Regression Analysis for profiling L-Store metadata throughput handling
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Objective
As part of some of the initial testing with L-Store these tests are attempting to create a base reference model for meta data handling with L-Store. Specifically we are interested in seeing that as we increase from very small file sizes to large file sizes whether the latency profile is a linear fit or a non-linear fit.
Parameters
1. File Size: 1KB, 500KB, 1MB, 50 MB, 100MB, 150MB, 200MB, 250MB
2. Number of Files: 30 files
3. Number of threads: 10 threads
Results
- Number of Threads: 10
- Block Size : 1MB (Each Slice is 1MB)
- Number of Files : 30
- Current Status: In progress
- Time of Completion:
| Type of Test | Number of files | Average File Size (MB) | Average Latency (sec) | Median Latency (sec) | Maximum Latency (sec) | Std Deviation on Latency |
|---|---|---|---|---|---|---|
| profile_upload | 30 | 0.001 | 2.8 | 2.7 | 11.0 | 0.63 |
| profile_upload | 30 | 0.5 | 3.0 | 3.0 | 10.0 | 0.45 |
| profile_upload | 30 | 1.0 | 3.5 | 3.4 | 4.5 | 0.22 |
| profile_upload | 30 | 50.0 | 8.4 | 8.3 | 10.0 | 0.49 |
| profile_upload | 30 | 100.0 | 13.0 | 13.0 | 16.0 | 0.8 |
| profile_upload | 30 | 150.0 | 18.0 | 18.0 | 19.0 | 0.87 |
| profile_upload | 30 | 200.0 | 23.0 | 23.0 | 27.0 | 1.3 |
| profile_upload | 30 | 500.0 | 54.0 | 53.0 | 78.0 | 4.8 |
| profile_upload | 30 | 250.0 | 27.0 | 27.0 | 47.0 | 1.2 |