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Secondary Storage

Secondary Storage. Rough Speed Differentials nanoseconds: retrieve data in main memory microseconds: retrieve from under a read head milliseconds: retrieve from elsewhere on disk Approximate Disk Speeds seek (head move): 8 milliseconds rotational latency (spin under): 4 milliseconds

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Secondary Storage

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  1. Secondary Storage • Rough Speed Differentials • nanoseconds: retrieve data in main memory • microseconds: retrieve from under a read head • milliseconds: retrieve from elsewhere on disk • Approximate Disk Speeds • seek (head move): 8 milliseconds • rotational latency (spin under): 4 milliseconds • block transfer: 68 microseconds (negligible) • total: 12.068 – about 12 milliseconds • Implications • cluster data on cylinders • make good use of caches

  2. Sequential Files • Operations • Add: write over a deleted record or after last record • Delete: mark deleted • Access: read until record found (half the file, on average) • Sorted (doesn’t help much without an index) • Access: • sequential (can be contiguous or non-contiguous) • binary search is usually worse • Add: can be expensive to maintain sort order • Delete: mark deleted

  3. Indexes Primary (Key) Index Guest(GuestNr Name StreetNr City) 1 101 Smith 12 Maple Boston 102 Carter 10 Main Hartford . . . 2 123 Jones 20 Main Boston . . . 144 Hansen 12 Oak Boston 25 763 Black 15 Elm Hartford 764 Barnes 45 Oak Boston Block#/Offset ---------------- 101 1,0 102 1,1 . . . 123 2,0 . . . Block# ----------- 101 1 123 2 . . . 763 25 Secondary (Key) Index <Smith, 12 Maple, Boston> 1 <Carter, 10 Main, Hartford> 1 . . . <Jones, 20 Main, Boston> 2 . . . Secondary (Nonkey) Index Boston 1, 2, . . ., 25 Hartford 1, . . ., 25 Dense & Sparse Indexes

  4. Indexed Sequential File 1. Sorted on primary key 2. Sparse index 3. Overflow buckets Index ----------- 101 1 123 2 . . . 763 25 Guest(GuestNr Name StreetNr City) 1 101 Smith 12 Maple Boston 102 Carter 10 Main Hartford . . . 2 123 Jones 20 Main Boston . . . 144 Hansen 12 Oak Boston 25 763 Black 15 Elm Hartford 764 Barnes 45 Oak Boston Operations: Access Delete Insert 146 Green 10 Main Albany 120 Adams 15 Oak Boston

  5. Variable-Length Records GuestNr RoomNr ArrivalDate NrDays --------------------------------------------------------- 101 1 10 May 2 2 20 May 1 3 15 May 2 102 3 10 May 5 . . . Three Implementations: 1. Reserve enough space for maximum. 2. Chain each nested record. 3. Reserve space for the expected number and chain the rest.

  6. Hashing • Static Hashing • similar to in-memory hashing (block/offset addresses) • records in (logically) contiguous blocks (degrades w/ chaining) • Open Hashing • hash table of pointers to buckets • buckets: chained blocks of dense-index value-pointer pairs • operations: retrieve, add, delete h(101) 101 Smith 12 Maple Boston 101 . . .

  7. Indexing Verses Hashing Which is better for: • Store and retrieve on key • Search on non-key • Range search • Search on multiple attributes For highly dynamic updates, indexed-sequential files degenerate quickly—need B+-tree indexes.

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