YMatrix
Quick Start
Simulate Time Series Scenarios
Standard Cluster Deployment
Data Modeling
Connecting to The database
Data Writing
Data Migration
Data Query
Scene Application Examples
Federal Query
Maintenance and Monitoring
Global Maintenance
Partition Maintenance
Backup and Restore
Cluster Expansion
Monitoring
Performance Tuning
Troubleshooting
Reference Guide
Tool Guide
Data Type
Storage Engine
Execution Engine
Configuration Parameters
SQL Reference
FAQ
Through this document, we will introduce the database technology architecture adopted by YMatrix at the physical level: MPP (Massive Parallel Processing) architecture.
MPP refers to the fact that in a database non-shared (Shared Nothing) cluster, each node (Node) has an independent disk storage system and memory system. The business data is divided into each node according to the database model and application characteristics. Each data node (Segment Node) is connected to each other through a proprietary network or a commercial general network, and computes with each other to provide database services. Non-shared database clusters have advantages such as scalability, high availability, high performance, and high cost performance.
Simply put, the MPP architecture distributes tasks to multiple servers and nodes in parallel. After the calculation of each node is completed, the results are summarized together to obtain the final result.
From the perspective of data technology architecture, distributed database architectures are divided into fully shared (Shared Everything), Shared Nothing and Shared Disk:
_1692009080.png)
The characteristics of the MPP architecture are as follows: