Download - Overview of Indexing
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Overview of Indexing
Chapter 8 – Part II.
1. Introduction to indexing2. First glimpse at indices and
workloads
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Understanding the Workload
For each query in workload: Which relations does it access? Which attributes are retrieved? Which attributes are involved in selection/join
conditions? How selective are these conditions likely to be?
For each update in workload: Which attributes are involved in selection/join
conditions? How selective are these conditions likely to be? The type of update (INSERT/DELETE/UPDATE), and the
attributes that are affected.
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Choice of Indexes What indexes should we create?
Which relations should have indexes? What field(s) should be the search key? Should we build several indexes?
For each index, what kind of an index should it be? Clustered vs. unclustered? Hash vs. tree?
• Clustering must be used sparingly and only when justified by frequent queries that benefit from clustering.
• At most one index can be clustered. (Why?)• Consider utilizing index-only evaluation. (e.g., avg(age))
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Choice of Indexes: One Approach
Consider most important queries in turn.
Consider best plan using current indexes, and see if a better plan possible with additional index. If so, create it.
Consider impact on updates in workload!• Trade-off: Indexes can make queries go faster,
updates slower. Require disk space, too.
Obviously, we must understand how DBMS evaluates queries and creates query evaluation plans
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Index Selection Guidelines
Attributes in WHERE clause are candidates for index keys.
Exact match condition suggests hash index.
Range query suggests tree index.
Clustering is especially useful for range queries
Clustering can also help equality queries if there are many duplicates.
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Index Selection Guidelines
Multi-attribute search keys considered when WHERE clause contains several conditions.
Order of attributes is important for range queries.
Such indexes can sometimes enable index-only strategies for important queries.
Question : For index-only strategies, is clustering important ?
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Index Selection Guidelines
Try to choose indexes that benefit as many queries as possible.
Since only one index can be clustered per relation, choose it based on important queries that would benefit the most from clustering.
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Examples of Clustered Indexes
B+ tree index on E.dno? B+ tree index on E.age ?
Trade-offs : How selective is the condition?
(all > 40?) or (only some > 40)
Is the index clustered?
SELECT E.dnoFROM Emp EWHERE E.age>40
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Examples of Clustered Indexes
Consider the GROUP BY query. Index on E.age ? E.dno ?
Issues : Use Index on E.age ? If many tuples have E.age > 10, using E.age
index and sorting the retrieved tuples may be costly.
Use Index on E.dno ? Clustered E.dno index may be better!
What about without WHERE condition?
SELECT E.dno, COUNT (*)FROM Emp EWHERE E.age>10GROUP BY E.dno
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Examples of Clustered Indexes
B+ tree index on E.hobby? NOTE: is equality query. NOTE : may contain many duplicates.
Clustered or Unclustered index ? CONCLUDE : Clustering on E.hobby helps!
QUESTION: what if index is unclustered ? CONCLUDE: may prefer to do a full scan.
SELECT E.dnoFROM Emp EWHERE E.hobby=Stamps
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Indexes with Composite Search Keys
sue 13 75
bob
cal
joe 12
10
20
8011
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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 recordssorted by name
Data entries in indexsorted by <sal,age>
Data entriessorted by <sal>
Composite Search Keys: Search on combination of fields (sal and age).
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Equality and Composite Search Keys
Equality query: Every field value is equal to a constant value.
Examples : age=20 sal =75 age=20 and sal =75 sal =75 and age=20
sue 13 75
bob
cal
joe 12
10
20
8011
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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 recordssorted by name
Data entries in indexsorted by <sal,age>
Data entriessorted by <sal>
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Composite Search Keys
If retrieve Emp records with age=30 AND sal=4000
Index on <age,sal> would be better than an index on age or an index on sal.
Choice of index key orthogonal to clustering
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Ranges and Composite Search Keys
Range query: Some field value is not a constant but a range.
Examples : age=12 and sal >
10
age =12
sue 13 75
bob
cal
joe 12
10
20
8011
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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 recordssorted by name
Data entries in indexsorted by <sal,age>
Data entriessorted by <sal>
Examples of composite keyindexes using lexicographic order.
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Composite Search Keys
If condition is: 20<age<30 AND 3000<sal<5000:
Clustered tree index on <age,sal> or <sal,age> is best.
If condition is: age=30 AND 3000<sal<5000:
Clustered <age,sal> index much better than <sal,age> index!
Composite indexes are larger, updated more often.
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Index-Only Plans
Answer a query without retrieving actual tuples …
Is that possible ?
If index with suitable information is available.
Why is it a good idea ?
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Index-Only Plans
SELECT E.dno, COUNT(*)FROM Emp EGROUP BY E.dno
SELECT E.dno, MIN(E.sal)FROM Emp EGROUP BY E.dno
SELECT AVG(E.sal)FROM Emp EWHERE E.age=25 AND E.sal BETWEEN 3000 AND 5000
<E.dno> ?
<E.dno> ?<E.sal> ?<E.dno,E.sal> ?
<E. age,E.sal> or<E.sal, E.age>?
Tree index!
+ Does index-only evaluation make sense?
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Index-Only Plans : Multi-Key Index
PROS:+ The chance for index-only evaluation is
increased.
CONS: - Index size larger. - Update response for any field.
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Index-Only Plans
Tree index on <dno,age>, or on :
<age,dno>
Which is better?
SELECT E.dno, COUNT (*)FROM Emp EWHERE E.age=30GROUP BY E.dno
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Index-Only Plans
Tree index on <dno,age>, or on :
<age,dno> Which is better?
SELECT E.dno, COUNT (*)FROM Emp EWHERE E.age=30GROUP BY E.dno
SELECT E.dno, COUNT (*)FROM Emp EWHERE E.age>30GROUP BY E.dno
What if we consider the second query?
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Index-Only Plans : Multiple Relations
SELECT DISTINCT ( D.mgr )FROM Dept D, Emp EWHERE D.dno=E.dno
<E.dno>Or<D.dno>Or<D.mgr>
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Summary
Understanding nature of workload for application, and the performance goals is essential to developing a good design.
What are the important queries and updates?
What attributes/relations are involved?
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More Summary Indexes must be chosen to speed up important
queries
Index maintenance overhead on updates to key fields.
Choose indexes that can help many queries, if possible.
Build indexes to support index-only strategies.
Clustering is an important decision; only one index on a given relation can be clustered!
Order of fields in composite index key can be important.