Retrieving data from one table
Retrieval with SQL
In SQL, to retrieve data stored in our tables, we use the SELECT statement. The result of this statement is always in the form of a table that we can view with our database client software or use with programming languages to build dynamic web pages or desktop applications. While the result may look like a table, it is not stored in the database like the named tables are. The result of a SELECT statement can also be used as part of another statement.
This reference contains a complete description of the Structured Query Language (SQL) used to manage information in an Oracle Database. Oracle SQL is a superset of the American National Standards Institute (ANSI) and the International Organization for Standardization (ISO) SQL:1999 standard. This Preface contains these topics: Audience.
Basic syntax of SELECT
statement
The basic syntax consists of four clauses as shown in the figure below. While SQL is not case sensitive, by convention many database developers use uppercase for keywords to improve readability.
- If any of the databases is on another server on another machine, than make sure the Database is in the Linked Server. Then you can access the table or view on that database via: SELECT. FROM AnotherServerName.DB.dbo.Table Here is another way that does not requires typing the database name.
- For databases using the vCore-based model, this column is NULL. Cpulimit: decimal (5,2) Number of vCores for this database during this interval. For databases using the DTU-based model, this column is NULL. Avginstancecpupercent: decimal (5,2) Average CPU usage for the SQL Server instance hosting the database, as measured by the operating.
Of the four clauses, only the first two are required. The two shown in square brackets are optional. When you start learning to build queries, it is helpful to follow a specific step-by-step sequence, look at the data after each modification to the query, and be sure that you understand the results at each step. This iterative refinement will allow you to hone in on just the right SQL statement to retrieve the desired information. Below is a summary of the clauses.
- The
SELECT
clause allows us to specify a comma-separated list of attribute names corresponding to the columns that are to be retrieved. You can use an asterisk character, *, to retrieve all the columns. - In queries where all the data is found in one table, the
FROM
clause is where we specify the name of the table from which to retrieve rows. In other articles we will use it to retrieve rows from multiple tables. - The
WHERE
clause is used to constrain which rows to retrieve. We do this by specifying a boolean predicate that compares the values of table columns to literal values or to other columns. - The
ORDER BY
clause gives us a way to order the display of the rows in the result of the statement.
The example of the next section provides more information on how to retrieve information using this
SELECT
statement.SQL Example: customers in a specified zip code
We’ll build a list of customers who live in a specific zip code area, showing their first and last names and phone numbers and listing them in alphabetical order by last name. A company might want to do this to initiate a marketing campaign to customers in this area. In this example, we’ll use zip code 90840. Listed below are the refinement steps we take to arrive at the statement that will retrieve what we need.
- Start by retrieving all of the relevant data; in this case, that is all data of every customer. In our database all of this is stored in only one table, so that table is specified in the FROM clause. Since we want to retrieve all columns from this table, instead of naming each of them individually, we can use the abbreviation symbol * to indicate that all columns are to be retrieved. That completes the recipe for our SQL statement which is shown below; note, we have no use for the two optional clauses in this initial statement. In the same figure below, you will also find the result of this query executed on a tiny database. While the result of a query is known as a result set, the result is not in fact always a set. The result could be a multiset, that is, a collection of rows that can have duplicate rows.
