# Parallel Index-based Stream Join on a Multicore CPU

## TL;DR

This paper presents a novel parallel index-based stream join method optimized for multicore CPUs, significantly improving throughput in streaming query processing by using a new index structure and concurrency algorithms.

## Contribution

Introduces the Partitioned In-memory Merge-Tree and a parallel join algorithm to enhance dynamic data indexing and stream processing on multicore processors.

## Key findings

- Achieves up to 5.5x higher throughput than single-threaded methods
- Effectively handles highly dynamic streaming data
- Demonstrates scalability on an octa-core processor

## Abstract

There is increasing interest in using multicore processors to accelerate stream processing. For example, indexing sliding window content to enhance the performance of streaming queries is greatly improved by utilizing the computational capabilities of a multicore processor. However, designing an effective concurrency control mechanism that addresses the problem of concurrent indexing in highly dynamic settings remains a challenge. In this paper, we introduce an index data structure, called the Partitioned In-memory Merge-Tree, to address the challenges that arise when indexing highly dynamic data, which are common in streaming settings. To complement the index, we design an algorithm to realize a parallel index-based stream join that exploits the computational power of multicore processors. Our experiments using an octa-core processor show that our parallel stream join achieves up to 5.5 times higher throughput than a single-threaded approach.