Load distribution strategy of decentralized databases

Abstract

Load management in databases typically involves segmentation strategies that determine the distribution and placement of information within data storage systems. This article explores a critical aspect of data segmentation and the challenges associated with selecting the right strategy. Some of the discussed strategies, such as range-based strategy and hashing strategy, come with their limitations and risks that can complicate scalability and data migration operations. The article also highlights issues related to choosing a specific data segmentation pattern in databases, including data movement complexity, uneven load distribution, transactional problems, and data integrity preservation. Choosing the right segmentation strategy is crucial to ensure the efficiency and productivity of a data storage system, and it should be a thoughtful choice tailored to the specific requirements of the system. The article discusses important data segmentation strategies in storage systems, which play a key role in the distribution and management of large datasets. The authors explore three main strategies: the search strategy, the range strategy, and the hashing strategy. Each of these strategies has its unique advantages and characteristics. The search strategy provides maximum control over data placement and the ability to use virtual segments for data balancing. This strategy is particularly useful for multi-user applications but may introduce additional overhead during segment retrieval. The range strategy groups related data into one segment and works well with queries for ranges of values. However, it can lead to uneven load distribution. The hashing strategy helps evenly distribute the load and avoid highly active segments but may introduce additional computational overhead when calculating the hash. The article also discusses data scaling and relocation operations for each of these strategies. For example, the search strategy allows for data scaling and relocation at the user level without system downtime. This article helps readers better understand the differences between data segmentation strategies and choose the most suitable one for their specific use case.