Database Index Merging for Time Series Replication Load
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Solution Overview
Problem
In time series databases, data replication leads to performance deterioration due to concentrated load on specific nodes, resulting in reduced data processing speed.
Innovation Solution
The method involves storing time series data and indices in multiple regions and files, merging these index regions into a single merged index file to reduce I/O overheads, and then replicating the combined data regions and index region to other nodes, thereby distributing the load and speeding up the replication process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data replication is performed in a time series database, then data redundancy and reliability are improved, but load concentration on specific nodes occurs resulting in performance deterioration
Solution Approach 1:
The patent segments the database into multiple nodes (master node and data nodes) and further segments data storage into multiple table regions (first table region with data regions and index regions, second table region for replication). This segmentation distributes the load across multiple nodes and regions, preventing any single node from becoming a bottleneck while maintaining data redundancy through replication across the segmented structure.
2Productivity
If multiple index regions are maintained separately for each data region, then data organization and query efficiency are improved, but I/O overhead increases during replication operations
Solution Approach 1:
The patent merges multiple index regions from the first table region into a single merged index region stored in the second table region. This merging reduces the number of separate I/O operations required during replication, as the system can now replicate a single consolidated index region rather than multiple separate index files, thereby reducing I/O overhead while maintaining efficient query capabilities through the organized index structure.
3Device complexity
If a single node performs all reception, replication, and storage operations, then system complexity is reduced, but load concentration occurs causing performance deterioration
Solution Approach 1:
The patent segments the database system into multiple nodes with specific roles: a master node that receives data and a plurality of data nodes that store replicated data. This segmentation distributes the computational and I/O load across multiple nodes, preventing any single node from becoming overloaded. The system maintains manageable complexity through clear role differentiation while achieving improved performance through parallel processing and load distribution.
4Reliability
If data is replicated to multiple nodes, then system reliability and fault tolerance are improved, but replication time and resource consumption increase
Solution Approach 1:
The patent merges multiple index regions into a single consolidated index region before replication. This merging reduces the total volume of data that needs to be replicated and reduces the number of separate replication operations required. As a result, replication time is reduced while still achieving the desired fault tolerance and reliability through replication to multiple data nodes, as the merged index region can be replicated as a single unit to multiple targets simultaneously.
Data Source
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AI summary
Disclosed herein are a method and an apparatus for replicating data. A master node or a data node stores data and indices in a table region including a plurality of data regions and a plurality of index regions, merges the plurality of index regions with one another to be one index region, and then replicates a table region including the plurality of data regions and the one index region to other nodes.