- Clearly we need to a refinement step as the query retrieves all customers while we are only interested in customers who live in zip code 90840. We need to specify in the statement that the only rows to retrieve from the database are those that meet this criteria. Such qualifying criteria is specified in the
WHERE
clause using boolean expressions. Our first statement is thus refined as shown in the figure below. Note that SQL syntax requires the use of single quotes around literal strings like'90840'
. While not illustrated in this example and unlike SQL keywords, literal strings and strings stored in the database are case sensitive; thus,'Long Beach'
is a different string than'long beach'
. - We need just a couple of more refinements. While we now are retrieving only the customers we desire, we are also retrieving every column from the table yet, not all are needed. We need a way to pick the attributes (columns) we want. This is done by listing them in the
SELECT
clause, each column name separated by a comma. The figure below shows this refinement and its corresponding result set. Note that changing the order of the columns (like showing the last name first) does not change the meaning of the results. - For practical purposes our last refinement is all that we need. To make the result set more appealing to a human, we may want to order the result set. Imagine having a result set that is 100 times of what we are showing here! It would be better to display the result sorted alphabetically by the name of the customer. In SQL, you can use the
ORDER BY
clause to specify the order in which to retrieve the results. Once again, this ordering does not change the meaning of the results; the result set does not change, all it changes is the order in which the rows are displayed. This final refinement and its result are shown below. The keywordASC
is used to order the rows in ascending values, which is the default ordering so the keyword is not necessary and is shown here for completeness. To order rows in descending values, use the keywordDESC
. In the statement above, rows are first ordered in ascending value of the last name and in case of ties (two or more customers with the same name), then the rows are ordered in ascending value of the first name.
Retrieval with relational algebra
SQL is a declarative language. As such, SQL is used to declare what is to be retrieved from the database. In our SQL statement above, we did not specify how to retrieve the result. In an imperative language, we do specify the steps to take to solve a problem, such as how to retrieve a result from a database. Thus, it is the responsibility of the database system to determine how to retrieve what is declared in SQL. In relational database systems, this is commonly done by translating SQL into Relational Algebra.
Like all algebras, RA applies operators to operands to produce results of the same type as the operands. RA operands are relations and thus the results are also relations. Furthermore, like all algebras, the results of operators can be used as operands in building more complex expressions. We introduce two of the RA operators following the example and refinements above for SQL.
RA operators: σ and π
To retrieve a single relation in RA, we only need to use its name. The common notation in the relational model is to use uppercase letters for relation scheme (R, S, T, U, etc) and lowercase letters for relations (r, s, t, u, etc). Thus, the simplest RA expression is to retrieve all columns and every row of a relation is just the name of the relation: r
The two RA operators introduced here are σ, the select operator, and π, the project operator.
- The select (RA) operator specified by the symbol σ picks tuples that satisfy a predicate; thus, serving a similar purpose as the SQL
WHERE
clause. This RA select operator σ is unary taking a single relation or RA expression as its operand. The predicate, θ, to specify which tuples are required is written as a subscript of the operator, giving the syntax ofσθe
, where e is a RA expression.The scheme of the result ofσθr
is R—the same scheme we started with—since the entire tuple is selected, as long as the tuple satisfies the predicate. The result of this operation includes all tuples of relation r that satisfy the predicate θ—that is, θ evaluates to true. - The project (RA) operator specified by the symbol π picks attributes, confusingly like the SQL
SELECT
clause. It is also a unary operator that takes a single relation or expression as its operand and the attributes to retrieve are specified as a a subscheme, X (subset of its operand). The syntax isπXe
where, as before, e is a RA expression. Following are additional properties of the project operator.- For X to be a subscheme of R, it must be a subset of the attributes in R that preserves the assignment rule from R (that is, each attribute of X must have the same domain as its corresponding attribute in R).
- The scheme of the result of πXr is X. The tuples resulting from this operation are tuples of the original relation, r, but cut down to the attributes contained in X.
- If X is a super key of r, then there will be the same number of tuples in the result as there were to begin with in r. If X is not a super key of r, then any duplicate (non-distinct) tuples are eliminated from the result, ensuring the result is always a set. This is unlike SQL where the result of a
SELECT
statement with aWHERE
clause is a superset.
- As with other algebras, we can use function composition by applying the project operator to the result of the select operator from the previous set to get:
πXσθr
RA Example: customers in a specified zip code
Given the above RA syntax, we can now use RA to create expressions that match the SQL statements from above which retrieve the customers who live in zip code 90840.
- The first step is to retrieve all customers. This is done by a RA expression that consists of just the name of the relation, thus the RA expression
customers
is the equivalent of the first SQL statement above. Its scheme is the same as the Customers scheme. - To retrieve the equivalent result set as the SQL statement in refinement #2, we apply the σ operator to the result set of our previous expression: Again, the scheme of the result set is the same as the Customers scheme.
