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MySQL blob tinyint(1) date datetime decimal float int(11) varchar(255) text time datetime
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61 Creating Migrations
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class within postgresql_adapterrb:
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NATIVE_DATABASE_TYPES = { :primary_key => "serial :string => { :name :text => { :name :integer => { :name :float => { :name :decimal => { :name :datetime => { :name :timestamp => { :name :time => { :name :date => { :name :binary => { :name :boolean => { :name :xml => { :name } primary key"freeze, => "character varying", :limit => 255 }, => "text" }, => "integer" }, => "float" }, => "decimal" }, => "timestamp" }, => "timestamp" }, => "time" }, => "date" }, => "bytea" }, => "boolean" }, => "xml" }
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Column Options For many column types, just specifying type is not enough information All column declarations accept the following options:
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Sets a default to be used as the initial value of the column for new rows You don t ever need to explicitly set the default value to null Just leave off this option to get a null default value It s worth noting that MySQL 5x ignores default values for binary and text columns
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Adds a size parameter to string, text, binary, or integer columns Its meaning varies depending on the column type that it is applied to Generally speaking, limits for string types refers to number of characters, whereas for other types it specifies the number of bytes used to store the value in the database
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Makes the column required at the database level by adding a not null constraint
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Decimal Precision Columns declared as type :decimal accept the following options:
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Precision is the total number of digits in a number
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6: Active Record Migrations
Scale is the number of digits to the right of the decimal point For example, the number 12345 has a precision of 5 and a scale of 2 Logically, the scale cannot be larger than the precision Note
Decimal types pose a serious opportunity for data loss during migrations of production data between different kinds of databases For example, the default precisions between Oracle and SQL Server can cause the migration process to truncate and change the value of your numeric data It s always a good idea to specify precision details for your data
Column Type Gotchas The choice of column type is not necessarily a simple choice and depends on both the database you re using and the requirements of your application
:binary Depending on your particular usage scenario, storing binary data in the
database can cause big performance problems Active Record doesn t generally exclude any columns when it loads objects from the database, and putting large binary attributes on commonly used models will increase the load on your database server significantly If you must put binary content in a commonly-used class, take advantage of the select method to only bring back the columns you need
:boolean The way that boolean values are stored varies from database to database
Some use 1 and 0 integer values to represent true and false, respectively Others use characters such as T and F Rails handles the mapping between Ruby s true and false very well, so you don t need to worry about the underlying scheme yourself Setting attributes directly to database values such as 1 or F may work correctly, but is considered an anti-pattern
:datetime and :timestamp The Ruby class that Rails maps to datetime and
timestamp columns is Time In 32-bit environments, Time doesn t work for dates
before 1902 Ruby s DateTime class does work with year values prior to 1902, and Rails falls back to using it if necessary It doesn t use DateTime to begin for performance reasons Under the covers, Time is implemented in C and is very fast, whereas DateTime is written in pure Ruby and is comparatively slow
:time It s very, very rare that you want to use a :time datatype; perhaps if you re
modeling an alarm clock Rails will read the contents of the database as hour, minute, and second values, into a Time object with dummy values for the year, month, and day
61 Creating Migrations
:decimal Older versions of Rails (prior to 12) did not support the fixed-precision
:decimal type and as a result many old Rails applications incorrectly used :float
datatypes Floating-point numbers are by nature imprecise, so it is important to choose :decimal instead of :float for most business-related applications
Tim says
If you re using a float to store values which need to be precise, such as money, you re a jackass Floating point calculations are done in binary rather than decimal, so rounding errors abound in places you wouldn t expect