Toward fast theta‐join: A prefiltering and amalgamated partitioning approach

Abstract

As one of the most useful online processing techniques, the theta‐join operation has been utilized by many applications to fully excavate the relationships between data streams in various scenarios. As such, constant research efforts have been put to optimize its performance in the distributed environment, which is typically characterized by reducing the number of Cartesian products as much as possible. In this article, we design and implement a novel fast theta‐join algorithm, called Prefap, by developing two distinct techniques—prefiltering and amalgamated partitioning—based on the state‐of‐the‐art FastThetaJoin algorithm to optimize the efficiency of the theta‐join operation. Firstly, we develop a prefiltering strategy before data streams are partitioned to reduce the amount of data to be involved and benefit a more fine‐grained partitioning. Secondly, to avoid the data streams being partitioned in a coarse‐grained isolated manner and improve the quality of the partition‐level filtering, we introduce an amalgamated partitioning mechanism that can amalgamate the partitioning boundaries of two data streams to assist a fine‐grained partitioning. With the integration of these two techniques into the existing FastThetaJoin algorithm, we design and implement a new framework to achieve a decreased number of Cartesian products and a higher theta‐join efficiency. By comparing with existing algorithms, FastThetaJoin in particular, we evaluate the performance of Prefap on both synthetic and real data streams from two‐way to multiway theta‐join to demonstrate its superiority.

PECCO: A profit and cost‐oriented computation offloading scheme in edge‐cloud environment with improved Moth‐flame optimization

“…FIGURE 5 The percentage of objective value reduction achieved by the PECCO-MFI algorithm compared with other methods. Since the objective value reduction yielded by the PECCO-MFI is 149.7% and 112.6% compared with LARAC and GREEDY, respectively.…”

“…However, the fast growing of computation demands pose severe burden on cloud centers, [14][15][16] and tremendous amount of data generated 5,17 congests the network with limited bandwidth, 15,16,18 hence causing bottlenecks for the cloud-based computing paradigm. To relieve the pressure on cloud centers, the edge computing concept has emerged, 15,19,20 which allows computation to be performed at the edge network.…”

“…With the rapid prevalence of smart devices 1 such as mobile phone and Internet‐of‐Things (IoT) devices, 2–4 a vast amount of data has been generated 5,6 and the demand of computation resources has been boosted 7,8 . Due to the limited computation, storage, and energy capacity of these smart devices, 9 the powerful cloud computing has been leveraged to provide elastic on‐demand services to cope with limitations of smart devices 10,11 .…”

“…7,8 Due to the limited computation, storage, and energy capacity of these smart devices, 9 the powerful cloud computing has been leveraged to provide elastic on-demand services to cope with limitations of smart devices. 10,11 With the support of resource-rich cloud servers, processing and storage-intensive applications such as augmented reality (AR) 12 and virtual reality (VR) 13 become feasible.However, the fast growing of computation demands pose severe burden on cloud centers, [14][15][16] and tremendous amount of data generated 5,17 congests the network with limited bandwidth, 15,16,18 hence causing bottlenecks for the cloud-based computing paradigm. To relieve the pressure on cloud centers, the edge computing concept has emerged, 15,19,20 which allows computation to be performed at the edge network.…”

How does solid‐state drives cluster perform for distributed file systems: An empirical study

“…With rapid developments of technologies such as cloud computing 1 and big data analytics 2,3,4 , efficient and reliable storage technologies with high throughput and scalability become increasingly indispensable and thus are drawing great attention from both industry and academic communities. Among various storage mediums, the Solid-State Drive (SSD), by virtue of its high performance, has been identified as a mainstream substrate for storage systems.…”