2018 02 20_biological_databases_part2_v_upload
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This document discusses biological databases and SQL. It provides an overview of primary and derived data in biological research, as well as different data levels. It then discusses direct querying of selected bioinformatics databases using SQL and provides examples of 3-tier database models. The document proceeds to discuss rationale for learning SQL to query biological databases and provides definitions and explanations of key SQL concepts like tables, records, queries, data types, keys, integrity rules and constraints.
2018 02 20_biological_databases_part2_v_upload
- 2. FBW 27-02-2018 Biological Databases Wim Van Criekinge
- 5. Syllabi left
- 6. Project
- 9. Data Levels in Biological Research
- 11. Primary dataDerived data Interpreted data/ knowledge Experimental metadata Analytical metadata
- 12. Direct Queryability of Selected Bioinformatics Databases Database Direct Querying? How? Modality DB Engine ArrayExpressWarehouse Eventually http://www.ebi.ac.uk/aedw/ SQL Oracle BioWarehouse Yes http://biowarehouse.ai.sri.com/ - need account SQL Oracle/MySQL Ensembl Yes http://www.ensembl.org/info/d ata/download.html SQL MySQL Mouse Genome Database Yes ask for account SQL Sybase PharmGKB Yes http://www.pharmgkb.org/hom e/projects/webservices/ SOAP-based Oracle Saccharomyces Genome Database EventuallyMaybe Oracle Stanford Microarray Database No Oracle
- 13. Example 3-tier model in biological database
- 14. Rationale to study SQL • Learning SQL to Query Biological Databases • Are you getting too much data, or missing crucial data when querying via a Web interface? Many biological databases can be queried directly via SQL, thus bypassing the limitations of the database's interface. SQL is at the heart of biological databases as diverse as Ensembl, ArrayExpress and the Mouse Genome Database. • Focus on understanding relational databases by studying a repository of biological data and learn how to query it using SQL.
- 15. SQL consists of only 4 statements, sometimes referred to as CRUD: –Create - INSERT - to store new data –Read - SELECT - to retrieve data –Update - UPDATE - to change or modify data. –Delete - DELETE - delete or remove data Structured Query Language
- 16. Definitions Definitions • Database: Collection of tables • Table – Collection of records that share a common fundamental characteristic • E.g., patients and locations can each be stored in their own table • Record – Basic unit of information in a relation information – A record is composed of fields – E.g., 1 record per person • Query – Set of instructions to a database “engine” to retrieve, sort and format returning data. • “find me all patients in my database”
- 17. Table Characteristics • Two-dimensional structure with rows and columns • Rows (tuples) represent single entity • Columns represent attributes • Row/column intersection represents single value • Tables must have an attribute to uniquely identify each row • Column values all have same data format • Each column has range of values called attribute domain • Order of the rows and columns is immaterial to the DBMS
- 18. Numeric Data Types MySQL uses all the standard ANSI SQL numeric data types, so if you're coming to MySQL from a different database system, these definitions will look familiar to you. The following list shows the common numeric data types and their descriptions: INT - A normal-sized integer that can be signed or unsigned. If signed, the allowable range is from -2147483648 to 2147483647. If unsigned, the allowable range is from 0 to 4294967295. You can specify a width of up to 11 digits. TINYINT - A very small integer that can be signed or unsigned. If signed, the allowable range is from -128 to 127. If unsigned, the allowable range is from 0 to 255. You can specify a width of up to 4 digits. SMALLINT - A small integer that can be signed or unsigned. If signed, the allowable range is from -32768 to 32767. If unsigned, the allowable range is from 0 to 65535. You can specify a width of up to 5 digits. MEDIUMINT - A medium-sized integer that can be signed or unsigned. If signed, the allowable range is from - 8388608 to 8388607. If unsigned, the allowable range is from 0 to 16777215. You can specify a width of up to 9 digits. BIGINT - A large integer that can be signed or unsigned. If signed, the allowable range is from - 9223372036854775808 to 9223372036854775807. If unsigned, the allowable range is from 0 to 18446744073709551615. You can specify a width of up to 20 digits. FLOAT(M,D) - A floating-point number that cannot be unsigned. You can define the display length (M) and the number of decimals (D). This is not required and will default to 10,2, where 2 is the number of decimals and 10 is the total number of digits (including decimals). Decimal precision can go to 24 places for a FLOAT. DOUBLE(M,D) - A double precision floating-point number that cannot be unsigned. You can define the display length (M) and the number of decimals (D). This is not required and will default to 16,4, where 4 is the number of decimals. Decimal precision can go to 53 places for a DOUBLE. REAL is a synonym for DOUBLE. DECIMAL(M,D) - An unpacked floating-point number that cannot be unsigned. In unpacked decimals, each decimal corresponds to one byte. Defining the display length (M) and the number of decimals (D) is required. NUMERIC is a synonym for DECIMAL.
