This topic describes the recommended configurations for several typical scenarios, including online transaction processing (OLTP), complex OLTP, hybrid transactional/analytical processing (HTAP), online analytical processing (OLAP), and OBKV applications.
To ensure good performance of OceanBase Database in various business scenarios, OceanBase summarizes the recommended configurations for key parameters and variables based on extensive tuning experience from real-world scenarios. These recommended configurations are included in the installation package and can be viewed after deployment. Additionally, parameter templates are supported in OceanBase Cloud Platform (OCP) and OceanBase Deployer (obd). When creating clusters and tenants using OCP or obd, users can directly select the corresponding parameter templates to complete the settings.
Parameter configuration templates
After installing the OceanBase Database RPM package, you can view the parameter configuration templates for different business scenarios in the /home/admin/oceanbase/etc directory.
default_parameter.json: This file stores the recommended configurations for parameters.default_system_variable.json: This file stores the recommended configurations for system variables.
Scenario descriptions
Online transaction processing (OLTP)
Online transaction processing (OLTP) refers to real-time, interactive, and frequent operations such as adding, deleting, modifying, and querying data in a database. It is commonly used in industries such as banking, retail, aviation, and hospitality for daily business operations such as bill payments, inventory management, and order processing. OLTP scenarios typically require handling a large number of concurrent transactions and require the database to respond quickly and reliably to user requests.
For more information about the recommended configurations for this scenario, see Configuration best practices.
Complex online transaction processing (COMPLEX OLTP)
Complex online transaction processing (COMPLEX OLTP) is a scenario that involves handling large amounts of data and complex transactions. This scenario is commonly used in workloads such as banking and insurance systems. These workloads typically involve complex joins, complex correlated subqueries, batch jobs written in PL/SQL, long and large transactions. Sometimes, parallel execution strategies are also used to accelerate short-running queries.
For more information about the recommended configurations for this scenario, see Configuration best practices.
Hybrid transaction/analytical processing (HTAP)
Hybrid transaction/analytical processing (HTAP) refers to a database management system or architecture that supports both online transaction processing (OLTP) and online analytical processing (OLAP). HTAP scenarios are common in business environments that require real-time data analysis and querying, such as financial transactions, retail, and logistics. These industries require efficient transaction processing and real-time data analysis and querying capabilities to support business decisions and analytics. The advantage of HTAP architecture is that it reduces the costs of data replication and transformation, provides real-time data analysis capabilities, and accelerates the business decision-making process.
For more information about the recommended configurations for this scenario, see Configuration best practices.
Online analytical processing (OLAP)
Online analytical processing (OLAP) is a data processing technique used for multidimensional analysis of large datasets. It allows users to perform complex analyses from different perspectives, including dimensions, metrics, filters, and sorting. OLAP helps users identify and understand patterns, trends, and relationships in data, supporting decision-making and business intelligence. OLAP technology is commonly used in data warehouses and business intelligence systems.
For more information about the recommended configurations for this scenario, see Configuration best practices.
OBKV
OBKV is a multi-model key-value (KV) product of OceanBase Database, primarily used for providing low-cost, large-scale storage of structured and semi-structured data, as well as extremely high access performance under simple operation interfaces. In terms of implementation, OBKV bypasses the SQL layer and directly utilizes OceanBase's distributed storage to build various multi-model KV forms. Between the distributed storage and the multi-model forms, OBKV has a framework layer called TableAPI, which provides encapsulated storage and transaction call capabilities to the model layer.
For more information about the recommended configurations for this scenario, see Configuration best practices.
References
- For more information about parameters and system variables, see Overview of parameters and system variables.
- For more information about how to set parameters, see Set parameters.
- For more information about how to set variables, see Set variables.