This chapter covers how one creates the database structures that will hold one's data. In a relational database, the raw data is stored in tables, so the majority of this chapter is devoted to explaining how tables are created and modified and what features are available to control what data is stored in the tables. Subsequently, we discuss how tables can be organized into schemas, and how privileges can be assigned to tables. Finally, we will briefly look at other features that affect the data storage, such as views, functions, and triggers. Detailed information on these topics is found in . A table in a relational database is much like a table on paper: It consists of rows and columns. The number and order of the columns is fixed, and each column has a name. The number of rows is variable -- it reflects how much data is stored at a given moment. SQL does not make any guarantees about the order of the rows in a table. When a table is read, the rows will appear in random order, unless sorting is explicitly requested. This is covered in . Furthermore, SQL does not assign unique identifiers to rows, so it is possible to have several completely identical rows in a table. This is a consequence of the mathematical model that underlies SQL but is usually not desirable. Later in this chapter we will see how to deal with this issue. Each column has a data type. The data type constrains the set of possible values that can be assigned to a column and assigns semantics to the data stored in the column so that it can be used for computations. For instance, a column declared to be of a numerical type will not accept arbitrary text strings, and the data stored in such a column can be used for mathematical computations. By contrast, a column declared to be of a character string type will accept almost any kind of data but it does not lend itself to mathematical calculations, although other operations such as string concatenation are available. PostgreSQL includes a sizable set of built-in data types that fit many applications. Users can also define their own data types. Most built-in data types have obvious names and semantics, so we defer a detailed explanation to . Some of the frequently used data types are integer for whole numbers, numeric for possibly fractional numbers, text for character strings, date for dates, time for time-of-day values, and timestamp for values containing both date and time. To create a table, you use the aptly named CREATE TABLE command. In this command you specify at least a name for the new table, the names of the columns and the data type of each column. For example: CREATE TABLE my_first_table ( first_column text, second_column integer ); This creates a table named my_first_table with two columns. The first column is named first_column and has a data type of text; the second column has the name second_column and the type integer. The table and column names follow the identifier syntax explained in . The type names are usually also identifiers, but there are some exceptions. Note that the column list is comma-separated and surrounded by parentheses. Of course, the previous example was heavily contrived. Normally, you would give names to your tables and columns that convey what kind of data they store. So let's look at a more realistic example: CREATE TABLE products ( product_no integer, name text, price numeric ); (The numeric type can store fractional components, as would be typical of monetary amounts.) When you create many interrelated tables it is wise to choose a consistent naming pattern for the tables and columns. For instance, there is a choice of using singular or plural nouns for table names, both of which are favored by some theorist or other. There is a limit on how many columns a table can contain. Depending on the column types, it is between 250 and 1600. However, defining a table with anywhere near this many columns is highly unusual and often a questionable design. If you no longer need a table, you can remove it using the DROP TABLE command. For example: DROP TABLE my_first_table; DROP TABLE products; Attempting to drop a table that does not exist is an error. Nevertheless, it is common in SQL script files to unconditionally try to drop each table before creating it, ignoring the error messages. If you need to modify a table that already exists look into later in this chapter. With the tools discussed so far you can create fully functional tables. The remainder of this chapter is concerned with adding features to the table definition to ensure data integrity, security, or convenience. If you are eager to fill your tables with data now you can skip ahead to and read the rest of this chapter later. Every table has several system columns that are implicitly defined by the system. Therefore, these names cannot be used as names of user-defined columns. (Note that these restrictions are separate from whether the name is a key word or not; quoting a name will not allow you to escape these restrictions.) You do not really need to be concerned about these columns, just know they exist. columns system columns oid OID The object identifier (object ID) of a row. This is a serial number that is automatically added by PostgreSQL to all table rows (unless the table was created using WITHOUT OIDS, in which case this column is not present). This column is of type oid (same