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Assignment 3

Index Tuning

Database Tuning

Start date: November 3, 2015 Due date: November 16, 12:00 Grading: 1 point

In this assignment you will study the indexing capabilities of a database management systems of your choice.

Choose one of the following database management systems:

• PostgreSQL 9

• Oracle 12c

• SQL Server 2012

• IBM DB2 UDB V9

Consider the table Employee(ssnum,name,dept,salary), where ssnum is a key. For the system of your choice answer the following questions.

1. Which index data structures (e.g.,B+-tree index) are supported?

2. Discuss how the system supports clustered indexes, in particular:

a) How do you create a clustered index on ssnum? Show the query.1

b) Are clustered indexes on non-key attributes supported, e.g., on name? Show the query.

c) Is the clustered index dense or sparse?

d) How does the system deal with overflows in clustered indexes? How is the fill factor controlled?

e) Discuss any further characteristics of the system related to clustered indexes that are relevant to a database tuner?

3. Discuss how the system supports non-clustered indexes, in particular:

a) How do you create a non-clustered index on (dept,salary)? Show the query.1

1Give the queries for creating a hash indexand aB+-tree index if both of them are supported.

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b) Can the system take advantage of covering indexes? What if the index cov- ers the query, but the condition is not a prefix of the attribute sequence (dept,salary)?

c) Discuss any further characteristics of the system related to non-clustered in- dexes that are relevant to a database tuner?

4. If your system supports B+-trees, what kind of key compression (if any) does it support? How large is the default disk page? Can it be changed?

Important: Reference your information sources.

Please indicate the average time per group member that was spent solving this assign- ment. The time that you indicate will haveno impact on your grade.

Referenzen

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e) Discuss any further characteristics of the system related to clustering indexes that are relevant to a database tuner.. 3

• To ensure statistical soundness of the throughput, compute the average runtime per query, the overall runtime should be more than one minute, and the client program generating

hash join: large buckets (build bucket does not fit main memory) index join: matching records on multiple disk pages. merge join: matching records do not fit in memory at the

• To compute the throughput, measure the overall runtime for several runs of a query and divide the number of queries by the runtime.. The overall runtime should be more than one

e) Discuss any further characteristics of the system related to clustering indexes that are relevant to a database tuner.. 3

hash join: large buckets (build bucket does not fit main memory) index join: matching records on multiple disk pages. merge join: matching records do not fit in memory at the

Compare clustered B + -tree, non-clustered B + -tree, non-clustered hash index, and table scan (no index) for the following queries and measure the throughput:.. SELECT * FROM