- Now, applying function composition here, we can retrieve just the columns we desire from the result set of the previous expression to get the RA expression that retrieves the equivalent result set as the SQL statement in refinement #3:
- Note that, in RA the results of expressions are strictly sets of tuples, thus, there is no way to specify the order of tuples in a result set. This is unlike SQL and its
ORDER BY
caluse.
Django gives you two ways of performing raw SQL queries: you can use
Manager.raw()
to perform raw queries and return model instances, oryou can avoid the model layer entirely and execute custom SQL directly.Explore the ORM before using raw SQL!
The Django ORM provides many tools to express queries without writing rawSQL. For example:
- The QuerySet API is extensive.
- You can
annotate
and aggregate using many built-in database functions. Beyond those, you can createcustom query expressions.
Before using raw SQL, explore the ORM. Ask ondjango-users or the #django IRC channel to see if the ORM supports youruse case.
Warning
You should be very careful whenever you write raw SQL. Every time you useit, you should properly escape any parameters that the user can controlby using
params
in order to protect against SQL injection attacks.Please read more about SQL injection protection.Performing raw queries¶
The
raw()
manager method can be used to perform raw SQL queries thatreturn model instances:Manager.
raw
(raw_query, params=None, translations=None)¶
This method takes a raw SQL query, executes it, and returns a
django.db.models.query.RawQuerySet
instance. This RawQuerySet
instancecan be iterated over like a normal QuerySet
toprovide object instances.This is best illustrated with an example. Suppose you have the following model:
You could then execute custom SQL like so:
This example isn’t very exciting – it’s exactly the same as running
Person.objects.all()
. However, raw()
has a bunch of other options thatmake it very powerful.Model table names
Where did the name of the
Person
table come from in that example?By default, Django figures out a database table name by joining themodel’s “app label” – the name you used in
manage.pystartapp
– tothe model’s class name, with an underscore between them. In the examplewe’ve assumed that the Person
model lives in an app named myapp
,so its table would be myapp_person
.For more details check out the documentation for the
db_table
option, which also lets you manually set thedatabase table name.Warning
Garagesale 7 0 15 – create outstanding ebay auctions. No checking is done on the SQL statement that is passed in to
.raw()
.Django expects that the statement will return a set of rows from thedatabase, but does nothing to enforce that. If the query does notreturn rows, a (possibly cryptic) error will result.Warning
If you are performing queries on MySQL, note that MySQL’s silent type coercionmay cause unexpected results when mixing types. If you query on a stringtype column, but with an integer value, MySQL will coerce the types of all valuesin the table to an integer before performing the comparison. For example, if yourtable contains the values
'abc'
, 'def'
and you query for WHEREmycolumn=0
,both rows will match. To prevent this, perform the correct typecastingbefore using the value in a query.Mapping query fields to model fields¶
raw()
automatically maps fields in the query to fields on the model.The order of fields in your query doesn’t matter. In other words, bothof the following queries work identically:
Matching is done by name. This means that you can use SQL’s
AS
clauses tomap fields in the query to model fields. So if you had some other table thathad Person
data in it, you could easily map it into Person
instances:As long as the names match, the model instances will be created correctly.
Sql Database Query Tool
Alternatively, you can map fields in the query to model fields using the
translations
argument to raw()
. This is a dictionary mapping names offields in the query to names of fields on the model. For example, the abovequery could also be written:Index lookups¶
raw()
supports indexing, so if you need only the first result you canwrite:However, the indexing and slicing are not performed at the database level. Ifyou have a large number of
Person
objects in your database, it is moreefficient to limit the query at the SQL level:Deferring model fields¶
Fields may also be left out:
The
Person
objects returned by this query will be deferred model instances(see defer()
). This means that thefields that are omitted from the query will be loaded on demand. For example:From outward appearances, this looks like the query has retrieved boththe first name and last name. However, this example actually issued 3queries. Only the first names were retrieved by the raw() query – thelast names were both retrieved on demand when they were printed. Medico 2 44 – professional karaoke software windows 10.