name as the column); see for more information about the type. tableoid The OID of the table containing this row. This column is particularly handy for queries that select from inheritance hierarchies, since without it, it's difficult to tell which individual table a row came from. The tableoid can be joined against the oid column of pg_class to obtain the table name. xmin The identity (transaction ID) of the inserting transaction for this tuple. (Note: In this context, a tuple is an individual state of a row; each update of a row creates a new tuple for the same logical row.) cmin The command identifier (starting at zero) within the inserting transaction. xmax The identity (transaction ID) of the deleting transaction, or zero for an undeleted tuple. It is possible for this column to be nonzero in a visible tuple: That usually indicates that the deleting transaction hasn't committed yet, or that an attempted deletion was rolled back. cmax The command identifier within the deleting transaction, or zero. ctid The physical location of the tuple within its table. Note that although the ctid can be used to locate the tuple very quickly, a row's ctid will change each time it is updated or moved by VACUUM FULL. Therefore ctid is useless as a long-term row identifier. The OID, or even better a user-defined serial number, should be used to identify logical rows. OIDs are 32-bit quantities and are assigned from a single cluster-wide counter. In a large or long-lived database, it is possible for the counter to wrap around. Hence, it is bad practice to assume that OIDs are unique, unless you take steps to ensure that they are unique. Recommended practice when using OIDs for row identification is to create a unique constraint on the OID column of each table for which the OID will be used. Never assume that OIDs are unique across tables; use the combination of tableoid and row OID if you need a database-wide identifier. (Future releases of PostgreSQL are likely to use a separate OID counter for each table, so that tableoid must be included to arrive at a globally unique identifier.) Transaction identifiers are also 32-bit quantities. In a long-lived database it is possible for transaction IDs to wrap around. This is not a fatal problem given appropriate maintenance procedures; see for details. However, it is unwise to depend on uniqueness of transaction IDs over the long term (more than one billion transactions). Command identifiers are also 32-bit quantities. This creates a hard limit of 232 (4 billion) SQL commands within a single transaction. In practice this limit is not a problem --- note that the limit is on number of SQL commands, not number of tuples processed. A column can be assigned a default value. When a new row is created and no values are specified for some of the columns, the columns will be filled with their respective default values. A data manipulation command can also request explicitly that a column be set to its default value, without knowing what this value is. (Details about data manipulation commands are in .) If no default value is declared explicitly, the null value is the default value. This usually makes sense because a null value can be thought to represent unknown data. In a table definition, default values are listed after the column data type. For example: CREATE TABLE products ( product_no integer, name text, price numeric DEFAULT 9.99 ); The default value may be a scalar expression, which will be evaluated whenever the default value is inserted (not when the table is created). Data types are a way to limit the kind of data that can be stored in a table. For many applications, however, the constraint they provide is too coarse. For example, a column containing a product price should probably only accept positive values. But there is no data type that accepts only positive numbers. Another issue is that you might want to constrain column data with respect to other columns or rows. For example, in a table containing product information, there should only be one row for each product number. To that end, SQL allows you to define constraints on columns and tables. Constraints give you as much control over the data in your tables as you wish. If a user attempts to store data in a column that would violate a constraint, an error is raised. This applies even if the value came from the default value definition. A check constraint is the most generic constraint type. It allows you to specify that the value in a certain column must satisfy an arbitrary expression. For instance, to require positive product prices, you could use: CREATE TABLE products ( product_no integer, name text, price numeric CHECK (price > 0) ); As you see, the constraint definition comes after the data type, just like default value definitions. Default values and constraints can be listed in any order. A check constraint consists of the key word CHECK followed by an expression in parentheses. The check constraint expression should involve the column thus constrained, otherwise the constraint would not make too much sense. You can also give the constraint a separate name. This clarifies error messages and allows you to refer to the constraint when you need to change it. The syntax is: CREATE TABLE products ( product_no integer, name text, price numeric CONSTRAINT positive_price CHECK (price > 0) ); So, to specify a named constraint, use the key word CONSTRAINT followed by an identifier followed by the constraint definition. A check constraint can also refer to several columns. Say you store a regular price and a discounted price, and you want to ensure that the discounted price is lower than the regular price. CREATE TABLE products ( product_no integer, name text, price numeric CHECK (price > 0), discounted_price numeric CHECK (discounted_price > 0), CHECK (price > discounted_price) ); The first two constraints should look familiar. The third one uses a new syntax. It is not attached to a particular column, instead it appears as a separate item in the comma-separated column list. Column definitions and these constraint definitions can be listed in mixed order. We say that the first two constraints are column constraints, whereas the third one is a table constraint because it is written separately from the column definitions. Column constraints can also be written as table constraints, while the reverse is not necessarily possible. The above example could also be written as CREATE TABLE products ( product_no integer, name text, price numeric, CHECK (price > 0), discounted_price numeric, CHECK (discounted_price > 0), CHECK (price > discounted_price) ); or even CREATE TABLE products ( product_no integer, name text, price numeric CHECK (price > 0), discounted_price numeric, CHECK (discounted_price > 0 AND price > discounted_price) ); It's a matter of taste. It should be noted that a check constraint is satisfied if the check expression evaluates to true or the null value. Since most expressions will evaluate to the null value if one operand is null they will not prevent null values in the constrained columns. To ensure that a column does not contain null values, the not-null constraint described in the next section should be used. A not-null constraint simply specifies that a column must not assume the null value. A syntax example: CREATE TABLE products ( product_no integer NOT NULL, name text NOT NULL, price numeric ); A not-null constraint is always written as a column constraint. A not-null constraint is functionally equivalent to creating a check constraint CHECK (column_name IS NOT NULL), but in PostgreSQL creating an explicit not-null constraint is more efficient. The drawback is that you cannot give explicit names to not-null constraints created that way. Of course, a column can have more than one constraint. Just write the constraints after one another: CREATE TABLE products ( product_no integer NOT NULL, name text NOT NULL, price numeric NOT NULL CHECK (price > 0) ); The order doesn't matter. It does not necessarily affect in which order the constraints are checked. The NOT NULL constraint has an inverse: the NULL constraint. This does not mean that the column must be null, which would surely be useless. Instead, this simply defines the default behavior that the column may be null. The NULL constraint is not defined in the SQL standard and should not be used in portable applications. (It was only added to PostgreSQL to be compatible with other database systems.) Some users, however, like it because it makes it easy to toggle the constraint in a script file. For example, you could start with CREATE TABLE products ( product_no integer NULL, name text NULL, price numeric NULL ); and then insert the NOT key word where desired. In most database designs the majority of columns should be marked not null. Unique constraints ensure that the data contained in a column or a group of columns is unique with respect to all the rows in the table. The syntax is CREATE TABLE products ( product_no integer UNIQUE, name text, price numeric ); when written as a column constraint, and CREATE TABLE products ( product_no integer, name text, price numeric, UNIQUE (product_no) ); when written as a table constraint. If a unique constraint refers to a group of columns, the columns are listed separated by commas: CREATE TABLE example ( a integer, b integer, c integer, UNIQUE (a, c) ); It is also possible to assign names to unique constraints: CREATE TABLE products ( product_no integer CONSTRAINT must_be_different UNIQUE, name text, price numeric ); In general, a unique constraint is violated when there are (at least) two rows in the table where the values of each of the corresponding columns that are part of the constraint are equal. However, null values are not considered equal in this consideration. That means, in the presence of a multicolumn unique constraint it is possible to store an unlimited number of rows that contain a null value in at least one of the constrained columns. This behavior conforms to the SQL standard, but we have heard that other SQL databases may not follow this rule. So be careful when developing applications that are intended to be portable. Technically, a primary key constraint is simply a combination of a unique constraint and a not-null constraint. So, the following two table definitions accept the same data: CREATE TABLE products ( product_no integer UNIQUE NOT NULL, name text, price numeric ); CREATE TABLE products ( product_no integer PRIMARY KEY, name text, price numeric ); Primary keys can also constrain more than one column; the syntax is similar to unique constraints: CREATE TABLE example ( a integer, b integer, c integer, PRIMARY KEY (a, c) ); A primary key indicates that a column or group of columns can be used as a unique identifier for rows in the table. (This is a direct consequence of the definition of a primary key. Note that a unique constraint does not, in fact, provide a unique identifier because it does not exclude null values.) This is useful both for documentation purposes and for client applications. For example, a GUI application that allows modifying row values probably needs to know the primary key of a table to be able to identify rows uniquely. A table can have at most one primary key (while it can have many unique and not-null constraints). Relational database theory dictates that every table must have a primary key. This rule is not enforced by PostgreSQL, but it is usually best to follow it. A foreign key constraint specifies that the values in a column (or a group of columns) must match the values appearing in some row of another table. We say this maintains the referential integrity between two related tables. Say you have the product table that we have used several times already: CREATE TABLE products ( product_no integer PRIMARY KEY, name text, price numeric ); Let's also assume you have a table storing orders of those products. We want to ensure that the orders table only contains orders of products that actually exist. So we define a foreign key constraint in the orders table that references the products table: CREATE TABLE orders ( order_id integer PRIMARY KEY, product_no integer REFERENCES products (product_no), quantity integer ); Now it is impossible to create orders with product_no entries that do not appear in the products table. We say that in this situation the orders table is the referencing table and the products table is the referenced table. Similarly, there are referencing and referenced columns. You can also shorten the above command to CREATE TABLE orders ( order_id integer PRIMARY KEY, product_no integer REFERENCES products, quantity integer ); because in absence of a column list the primary key of the referenced table is used as referenced column. A foreign key can also constrain and reference a group of columns. As usual, it then needs to be written in table constraint form. Here is a contrived syntax example: CREATE TABLE t1 ( a integer PRIMARY KEY, b integer, c integer, FOREIGN KEY (b, c) REFERENCES other_table (c1, c2) ); Of course, the number and type of the constrained columns needs to match the number and type of the referenced columns. A table can contain more than one foreign key constraint. This is used to implement many-to-many relationships between tables. Say you have tables about products and orders, but now you want to allow one order to contain possibly many products (which the structure above did not allow). You could use this table structure: CREATE TABLE products ( product_no integer PRIMARY KEY, name text, price numeric ); CREATE TABLE orders ( order_id integer PRIMARY KEY, shipping_address text, ... ); CREATE TABLE order_items ( product_no integer REFERENCES products, order_id integer REFERENCES orders, quantity integer, PRIMARY KEY (product_no, order_id) ); Note also that the primary key overlaps with the foreign keys in the last table. We know that the foreign keys disallow creation of orders that do not relate to any products. But what if a product is removed after an order is created that references it? SQL allows you to specify that as well. Intuitively, we have a few options: Disallow deleting a referenced product Delete the orders as well Something else? To illustrate this, let's implement the following policy on the many-to-many relationship example above: When someone wants to remove a product that is still referenced by an order (via order_items), we disallow it. If someone removes an order, the order items are removed as well. CREATE TABLE products ( product_no integer PRIMARY KEY, name text, price numeric ); CREATE TABLE orders ( order_id integer PRIMARY KEY, shipping_address text, ... ); CREATE TABLE order_items ( product_no integer REFERENCES products ON DELETE RESTRICT, order_id integer REFERENCES orders ON DELETE CASCADE, quantity integer, PRIMARY KEY (product_no, order_id) ); Restricting and cascading deletes are the two most common options. RESTRICT can also be written as NO ACTION and it's also the default if you do not specify anything. There are two other options for what should happen with the foreign key columns when a primary key is deleted: SET NULL and SET DEFAULT. Note that these do not excuse you from observing any constraints. For example, if an action specifies SET DEFAULT but the default value would not satisfy the foreign key, the deletion of the primary key will fail. Analogous to ON DELETE there is also ON UPDATE which is invoked when a primary key is changed (updated). The possible actions are the same. More information about updating and deleting data is in . Finally, we should mention that a foreign key must reference columns that are either a primary key or form a unique constraint. If the foreign key references a unique constraint, there are some additional possibilities regarding how null values are matched. These are explained in the reference documentation for . This section needs to be rethought. Some of the information should go into the following chapters. Let's create two tables. The capitals table contains state capitals which are also cities. Naturally, the capitals