Leader Election

Overview

This section describes the Space Where GigaSpaces data is stored. It is the logical cache that holds data objects in memory and might also hold them in layered in tiering. Data is hosted from multiple SoRs, consolidated as a unified data model.'s leader election mechanism, which is based on the CAP theorem. It also explains how to configure and optimize it.

CAP Theorem

The CAP theorem, also known as Brewer's theorem, states that it is impossible for a distributed computer system to simultaneously provide all three of the following guarantees:

• Consistency (all nodes see the same data at the same time),  This is the default path.

• Availability (node failures do not prevent survivors from continuing to operate). This is only applicable for XAP GigaSpaces eXtreme Application Platform. Provides a powerful solution for data processing, launching, and running digital services.

• Partition Tolerance (the system continues to operate despite arbitrary message loss)

Gigaspaces provides two available implementations to support the approach that is best suited to your environment and business needs.

Consistency based implementation is based on Apache Zookeeper Apache Zookeeper. An open-source server for highly reliable distributed coordination of cloud applications. It provides a centralized service for providing configuration information, naming, synchronization and group services over large clusters in distributed systems. The goal is to make these systems easier to manage with improved, more reliable propagation of changes., whereas availability based is based on the native Lookup Service.

GigaSpaces recommends that you use partition tolerance plus consistency. However, if your system does not include at least three machines, you can manually choose to work with partition tolerance plus availability.  

• Consistency biased - this implementation is based on Apache Zookeeper.

• Availability biased - this implementation is based on the native Lookup Service.