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Query Processing and Optimizing on SSDs. Flash Group Qingling Cao qingling1220@sina.com. Outline. Introduction. Page Layout on SSD. Scan Approaches. Join Algorithms. Conclusion. Outline. Introduction. Page Layout on SSD. Scan Approaches. Join Algorithms. Conclusion.
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Query Processing and Optimizing on SSDs Flash Group Qingling Cao qingling1220@sina.com
Outline Introduction Page Layout on SSD Scan Approaches Join Algorithms Conclusion
Outline Introduction Page Layout on SSD Scan Approaches Join Algorithms Conclusion
Introduction • Page layout and data structure • Leverage fast random read to speed up selection、projectionand join operation • Database query processing engines traditionally emphasize on sequential I/O
Outline Introduction Page Layout on SSD Scan Approaches Join Algorithms Conclusion
Page Layout on SSD Row Layout slot Column Layout -Attributes of one column stored in continuous pages
Page Layout on SSD PAX Layout PAX Layout is efficient for SSD but not for disk. Why?
Page Layout on SSD • Disk, the sequential read speed is 100MB/s. A skip takes 3-4ms. So a mini-page should be 300-400KB. Then full page size will be MB. • IDE flash drive, the sequential read bandwidth is 28MB/s. Seek time is 0.25ms, so mini-page should be 7KB. Then full page size can be 32-128KB.
Page Layout on SSD • Disk, the sequential read speed is 100MB/s. A skip takes 3-4ms. So a mini-page should be 300-400KB. Then full page size will be MB. • IDE flash drive, the sequential read bandwidth is 28MB/s. Seek time is 0.25ms, so mini-page should be 7KB. Then full page size can be 32-128KB.
Page Layout on SSD • Disk, the sequential read speed is 100MB/s. A skip takes 3-4ms. So a mini-page should be 300-400KB. Then full page size will be MB. • IDE flash drive, the sequential read bandwidth is 28MB/s. Seek time is 0.25ms, so mini-page should be 7KB. Then full page size can be 32-128KB.
Page Layout on SSD • Disk, the sequential read speed is 100MB/s. A skip takes 3-4ms. So a mini-page should be 300-400KB. Then full page size will be MB. • IDE flash drive, the sequential read bandwidth is 28MB/s. Seek time is 0.25ms, so mini-page should be 7KB. Then full page size can be 32-128KB.
Page Layout on SSD • Disk, the sequential read speed is 100MB/s. A skip takes 3-4ms. So a mini-page should be 300-400KB. Then full page size will be MB. • IDE flash drive, the sequential read bandwidth is 28MB/s. Seek time is 0.25ms, so mini-page should be 7KB. Then full page size can be 32-128KB.
Page Layout on SSD • Disk, the sequential read speed is 100MB/s. A skip takes 3-4ms. So a mini-page should be 300-400KB. Then full page size will be MB. • IDE flash drive, the sequential read bandwidth is 28MB/s. Seek time is 0.25ms, so mini-page should be 7KB. Then full page size can be 32-128KB.
Page Layout on SSD • Disk, the sequential read speed is 100MB/s. A skip takes 3-4ms. So a mini-page should be 300-400KB. Then full page size will be MB. • IDE flash drive, the sequential read bandwidth is 28MB/s. Seek time is 0.25ms, so mini-page should be 7KB. Then full page size can be 32-128KB.
Page Layout on SSD • Disk, the sequential read speed is 100MB/s. A skip takes 3-4ms. So a mini-page should be 300-400KB. Then full page size will be MB. • IDE flash drive, the sequential read bandwidth is 28MB/s. Seek time is 0.25ms, so mini-page should be 7KB. Then full page size can be 32-128KB.
Page Layout on SSD • Disk, the sequential read speed is 100MB/s. A skip takes 3-4ms. So a mini-page should be 300-400KB. Then full page size will be MB. • IDE flash drive, the sequential read bandwidth is 28MB/s. Seek time is 0.25ms, so mini-page should be 7KB. Then full page size can be 32-128KB.
Outline Introduction Page Layout on SSD Scan Approaches Join Algorithms Conclusion
Scan Approaches • NSMScan – Always read the whole relation. • FlashScan – Read only the related columns. e.g. select S from R where J
Scan Approaches • FlashScanOPT(U) – read only the mini-pages consist the tuples needed. e.g. select S from R where J • FlashScanOPT(S) – Attributes are sorted, so the mini-pages are read at most once.
Scan Approaches Table: 70m tuples, 11columns, 10GB System: Intel Core 2 Duo at 2.33GHz, 4GB of RAM Mtron 32GB SSD
Outline Introduction Page Layout on SSD Scan Approaches Join Algorithms Conclusion
Join Algorithms – past lessons Block Nested Loops Join Sort-Merge Join Grace Hash Join Hybrid Hash Join
Join Algorithms – past lessons Customer: 450w tuples, 730MB Order: 4500w tuples, 5GB HDD: 5400RPM, 320GB SSD: OCZ Core series 60GB SATA II ☆Algorithms that stress random reads , and avoid random writes as much as possible see bigger improvements on flash
Join Algorithms – RARE-join Select Name, Team from Player, Game where Player.Team=Game.Geam J1 J2 Player Game
Join Algorithms – RARE-join Join Index: Join Result: Total I/O cost: |J1|+ σ1|V1|+|J2|+ σ2|V2|
Join Algorithms – FlashJoin id1,id2,id3 hashG, id1,id2 hashK, id3 id1,id2 hashA, id1 hashD, id2 Read(A) Read(D)
Join Algorithms – Fetch Kernel Join Index: Join Index: Each page is read no more than once.
Join Algorithms – Fetch Kernel Join Index: Join Index:
Join Algorithms – FlashJoin R: 70m tuples, 10GB S: 7m tuples, 1GB System: Intel Core 2 Duo at 2.33GHz, 4GB of RAM Mtron 32GB SSD
Join Algorithms – DigestJoin • Row-based • {JI, idx, idy} • Minimize the IO to fetch the join result
Join Algorithms – Page Fetching(1) • Sort-merge join • Join results are clustered • Memory is enough • Fetch the pages of the tuples as soon as they are produced
Join Algorithms – Page Fetching(2) ft1={A:1, A:2, B:1, B:2} ft2={C:1, C:2, D:1, D:2} jct1={x1,x2,x3,x4} jct2={y1,y2,y3,y4} Fetching instruction table Join candidate table Join Index: (x1,A:1,C:1) (x2,B:1,D:1) (x3,A:2,C:2) (x4,B:2,D:2) ft1={A:1, B:1, A:2, B:2} ft2={C:1, D:1, C:2, D:2}
Join Algorithms – Page Fetching(3) • Join Graph G=(V1 ∪ V2, E) E V1 V2 • Segment e.g. {1, a, b, c}, {a, 1, 2}
Join Algorithms – Page Fetching(3) • Required storage size(RSS) • Required cache size(RCS) • <join_atrr,tid1,tid2>
Outline Introduction Page Layout on SSD Scan Approaches Join Algorithms Conclusion
Conclusion PAX: • Scan algorithm has little room for improvement. • RARE-Join、FlashJoin. • No write. • Join index will be sorted many times. • The size of minipage is not fixed.
Conclusion Row: • DigestJoin. • IO is much more than other join algorithms. Column: • None • Storage is more flexible. • Utilize the technology of tuple reconstruction.