- 19. String Data Type • Although numeric and date types are fun, most data you'll store will be in string format. This list describes the common string datatypes in MySQL. • CHAR(M) - A fixed-length string between 1 and 255 characters in length (for example CHAR(5)), right- padded with spaces to the specified length when stored. Defining a length is not required, but the default is 1. • VARCHAR(M) - A variable-length string between 1 and 255 characters in length; for example VARCHAR(25). You must define a length when creating a VARCHAR field. • BLOB or TEXT - A field with a maximum length of 65535 characters. BLOBs are "Binary Large Objects" and are used to store large amounts of binary data, such as images or other types of files. Fields defined as TEXT also hold large amounts of data; the difference between the two is that sorts and comparisons on stored data are case sensitive on BLOBs and are not case sensitive in TEXT fields. You do not specify a length with BLOB or TEXT. • TINYBLOB or TINYTEXT - A BLOB or TEXT column with a maximum length of 255 characters. You do not specify a length with TINYBLOB or TINYTEXT. • MEDIUMBLOB or MEDIUMTEXT - A BLOB or TEXT column with a maximum length of 16777215 characters. You do not specify a length with MEDIUMBLOB or MEDIUMTEXT. • LONGBLOB or LONGTEXT - A BLOB or TEXT column with a maximum length of 4294967295 characters. You do not specify a length with LONGBLOB or LONGTEXT. • ENUM - An enumeration, which is a fancy term for list. When defining an ENUM, you are creating a list of items from which the value must be selected (or it can be NULL). For example, if you wanted your field to contain "A" or "B" or "C", you would define your ENUM as ENUM ('A', 'B', 'C') and only those values (or NULL) could ever populate that field.
- 20. Built-in Data Types in SQL • date: Dates, containing a (4 digit) year, month and date – Example: date ‘2005-7-27’ • time: Time of day, in hours, minutes and seconds. – Example: time ‘09:00:30’ time ‘09:00:30.75’ • timestamp: date plus time of day – Example: timestamp ‘2005-7-27 09:00:30.75’ • interval: period of time – Example: interval ‘1’ day – Subtracting a date/time/timestamp value from another gives an interval value – Interval values can be added to date/time/timestamp values
- 21. Build-in Data Types in SQL (Cont.) • Can extract values of individual fields from date/time/timestamp – Example: extract (year from r.starttime) • Can cast string types to date/time/timestamp – Example: cast <string-valued-expression> as date – Example: cast <string-valued-expression> as time
- 22. User-Defined Types • create type construct in SQL creates user-defined type create type Dollars as numeric (12,2) final • create domain construct in SQL-92 creates user- defined domain types create domain person_name char(20) not null • Types and domains are similar. Domains can have constraints, such as not null, specified on them.
- 23. Large-Object Types • Large objects (photos, videos, CAD files, etc.) are stored as a large object: – blob: binary large object -- object is a large collection of uninterpreted binary data (whose interpretation is left to an application outside of the database system) – clob: character large object -- object is a large collection of character data – When a query returns a large object, a pointer is returned rather than the large object itself.
- 24. Creating a Table • To create a table, use the CREATE TABLE command: mysql> CREATE TABLE pet ( -> name VARCHAR(20), -> owner VARCHAR(20), -> species VARCHAR(20), -> sex CHAR(1), -> birth DATE, death DATE); Query OK, 0 rows affected (0.04 sec)
- 25. Keys • One or more attributes that determine other attributes – Key attribute – Composite key • Full functional dependence • Entity integrity – Uniqueness – No ‘null’ value in key
- 26. Example Tables
- 28. Keys (con’t.) • Primary key – Candidate key to uniquely identify all other attributes in a given row • Foreign key – Values must match primary key in another table
- 29. Integrity Rules • Entity integrity – Ensures all entities are unique – Each entity has unique key • Referential integrity – Foreign key must have null value or match primary key values – Makes it impossible to delete row whose primary key has mandatory matching foreign key values in another table
- 30. Integrity Constraints • Integrity constraints guard against accidental damage to the database, by ensuring that authorized changes to the database do not result in a loss of data consistency. – A checking account must have a balance greater than $10,000.00 – A salary of a bank employee must be at least $4.00 an hour – A customer must have a (non-null) phone number
- 31. Referential Integrity • Ensures that a value that appears in one relation for a given set of attributes also appears for a certain set of attributes in another relation. – Example: If “Perryridge” is a branch name appearing in one of the tuples in the account relation, then there exists a tuple in the branch relation for branch “Perryridge”. • Primary and candidate keys and foreign keys can be specified as part of the SQL create table statement: – The primary key clause lists attributes that comprise the primary key. – The unique key clause lists attributes that comprise a candidate key. – The foreign key clause lists the attributes that comprise the foreign key and the name of the relation referenced by the foreign key. By default, a foreign key references the primary key attributes of the referenced table.
- 42. Install BIOSQL locally • Get latest version of mysql (MAMP, mariaDB) • Download biosqldb-mysql.sql • Remove type=innodb • Launch database server • Connect using toad (port 8889) • Create database biosql; • Set as active database • Use worksheet to execute biosqldb- mysql.sql
- 44. How ODBC Works? • ODBC inserts a middle layer called a Client Driver • Purpose of the Client Driver is to translate the applications queries into commands that the DBMS understands
- 45. Other Parts of the Architecture • Application – calls functions defined in the ODBC API to access a data source • Driver Manager – implements the ODBC API and provides information to the application • Database – contains all the data
- 46. Setting Up a Data Source in Windows • A data source is just a database that ODBC connects to • This allows the person to change database types without any changes to the program • Step 1. Get a database. – Using access for this example because it’s on this computer
- 47. Conclusion The four parts that make up ODBC:
- 48. Conclusion • Advantages: – Allows access to different types of databases – Uniform way of retrieving information – Highly efficient – Low memory requirements • Disadvantages – Complex and steep learning curve – All data in database must look like a relational database
- 49. Conclusion • ODBC changed the way people code their programs that have to interact with databases. • The efficiency of programmers in the business world has increased due to ODBC because they no longer are wasting time to create multiple copies of a program. • ODBC has vastly improved the way programmers deal with databases.
- 55. Project