How does Reliance Nitro’s tree-based architecture improve performance?
The most common metadata architecture is linear allocation. In this method, the file system uses a linear array to store metadata information. This makes the file system simple and works fairly well for a system with a small number of files. The limitations of linear allocation start to show significant impact as the number of files in a system grows. Accessing large number of files through linear traversal of a folder takes a long time, leading to a serious degradation in performance. Tree-based allocations are a faster way to organize and find files, based on grouping information into addressable chunks, and assigning keys that direct the system where to find them this needs to be better formatted: Tree Depth 512 1024 2048 Level 1 15 31 63 Level 2 615 2,604 10,647 Level 3 25,215 218,736 1,799,343 Level 4 1,033,815 18,373,824 304,088,967 For 512 bytes block size: * On a linear file system (like TFAT), nodes traversed to access file #25,215 = 25,215/8 = 3,151 * On a tree-based file sys
Related Questions
- In the blog article you said the new architecture would provide good performance benefit but eclipse feels quite sluggish?
- What does it deliver to enterprise in terms of performance, architecture, ease of use and administration?
- How does Reliance Nitro’s tree-based architecture improve performance so dramatically?