There is only one field that you can’t leave out - the primary keyfield. Django uses the primary key to identify model instances, so itmust always be included in a raw query. A
FieldDoesNotExist
exception will be raised ifyou forget to include the primary key.Db Solo 5 2 – Query Sql Databases Query
Adding annotations¶
You can also execute queries containing fields that aren’t defined on themodel. For example, we could use PostgreSQL’s age() function to get a listof people with their ages calculated by the database:
You can often avoid using raw SQL to compute annotations by instead using aFunc() expression.
Passing parameters into raw()
¶
If you need to perform parameterized queries, you can use the
params
argument to raw()
:params
is a list or dictionary of parameters. You’ll use %s
placeholders in the query string for a list, or %(key)s
placeholders for a dictionary (where key
is replaced by adictionary key), regardless of your database engine. Such placeholders will bereplaced with parameters from the params
argument.Note
Dictionary params are not supported with the SQLite backend; withthis backend, you must pass parameters as a list.
Warning
Do not use string formatting on raw queries or quote placeholders in yourSQL strings!
It’s tempting to write the above query as:
You might also think you should write your query like this (with quotesaround
%s
):Cosmos Db Query Sql
Don’t make either of these mistakes.
As discussed in SQL injection protection, using the
params
argument and leaving the placeholders unquoted protects you from SQLinjection attacks, a common exploit where attackers inject arbitrarySQL into your database. If you use string interpolation or quote theplaceholder, you’re at risk for SQL injection.Executing custom SQL directly¶
Sometimes even
Manager.raw()
isn’t quite enough: you might need toperform queries that don’t map cleanly to models, or directly executeUPDATE
, INSERT
, or DELETE
queries.In these cases, you can always access the database directly, routing aroundthe model layer entirely.
The object
django.db.connection
represents the default databaseconnection. To use the database connection, call connection.cursor()
toget a cursor object. Then, call cursor.execute(sql,[params])
to executethe SQL and cursor.fetchone()
or cursor.fetchall()
to return theresulting rows.For example:
To protect against SQL injection, you must not include quotes around the
%s
placeholders in the SQL string.Note that if you want to include literal percent signs in the query, you have todouble them in the case you are passing parameters:
If you are using more than one database, you canuse
django.db.connections
to obtain the connection (and cursor) for aspecific database. django.db.connections
is a dictionary-likeobject that allows you to retrieve a specific connection using itsalias:By default, the Python DB API will return results without their field names,which means you end up with a
list
of values, rather than a dict
. At asmall performance and memory cost, you can return results as a dict
byusing something like this:Another option is to use
collections.namedtuple()
from the Pythonstandard library. A namedtuple
is a tuple-like object that has fieldsaccessible by attribute lookup; it’s also indexable and iterable. Results areimmutable and accessible by field names or indices, which might be useful:Here is an example of the difference between the three:
Connections and cursors¶
Wattagio 1 7 2 torrent.
connection
and cursor
mostly implement the standard Python DB-APIdescribed in PEP 249 — except when it comes to transaction handling.If you’re not familiar with the Python DB-API, note that the SQL statement in
cursor.execute()
uses placeholders, '%s'
, rather than addingparameters directly within the SQL. If you use this technique, the underlyingdatabase library will automatically escape your parameters as necessary.Also note that Django expects the
'%s'
placeholder, not the '?'
placeholder, which is used by the SQLite Python bindings. This is for the sakeof consistency and sanity.Using a cursor as a context manager:
is equivalent to:
Calling stored procedures¶
CursorWrapper.
callproc
(procname, params=None, kparams=None)¶Calls a database stored procedure with the given name. A sequence(
params
) or dictionary (kparams
) of input parameters may beprovided. Most databases don’t support kparams
. Of Django’s built-inbackends, only Oracle supports it.![Db solo 5 2 – query sql databases query Db solo 5 2 – query sql databases query](https://www.dbsolo.com/sshots/query_window.jpg)
For example, given this stored procedure in an Oracle database:
Sql Db Download
This will call it: