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February 8th, 2018, 12:22 PM   #1
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How derive formula for database disk cache?

We have database which is partially in memory. If DB were all in memory then we assume costs=0 - we calculate only disk->memory costs.
Computer must not whole memory allocate for database. Let is 1 GB in memory (or 12 GB), whole database have for example 2 GB or 200 GB or 5 TB.
One record has 100-160 bytes.
Random time reading from disk=14 ms, average speed 120 MB/s.
If we read record which is not in memory, we must read whole block. (Blocks have size for example 32 KB, 512 KB, 10 MB or even 100 MB – this size is also parameter of formula).
Fortunately, we have possibility of many records in one query: 50 or 1000 – there records can be grouped and reading one block give us many records.
How is best strategy?
How is formula of number accessed to disk and number bytes reading from disk, depend on: size in memory, size whole, size one record,size block and number records in one query?
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February 8th, 2018, 01:08 PM   #2
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This analysis sounds like it is the better part of a senior project.

Perhaps you can give us some more details about how you happened to come by this problem. Some of us are happy to help students, to a point, but disinclined to assist professionals.
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February 8th, 2018, 01:33 PM   #3
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M: memory size
D: database size
r: record size
B: block size
m : number records in one query
Assume nontrivial D>M
Let come next record. Probability that is not in memory is (D-M)/D
then we read one block B bytes. Removing from memory B/r records.
If 10% were cached is 90% chance that we must read one block to read record??
Records can be random, but sometimes we want read succeeding records.
For example: we read index, index can be large like table and can be not fit whole in memory.
This query cached succeeded records, but if we want add random records with unique keys, block must be small as possible?
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