1. Putting things in order
Sorting
Putting things in order
This is the big picture version, it includes sort_i and sort_e and would be suitable for data structures.
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2. Sorting is Important One of the largest consumers of resources
Estimated that in the 1960s 1/3 of all CPU power was used on sorts
One sort was recorded to take months
Sorts are expensive
Still consume cycles or accesses
Too many things do not work without them
Entire grad level classes on just sorting
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3. Definitions Internal sorting External sorting Merge
All the data is in memory – most often in an array
No I/Os are required
External sorting
The data will not fit in memory
Usually the I/O costs exceed the CPU costs
Merge
Start with two (or more) sorted files
Produce one sorted result
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4. Keys Often more than one Primary key Secondary key Most important
The DB notion is different than the sort one
Secondary key
Discriminate between two records where primary key is the same
There may be multiple secondaries
Ordered by importance
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5. The Sort Merge Generalized program that will sort any file
Standard program on mainframes, but less common on other platforms
User specifies the sort and file characteristics
The program then creates the sorted file
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6. Sort Characteristics Primary and secondary keys Exits Position Length
Type
Ascending or descending
Exits
Points in the algorithm where a user written program could be invoked
Usually to filter/reformat the data
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7. The Sort Merge Did as much as it could using internal sorting
Usually had to resort to file merging for files that were too large to fit in memory
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8. Internal Sorting Data fits in memory Typically an array or table
Examined first Sort_I.ppt
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9. External Sorting Usual situation with a DBMS
Occurs elsewhere as well
Too many pages for a file to fit in memory
The internal sorts mostly require random access to individual records
While we have random access to pages
Want to minimize the number of pages
sort_e.ppt
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10. Parallelism With multiple CPUs some gain in sorting may occur
Each CPU may do part of a sort in parallel
Only the final merge needs a single CPU to properly handle
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11. Using a BTree
Suppose that the file in question has a BTree index on the field in question
Should that be used instead of sorting?
The answer depends on whether this is a clustered or unclustered index
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12. Well? Clustered Unclustered Traverse root to initial value
Ride the leaves as long as needed
This eliminates the need for a sort, the leaves are already sorted
Unclustered
We will have to use index for each record
Generally a sequential scan that is sorted will be faster for normal index sizes
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