table should inherit from cities. CREATE TABLE cities ( name text, population float, altitude int -- (in ft) ); CREATE TABLE capitals ( state char(2) ) INHERITS (cities); In this case, a row of capitals inherits all attributes (name, population, and altitude) from its parent, cities. The type of the attribute name is text, a native PostgreSQL type for variable length ASCII strings. The type of the attribute population is float, a native PostgreSQL type for double precision floating-point numbers. State capitals have an extra attribute, state, that shows their state. In PostgreSQL, a table can inherit from zero or more other tables, and a query can reference either all rows of a table or all rows of a table plus all of its descendants. The inheritance hierarchy is actually a directed acyclic graph. For example, the following query finds the names of all cities, including state capitals, that are located at an altitude over 500ft: SELECT name, altitude FROM cities WHERE altitude > 500; which returns: name | altitude -----------+---------- Las Vegas | 2174 Mariposa | 1953 Madison | 845 On the other hand, the following query finds all the cities that are not state capitals and are situated at an altitude over 500ft: SELECT name, altitude FROM ONLY cities WHERE altitude > 500; name | altitude -----------+---------- Las Vegas | 2174 Mariposa | 1953 Here the ONLY before cities indicates that the query should be run over only cities and not tables below cities in the inheritance hierarchy. Many of the commands that we have already discussed -- SELECT, UPDATE and DELETE -- support this ONLY notation. In some cases you may wish to know which table a particular tuple originated from. There is a system column called TABLEOID in each table which can tell you the originating table: SELECT c.tableoid, c.name, c.altitude FROM cities c WHERE c.altitude > 500; which returns: tableoid | name | altitude ----------+-----------+---------- 139793 | Las Vegas | 2174 139793 | Mariposa | 1953 139798 | Madison | 845 (If you try to reproduce this example, you will probably get different numeric OIDs.) By doing a join with pg_class you can see the actual table names: SELECT p.relname, c.name, c.altitude FROM cities c, pg_class p WHERE c.altitude > 500 and c.tableoid = p.oid; which returns: relname | name | altitude ----------+-----------+---------- cities | Las Vegas | 2174 cities | Mariposa | 1953 capitals | Madison | 845 In previous versions of PostgreSQL, the default was not to get access to child tables. This was found to be error prone and is also in violation of the SQL standard. Under the old syntax, to get the sub-tables you append * to the table name. For example SELECT * from cities*; You can still explicitly specify scanning child tables by appending *, as well as explicitly specify not scanning child tables by writing ONLY. But beginning in version 7.1, the default behavior for an undecorated table name is to scan its child tables too, whereas before the default was not to do so. To get the old default behavior, set the configuration option SQL_Inheritance to off, e.g., SET SQL_Inheritance TO OFF; or add a line in your postgresql.conf file. A limitation of the inheritance feature is that indexes (including unique constraints) and foreign key constraints only apply to single tables, not to their inheritance children. Thus, in the above example, specifying that another table's column REFERENCES cities(name) would allow the other table to contain city names but not capital names. This deficiency will probably be fixed in some future release. When you create a table and you realize that you made a mistake, or the requirements of the application changed, then you can drop the table and create it again. But this is not a convenient option if the table is already filled with data, or if the table is referenced by other database objects (for instance a foreign key constraint). Therefore PostgreSQL provides a family of commands to make modifications on existing tables. You can Add columns, Remove columns, Add constraints, Remove constraints, Change default values, Rename columns, Rename tables. All these actions are performed using the ALTER TABLE command. To add a column, use this command: ALTER TABLE products ADD COLUMN description text; The new column will initially be filled with null values in the existing rows of the table. You can also define a constraint on the column at the same time, using the usual syntax: ALTER TABLE products ADD COLUMN description text CHECK (description <> ''); A new column cannot have a not-null constraint since the column initially has to contain null values. But you can add a not-null constraint later. Also, you cannot define a default value on a new column. According to the SQL standard, this would have to fill the new columns in the existing rows with the default value, which is not implemented yet. But you can adjust the column default later on. To remove a column, use this command: ALTER TABLE products DROP COLUMN description; To add a constraint, the table constraint syntax is used. For example: ALTER TABLE products ADD CHECK (name <> ''); ALTER TABLE products ADD CONSTRAINT some_name UNIQUE (product_no); ALTER TABLE products ADD FOREIGN KEY (product_group_id) REFERENCES product_groups; To add a not-null constraint, which cannot be written as a table constraint, use this syntax: