1. Flashing Up the Storage Layer I. Koltsidas, S. D. Viglas (U of Edinburgh), VLDB 2008 Shimin Chen Big Data Reading Group

2. Motivation: Flash Disks: 64GB – 128GB SSDs available as of Feb’08 Intel announced 80GB SSDs Flash disks vs. magnetic disks Same I/O interface: logical 512B sectors No mechanical latency, I/O asymmetry, erase-before-write: Random reads 10X faster than magnetic disks Random writes 10X slower than magnetic disks, esp MLC Exploit flash disks for storage?

3. Architecture Flash disk as a cache for magnetic disk? Suboptimal for database workloads because of write inefficiency Flash disk and magnetic disk on the same level (This Paper)

4. Problem Statement Page migrations (Storage Manager) Workload prediction Self-tuning Page replacement (Buffer Manager)

5. Outline Introduction Page placement Page replacement Experimental study Conclusion

6. Model Random read/write costs of flash and magnetic disks Page migration decision is always made when a page is in buffer pool Migration cost == write cost The ideas are not new. The novel thing here is that logical I/Os are served by buffer pool. Only part of them are seen physically.

7. r, w: the cost of the current disk; r’, w’: the cost of the other disk pg.C: a counter per page – the accumulated cost difference

8. Conservativeness Migration operation only after the cost of migrating to and back Only physical operations on pages 3-competitive to optimal offline algorithm

10. Properties Not conservative on migrations Based on logical operations

11. Hybrid Algorithm Idea: Consider both physical and logical operations More weight on physical ones If a file has n pages, and b pages are cached in the buffer pool, then Prob_miss = 1 – b/n

13. Outline Introduction Page placement Page replacement Experimental study Conclusion

14. Eviction Cost Evicting a page: Dirty page incurs write cost Fetching a page back in the future incurs read cost Cost:

15. Buffer Pool Organization Sorted on timestamp Sorted on cost of eviction LRU

18. Impact of λ As λ increases: Time segment decreases Cost segment increases Disk pages increases, flash pages decreases Flash pages are evicted first, typically only found in time segment Let Hm be the increase of disk hit rate, Mf be the increase of flash miss rate So we want

19. Outline Introduction Page placement Page replacement Experimental study Conclusion

20. Experimental Setup Implementation: Buffer manager, storage manager, B+trees for storing data Machine: 2.26GHz Pentium4, 1.5GB RAM Debian linux, kernel 2.6.21 Two magnetic disks (300GB Maxtor DiamondMax) 1 SSD (Samsung MLC 32GB) Data is stored on 1 disk + 1 SSD (both raw devices)

21. Experimental Setup Cont’d Capacity of either disk is enough to hold all data Metadata for files, pages, page mappings, and free space are not modeled B+tree is 140MB large, scattered across 1.4GB address space Buffer pool is 20MB large

22. Raw Performance: 1 million 4KB random accesses

23. Impact of Using Both Disks Conservative + LRU Query mix: read-only, write-only, read/write Each set of queries executed 15 times

24. Read-Only

25. Write-Only

26. Mixed

27. Page Placement Algorithms Infrequently changing workload

28. Frequently changing workload

29. Buffer Pool Replacement

30. Conclusion Flash disk vs. magnetic disk Page migration and placement Page replacement Can be applied to databases and file systems (?)

31. Outline Introduction Page placement Page replacement Experimental study Conclusion