2012-02-14 1 Silvia Stefanova, UDBL - IT - UU

DATABASE DESIGN I - 1DL300

Spring 2012

An Introductory Course on Database Systems

http://www.it.uu.se/edu/course/homepage/dbastekn/vt12/

Erik Zeitler Uppsala Database Laboratory

Department of Information Technology, Uppsala University, Uppsala, Sweden

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Introduction to Physical Database Design

Elmasri/Navathe ch 16 & 17 Padron-McCarthy/Risch ch 21 & 22

Silvia Stefanova

Department of Information Technology Uppsala University, Uppsala, Sweden

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Outline • Index in the DBMS • Physical Database Design: main concepts • Data structures for physical storage of the database

Unsorted files Sorted files Hashing methods Files sorted according to an index

• Indexes and index files a) Simple (one-level) index

Primary index Secondary index Clustering index

b) Search trees - multi-level index (Covered in DB II) c) Hash indexes (Covered in DB II)

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• The physical database - a collection of stored records organized in files on the hard disk. A record consists of a number of data fields. Each field has an elementary data type

(integer, real, string, pointer etc.)

• Records are used for physical storage of: Tuples, where each attribute in the tuple is stored as a field. Objects in object-oriented databases.

Physical Database Design

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• A database file: sequence of units, called blocks. Blocks are units of both storage allocation and data transfer.

• Database system seeks to minimize the number of block

transfers between the disk and memory. Reduce the number of disk accesses by keeping as many

blocks as possible in main memory.

• Buffer – portion of main memory available to store copies of disk blocks.

• Buffer manager – subsystem responsible for allocating buffer space in main memory.

Physical Database Design

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• A disk block contains information that is needed for record access: Block addresses, record format etc. To find records, one or several blocks are transferred

to (one or several buffers in) primary memory. These blocks can then be searched to find the records that were sought. If the address to the block containing the record is

unknown one has to search through all block in the file (linear search).

Physical Database Design

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• Heap A record can be placed anywhere in the file where a space is

available • Sequential

Records are in sequential order The order is based on the value of the search key of each

record • Hashing

A hash function is computed on some attribute of each record; the result specifies in which block of the file the record should be placed

• Ordered according to an index

Organization of DB records in files

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• New records are added to the end of the file. • Suitable when we don’t know how data shall be used.

Insert - very efficient Search - expensive (linear to the size). Delete - expensive (search - read into - delete - write back). Update of a record of variable length can be hard Retrieval according to a certain order requires that the file

must be sorted which is expensive.

• Instead of physically removing a record one can mark the record as deleted. Both methods require a periodically reorganization of the file.

Heap files (Unordered files)

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• The records are ordered according to the value of a certain field (ordering field) Ordered retrieval - very fast (no sorting needed). Next record in the order is found on the same block (except

for the last record in the block) Search - fast (binary search - log2b; b – number of the

sorted blocks) Insert and delete - expensive since the file must be kept

sorted. • Suitable for applications that require sequential

processing of the entire file • Need to reorganize the file from time to time to restore

sequential order

Sequential files (Sorted files)

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Hashing technique

• Goal Retrieve records faster.

• How? Find a hash function, h, so that for a record p, h(f(p)) provides

the address to the block where p shall be stored. Example: h(f(p)) = f(p) mod M,

f(p) : hash field for p M : hash table size.

• What : Most of the records will be found in only one block access.

• Observe !!! Collision if: h(f(p)) = h(f(p’))

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External Hashing (Fig. 16.9)

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• The records in the file are organized as a hash table (external hashing) Records are hashed according to the bucket method. A bucket = one block. The bucket address is used as the address for a record. Info. regarding the block address for each bucket is stored in

the beginning of the file.

• Since several records can be stored in the same block, the number of collisions decreases.

• When a bucket is filled one can use a chaining method where a number of buckets are used as overflow buckets.

External Hashing

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• Choose a larger array of size M+O and use the extra space as overflow places.

Chaining Method in External Hashing

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Outline • Index in the DBMS • Physical Database Design: main concepts • Data structures for physical storage of the database

Unsorted files Sorted files Hashing methods Files ordered according to an index

• Indexes and index files a) Simple (one-level) index

Primary index Secondary index Clustering index

b) Search trees - multi-level index (Covered in DB II) c) Hash indexes (Covered in DB II)

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Indexes • An index (or index file) is an extra file structure used to

make the retrieval of records faster. • Search key (indexing field)– attribute or set of attributes

(data fields) used to look up records in a file. • An index file

Has records (index entries) of the form: <search key, pointer>

The entries determine the physical address for records Much smaller than the data file

• Two main types of indexes:

Ordered indexes: search keys are stored Hash indexes: search keys are distributed uniformly across

“buckets” using a “hash function”.

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Primary Index

• Records in the data file are kept ordered on the primary key

• Primary index - a file of records with two fields. 1st field : of the same type as the primary key field (index

field) for the data file 2nd field : a pointer to a block (block pointer).

• A primary index has one index record for each block in the data file, and therefore is called a sparse index (or “non-dense index”)

• The first record in each block is called the anchor record of the block

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Example - primary index (Fig 17.1)

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Clustering index

• Clustering index is defined for data files that are ordered according to a non-key field (the clustering field), i.e. several records in the data file can have the same value for the clustering field.

• A clustering index - a file of records with two fields: 1st field : the same type as the clustering field for the data file 2nd field : a pointer to a block of records (block pointer) in the

data file.

• Insert and dele are problematic. However, if each block only can contain records with the same clustering value the insertion problem is solved. (see Elmasri/Navathe Fig 17.3)

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Example - clustering index (Fig 17.2)

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Secondary index

• The data file is not sorted according to the indexing field. • A secondary index is an ordered file that consists of

records with two fields. The 1st field is of the same type as the indexing field (any field in

the data file) The 2nd field is a block pointer.

• Two options: Option 1 (key) : the index field has unique values for each

record; dense index Option 2 (non-key) : several records in the data file can have

the same value for the index field;

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Example – a dense secondary index (Fig 17.4)

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Summary 1. Physical Database Design

2. Indexes – why and how ? Primary Secondary Clustering