1. Relational Databases: Basic Concepts
BCHB524 Lecture 21
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2. Outline What is a (relational) database?
When are relational databases used?
Commonly used database management systems
Using existing databases
Creating and populating new databases
Python and relational databases
Exercises
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3. (Relational) Databases
Databases store information
Bioinformatics has lots of file-based information:
FASTA sequence databases
Genbank format sequences
Store sequence, annotation, references, annotation
Good as archive or comprehensive reference
Poor for a few items
Relational databases also store information
Good for a few items at a time
Flexible on which items
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4. Relational Databases Store information in a table Rows represent items
Columns represent items' properties or attributes
Name
Continent
Region
Surface Area
Population
GNP
Brazil
South America
776739
Indonesia
Asia
Southeast Asia
84982
India
Southern and Central Asia
447114
China
Eastern Asia
982268
Pakistan
796095
61289
United States
North America
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5. Relational Databases Tables can be millions of rows
Can access a few rows fast
Countries more than 100,000,000 in population?
Countries on the “Asia” continent?
Countries that start with “U”?
Countries with GNP =
Name
Continent
Region
Surface Area
Population
GNP
Brazil
South America
776739
Indonesia
Asia
Southeast Asia
84982
India
Southern and Central Asia
447114
China
Eastern Asia
982268
Pakistan
796095
61289
United States
North America
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6. When are Relational Databases Used?
LARGE datasets
Does data fit in memory?
Store data first ...
... ask questions later
Lookup or sort by many keys
For single key, simple data structures often work
Store results of expensive compute or data-cleanup
Compute once and return results many times
"Random" or unknown access patterns
Specialized data-structures not appropriate
Use string/sequence indexes for sequence data
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7. Common DBMS Oracle MySQL Sqlite
Commercial, market leader, widely used in businesses
MySQL
Free, open-source, widely used in bioinformatics, suitable for large scale deployment
Sqlite
Free, open-source, minimal installation requirements, no users, suitable for small scale deployment
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8. Lets look at some examples
We'll use a third-party program to "look at" Sqlite databases:
SqliteStudio (Linux), SqliteSpy (Windows), …
Download examples:
World.db3, taxa.db3 from Course data folder
Use SqliteStudio to look at examples
World.db3, taxa.db3
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9. Using existing databases
Use the "select" SQL command to find relevant rows
select * from Country where Population > ;
select * from Country where Continent = 'Asia';
select * from Country where Name like 'U%';
select * from Country where GNP = ;
Each command ends in semicolon ";".
"where" specifies the condition/constraint/rule.
"*" asks for all attributes from the relevant rows.
Lets experiment with world and taxa databases.
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10. Using existing databases
Select can combine (“join”) multiple tables
Use the where condition to match rows from each table and “link” corresponding rows…
select * from taxonomy, name
where
taxonomy.rank = 'species'
and
name.name_class = 'misspelling'
name.tax_id = taxonomy.tax_id
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11. Using existing databases
Select can sort and/or return top 10
select * from taxonomy limit 10;
select * from taxonomy
order by scientific_name;
order by tax_id desc limit 10;
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12. Using existing databases
Select can count and do string matching.
"like" uses special symbols:
% matches zero or more symbols
_ match exactly one symbol
Some RDBMS support regular expressions
MySQL, for example.
select count(*) from taxonomy where scientific_name like 'D%';
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13. Creating databases Use the "create" SQL command to create tables
CREATE TABLE taxonomy (
tax_id INTEGER PRIMARY KEY,
scientific_name TEXT,
rank TEXT,
parent_id INT );
CREATE TABLE name (
id INTEGER PRIMARY KEY,
tax_id INT,
name TEXT,
name_class TEXT
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14. Populating databases
Use the "insert" SQL command to add rows to tables
Usually, the special id column is initialized automatically
INSERT INTO name (tax_id,name,name_class) VALUES (9606,'H. sapiens','synonym');
SELECT * from name where tax_id = 9606;
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15. Python and Relational Databases
Issue select statements from python and iterate through the results
Sometimes it is easiest to make Python do some of the work!
import sqlite3 conn = sqlite3.connect('taxa.db3')
c = conn.cursor() c.execute("""    select * from name    where name like 'D%'    limit 10;  """) for row in c:    print row
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16. Python and Relational Databases
Use parameter substitution for run-time values
import sys import sqlite3 tid = int(sys.argv[1]) conn = sqlite3.connect('taxa.db3') params = [tid,'scientific name'] c = conn.cursor() c.execute("""    select * from name    where tax_id = ? and name_class = ?; """,params) for row in c:    print row
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17. Next-time: Object-relational mappers
Setup python to treat tables as classes, rows as objects
# Set up data-model from model import * hs = Taxonomy.get(9606) for n in hs.names:     print n.name, "|", n.nameClass condition = Name.q.name.startswith('Da') for n in Name.select(condition):     print n.name, "|", n.nameClass
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18. Exercises Read through an online course in SQL
sqlcourse.com, sql-tutorial.net, ...
Write a python program to lookup the scientific name for a user-supplied organism name.
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19. Homework 10 Due Monday, November 19th. Exercises from Lectures 20, 21
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