ALTER TABLE products ALTER COLUMN product_no SET NOT NULL; The constraint will be checked immediately, so the table data must satisfy the constraint before it can be added. To remove a constraint you need to know its name. If you gave it a name then that's easy. Otherwise the system assigned a generated name, which you need to find out. The psql command \d tablename can be helpful here; other interfaces might also provide a way to inspect table details. Then the command is: ALTER TABLE products DROP CONSTRAINT some_name; This works the same for all constraint types except not-null constraints. To drop a not null constraint use ALTER TABLE products ALTER COLUMN product_no DROP NOT NULL; (Recall that not-null constraints do not have names.) To set a new default for a column, use a command like this: ALTER TABLE products ALTER COLUMN price SET DEFAULT 7.77; To remove any default value, use ALTER TABLE products ALTER COLUMN price DROP DEFAULT; This is equivalent to setting the default to null, at least in PostgreSQL. As a consequence, it is not an error to drop a default where one hadn't been defined, because the default is implicitly the null value. To rename a column: ALTER TABLE products RENAME COLUMN product_no TO product_number; To rename a table: ALTER TABLE products RENAME TO items; When you create a database object, you become its owner. By default, only the owner of an object can do anything with the object. In order to allow other users to use it, privileges must be granted. (There are also users that have the superuser privilege. Those users can always access any object.) To change the owner of a table, index, sequence, or view, use the ALTER TABLE command. There are several different privileges: SELECT, INSERT, UPDATE, DELETE, RULE, REFERENCES, TRIGGER, CREATE, TEMPORARY, EXECUTE, USAGE, and ALL PRIVILEGES. For complete information on the different types of privileges supported by PostgreSQL, refer to the GRANT reference page. The following sections and chapters will also show you how those privileges are used. The right to modify or destroy an object is always the privilege of the owner only. To assign privileges, the GRANT command is used. So, if joe is an existing user, and accounts is an existing table, the privilege to update the table can be granted with GRANT UPDATE ON accounts TO joe; The user executing this command must be the owner of the table. To grant a privilege to a group, use GRANT SELECT ON accounts TO GROUP staff; The special user name PUBLIC can be used to grant a privilege to every user on the system. Writing ALL in place of a specific privilege specifies that all privileges will be granted. To revoke a privilege, use the fittingly named REVOKE command: REVOKE ALL ON accounts FROM PUBLIC; The special privileges of the table owner (i.e., the right to do DROP, GRANT, REVOKE, etc.) are always implicit in being the owner, and cannot be granted or revoked. But the table owner can choose to revoke his own ordinary privileges, for example to make a table read-only for himself as well as others. schemas namespaces A PostgreSQL database cluster contains one or more named databases. Users and groups of users are shared across the entire cluster, but no other data is shared across databases. Any given client connection to the server can access only the data in a single database, the one specified in the connection request. Users of a cluster do not necessarily have the privilege to access every database in the cluster. Sharing of user names means that there cannot be different users named, say, joe in two databases in the same cluster; but the system can be configured to allow joe access to only some of the databases. A database contains one or more named schemas, which in turn contain tables. Schemas also contain other kinds of named objects, including data types, functions, and operators. The same object name can be used in different schemas without conflict; for example, both schema1 and myschema may contain tables named mytable. Unlike databases, schemas are not rigidly separated: a user may access objects in any of the schemas in the database he is connected to, if he has privileges to do so. There are several reasons why one might want to use schemas: To allow many users to use one database without interfering with each other. To organize database objects into logical groups to make them more manageable. Third-party applications can be put into separate schemas so they cannot collide with the names of other objects. Schemas are analogous to directories at the operating system level, except that schemas cannot be nested. To create a separate schema, use the command CREATE SCHEMA. Give the schema a name of your choice. For example: CREATE SCHEMA myschema; qualified names names qualified To create or access objects in a schema, write a qualified name consisting of the schema name and table name separated by a dot: schema.table Actually, the even more general syntax database.schema.table can be used too, but at present this is just for pro-forma compliance with the SQL standard; if you write a database name it must be the same as the database you are connected to. So to create a table in the new schema, use CREATE TABLE myschema.mytable ( ... ); This works anywhere a table name is expected, including the table modification commands and the data access commands discussed