

Core Features & Use Cases

• Reduce Latency: By eliminating the need to wait for each response, pipelining can significantly reduce the overall time taken for multiple requests.
• Increase Throughput: Pipelining allows more work to be done over a single connection, increasing the number of requests that can be processed in a given time.
• Use Case: Imagine you have a web application that sends and receives many small HTTP requests. Pipelining can reduce the total time required for these requests by sending them in a continuous stream without waiting for responses.

Quick Start

To implement pipelining in a Redis client using redis-py, use the pipelined function as follows:

python
import redis
r = redis.Redis(host="cache.internal", port=6379)
pipeline = r.pipeline(transaction=False)
for i in range(10):
    pipeline.get(f"key{i}")
pipeline.execute()