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OPTIMIZE DATABASE QUERIES

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arnold 7490

The document discusses different types of indexes that can be used to organize data files on external storage. It compares file organizations like heap files, sorted files, and various indexing techniques including B-tree and hash indexes. It outlines the basic structure of indexes like B-trees, including leaf pages containing data entries and non-leaf pages containing index entries. The document also discusses concepts like clustered vs unclustered indexes, primary vs secondary indexes, and different alternatives for storing data entries in indexes.

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[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Data on External Storage ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Alternative File Organizations ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Index Classification ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Clustered vs. Unclustered Index ,[object Object],[object Object],[object Object],Index entries Data entries direct search for (Index File) (Data file) Data Records data entries Data entries Data Records CLUSTERED UNCLUSTERED
Indexes ,[object Object],[object Object],[object Object],[object Object],[object Object]
B+ Tree Indexes ,[object Object],[object Object],P 0 K 1 P 1 K 2 P 2 K m P m index entry Non-leaf Pages Pages (Sorted by search key) Leaf
Example B+ Tree ,[object Object],[object Object],[object Object],2* 3* Root 17 30 14* 16* 33* 34* 38* 39* 13 5 7* 5* 8* 22* 24* 27 27* 29* Entries <= 17 Entries > 17 Note how data entries in leaf level are sorted
Hash-Based Indexes ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Alternatives for Data Entry k* in Index ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Alternatives for Data Entries (Contd.) ,[object Object],[object Object],[object Object],[object Object]
Alternatives for Data Entries (Contd.) ,[object Object],[object Object],[object Object]
Cost Model for Our Analysis ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Comparing File Organizations ,[object Object],[object Object],[object Object],[object Object],[object Object]
Operations to Compare ,[object Object],[object Object],[object Object],[object Object],[object Object]
Assumptions in Our Analysis ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Assumptions (contd.) ,[object Object],[object Object],[object Object],[object Object],[object Object]
Cost of Operations
Understanding the Workload ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Choice of Indexes ,[object Object],[object Object],[object Object],[object Object]
Choice of Indexes (Contd.) ,[object Object],[object Object],[object Object],[object Object],[object Object]
Index Selection Guidelines ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Examples of Clustered Indexes ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],SELECT E.dno FROM Emp E WHERE E.age>40 SELECT E.dno, COUNT (*) FROM Emp E WHERE E.age>10 GROUP BY E.dno SELECT E.dno FROM Emp E WHERE E.hobby=Stamps
Indexes with Composite Search Keys ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],sue 13 75 bob cal joe 12 10 20 80 11 12 name age sal <sal, age> <age, sal> <age> <sal> 12,20 12,10 11,80 13,75 20,12 10,12 75,13 80,11 11 12 12 13 10 20 75 80 Data records sorted by name Data entries in index sorted by <sal,age> Data entries sorted by <sal> Examples of composite key indexes using lexicographic order.
Composite Search Keys ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Index-Only Plans ,[object Object],SELECT E.dno, COUNT (*) FROM Emp E GROUP BY E.dno SELECT E.dno, MIN (E.sal) FROM Emp E GROUP BY E.dno SELECT AVG (E.sal) FROM Emp E WHERE E.age=25 AND E.sal BETWEEN 3000 AND 5000 < E.dno > < E.dno,E.sal > Tree index! < E. age,E.sal > or < E.sal, E.age > Tree index!
Summary ,[object Object],[object Object],[object Object],[object Object],[object Object]
Summary (Contd.) ,[object Object],[object Object],[object Object],[object Object]
Introduction ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Range Searches ,[object Object],[object Object],[object Object],[object Object],Page 1 Page 2 Page N Page 3 Data File k2 kN k1 Index File
ISAM ,[object Object],P 0 K 1 P 1 K 2 P 2 K m P m index entry Non-leaf Pages Pages Primary pages Leaf Overflow page
Comments on ISAM ,[object Object],[object Object],[object Object],[object Object],[object Object],Data Pages Index Pages Overflow pages
Example ISAM Tree ,[object Object],10* 15* 20* 27* 33* 37* 40* 46* 51* 55* 63* 97* 20 33 51 63 40 Root
After Inserting 23*, 48*, 41*, 42* ... 10* 15* 20* 27* 33* 37* 40* 46* 51* 55* 63* 97* 20 33 51 63 40 Root 23* 48* 41* 42* Overflow Pages Leaf Index Pages Pages Primary
... Then Deleting 42*, 51*, 97* 10* 15* 20* 27* 33* 37* 40* 46* 55* 63* 20 33 51 63 40 Root 23* 48* 41*
B+ Tree: Most Widely Used Index ,[object Object],[object Object],[object Object],Index Entries Data Entries (&quot;Sequence set&quot;) (Direct search)
Example B+ Tree ,[object Object],[object Object],Root 17 24 30 2* 3* 5* 7* 14* 16* 19* 20* 22* 24* 27* 29* 33* 34* 38* 39* 13
B+ Trees in Practice ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Inserting a Data Entry into a B+ Tree ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Inserting 8* into Example B+ Tree ,[object Object],[object Object],2* 3* 5* 7* 8* 5 Entry to be inserted in parent node. (Note that 5 is continues to appear in the leaf.) s copied up and appears once in the index. Contrast 5 24 30 17 13 Entry to be inserted in parent node. (Note that 17 is pushed up and only this with a leaf split.)
Example B+ Tree After Inserting 8* ,[object Object],[object Object],2* 3* Root 17 24 30 14* 16* 19* 20* 22* 24* 27* 29* 33* 34* 38* 39* 13 5 7* 5* 8*
Deleting a Data Entry from a B+ Tree ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Example Tree After (Inserting 8*, Then) Deleting 19* and 20* ... ,[object Object],[object Object],2* 3* Root 17 30 14* 16* 33* 34* 38* 39* 13 5 7* 5* 8* 22* 24* 27 27* 29*
... And Then Deleting 24* ,[object Object],[object Object],30 22* 27* 29* 33* 34* 38* 39* 2* 3* 7* 14* 16* 22* 27* 29* 33* 34* 38* 39* 5* 8* Root 30 13 5 17

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OPTIMIZE DATABASE QUERIES

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  • 35. After Inserting 23*, 48*, 41*, 42* ... 10* 15* 20* 27* 33* 37* 40* 46* 51* 55* 63* 97* 20 33 51 63 40 Root 23* 48* 41* 42* Overflow Pages Leaf Index Pages Pages Primary
  • 36. ... Then Deleting 42*, 51*, 97* 10* 15* 20* 27* 33* 37* 40* 46* 55* 63* 20 33 51 63 40 Root 23* 48* 41*
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Editor's Notes

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