in the following chapters. To drop a schema if it's empty (all objects in it have been dropped), use DROP SCHEMA myschema; To drop a schema including all contained objects, use DROP SCHEMA myschema CASCADE; See for a description of the general mechanism behind this. Often you will want to create a schema owned by someone else (since this is one of the ways to restrict the activities of your users to well-defined namespaces). The syntax for that is: CREATE SCHEMA schemaname AUTHORIZATION username; You can even omit the schema name, in which case the schema name will be the same as the user name. See for how this can be useful. Schema names beginning with pg_ are reserved for system purposes and may not be created by users. In the previous sections we created tables without specifying any schema names. By default, such tables (and other objects) are automatically put into a schema named public. Every new database contains such a schema. Thus, the following are equivalent: CREATE TABLE products ( ... ); and CREATE TABLE public.products ( ... ); search path unqualified names names unqualified Qualified names are tedious to write, and it's often best not to wire a particular schema name into applications anyway. Therefore tables are often referred to by unqualified names, which consist of just the table name. The system determines which table is meant by following a search path, which is a list of schemas to look in. The first matching table in the search path is taken to be the one wanted. If there is no match in the search path, an error is reported, even if matching table names exist in other schemas in the database. The first schema named in the search path is called the current schema. Aside from being the first schema searched, it is also the schema in which new tables will be created if the CREATE TABLE command does not specify a schema name. To show the current search path, use the following command: SHOW search_path; In the default setup this returns: search_path -------------- $user,public The first element specifies that a schema with the same name as the current user is to be searched. Since no such schema exists yet, this entry is ignored. The second element refers to the public schema that we have seen already. The first schema in the search path that exists is the default location for creating new objects. That is the reason that by default objects are created in the public schema. When objects are referenced in any other context without schema qualification (table modification, data modification, or query commands) the search path is traversed until a matching object is found. Therefore, in the default configuration, any unqualified access again can only refer to the public schema. To put our new schema in the path, we use SET search_path TO myschema,public; (We omit the $user here because we have no immediate need for it.) And then we can access the table without schema qualification: DROP TABLE mytable; Also, since myschema is the first element in the path, new objects would by default be created in it. We could also have written SET search_path TO myschema; Then we no longer have access to the public schema without explicit qualification. There is nothing special about the public schema except that it exists by default. It can be dropped, too. See also for other ways to access the schema search path. The search path works in the same way for data type names, function names, and operator names as it does for table names. Data type and function names can be qualified in exactly the same way as table names. If you need to write a qualified operator name in an expression, there is a special provision: you must write OPERATOR(schema.operator) This is needed to avoid syntactic ambiguity. An example is SELECT 3 OPERATOR(pg_catalog.+) 4; In practice one usually relies on the search path for operators, so as not to have to write anything so ugly as that. By default, users cannot see the objects in schemas they do not own. To allow that, the owner of the schema needs to grant the USAGE privilege on the schema. To allow users to make use of the objects in the schema, additional privileges may need to be granted, as appropriate for the object. A user can also be allowed to create objects in someone else's schema. To allow that, the CREATE privilege on the schema needs to be granted. Note that by default, everyone has the CREATE privilege on the schema public. This allows all users that manage to connect to a given database to create objects there. If you do not want to allow that, you can revoke that privilege: REVOKE CREATE ON SCHEMA public FROM PUBLIC; (The first public is the schema, the second public means every user. In the first sense it is an identifier, in the second sense it is a reserved word, hence the different capitalization; recall the guidelines from .) In addition to public and user-created schemas, each database contains a pg_catalog schema, which contains the system tables and all the built-in data types, functions, and operators. pg_catalog is always effectively part of the search path. If it is not named explicitly in the path then it is implicitly searched before searching the path's schemas. This ensures that built-in names will always be findable. However, you may explicitly place pg_catalog at the end of your search path if you prefer to have user-defined names override built-in names. In PostgreSQL versions before 7.3, table names beginning with pg_ were reserved. This is no longer true: you may create such a table name if you wish, in any non-system schema. However, it's best to continue to avoid such names, to ensure that you won't suffer a conflict if some future version defines a system table named the same as your table. (With the default search path, an unqualified reference to your table name would be resolved as the system table instead.) System tables will continue to follow the convention of having names beginning with pg_, so that they will not conflict with unqualified user-table names so long as users avoid the pg_ prefix. Schemas can be used to organize your data in many ways. There are a few usage patterns that are recommended and are easily supported by the default configuration: If you do not create any schemas then all users access the public schema implicitly. This simulates the situation where schemas are not available at all. This setup is mainly recommended when there is only a single user or a few cooperating users in a database. This setup also allows smooth transition from the non-schema-aware world. You can create a schema for each user with the same name as that user. Recall that the default search path starts with $user, which resolves to the user name. Therefore, if each user has a separate schema, they access their own schemas by default. If you use this setup then you might also want to revoke access to the public schema (or drop it altogether), so users are truly constrained to their own schemas. To install shared applications (tables to be used by everyone, additional functions provided by third parties, etc.), put them into separate schemas. Remember to grant appropriate privileges to allow the other users to access them. Users can then refer to these additional objects by qualifying the names with a schema name, or they can put the additional schemas into their path, as they choose. In the SQL standard, the notion of objects in the same schema being owned by different users does not exist. Moreover, some implementations do not allow you to create schemas that have a different name than their owner. In fact, the concepts of schema and user are nearly equivalent in a database system that implements only the basic schema support specified in the standard. Therefore, many users consider qualified names to really consist of username.tablename. This is how PostgreSQL will effectively behave if you create a per-user schema for every user. Also, there is no concept of a public schema in the SQL standard. For maximum conformance to the standard, you should not use (perhaps even remove) the public schema. Of course, some SQL database systems might not implement schemas at all, or provide namespace support by allowing (possibly limited) cross-database access. If you need to work with those systems, then maximum portability would be achieved by not using schemas at all. Tables are the central objects in a relational database structure, because they hold your data. But they are not the only objects that exist in a database. Many other kinds of objects can be created to make the use and management of the data more efficient or convenient. They are not discussed in this chapter, but we give you a list here so that you are aware of what is possible. Views Functions, operators, data types, domains Triggers and rewrite rules When you create complex database structures involving many tables with foreign key constraints, views, triggers, functions, etc. you will implicitly create a net of dependencies between the objects. For instance, a table with a foreign key constraint depends on the table it references. To ensure the integrity of the entire database structure, PostgreSQL makes sure that you cannot drop objects that other objects still depend on. For example, attempting to drop the products table we had considered in , with the orders table depending on it, would result in an error message such as this: DROP TABLE products; NOTICE: constraint $1 on table orders depends on table products ERROR: Cannot drop table products because other objects depend on it Use DROP ... CASCADE to drop the dependent objects too The error message contains a useful hint: if you do not want to bother deleting all the dependent objects individually, you can run DROP TABLE products CASCADE; and all the dependent objects will be removed. In this case, it doesn't remove the orders table, it only removes the foreign key constraint. (If you want to check what DROP ... CASCADE will do, run DROP without CASCADE and read the NOTICE messages.) All drop commands in PostgreSQL support specifying CASCADE. Of course, the nature of the possible dependencies varies with the type of the object. You can also write RESTRICT instead of CASCADE to get the default behavior which is to restrict drops of objects that other objects depend on. According to the SQL standard, specifying either RESTRICT or CASCADE is required. No database system actually implements it that way, but whether the default behavior is RESTRICT or CASCADE varies across systems. Foreign key constraint dependencies and serial column dependencies from PostgreSQL versions prior to 7.3 are not maintained or created during the upgrade process. All other dependency types will be properly created during an upgrade.