Select (SQL)

From Wikipedia, the free encyclopedia

This is an old revision of this page, as edited by 151.62.240.221 (talk) at 15:26, 22 November 2019 (→‎Window function support by RDBMS vendors: Both MySQL+MariaDB added support. HSQLDB has the weakest support nowadays, since it provides only ROW_NUMBER over()). The present address (URL) is a permanent link to this revision, which may differ significantly from the current revision.

The SQL SELECT statement returns a result set of records from one or more tables.[1][2]

A SELECT statement retrieves zero or more rows from one or more database tables or database views. In most applications, SELECT is the most commonly used data manipulation language (DML) command. As SQL is a declarative programming language, SELECT queries specify a result set, but do not specify how to calculate it. The database translates the query into a "query plan" which may vary between executions, database versions and database software. This functionality is called the "query optimizer" as it is responsible for finding the best possible execution plan for the query, within applicable constraints.

The SELECT statement has many optional clauses:

  • WHERE specifies which rows to retrieve.
  • GROUP BY groups rows sharing a property so that an aggregate function can be applied to each group.
  • HAVING selects among the groups defined by the GROUP BY clause.
  • ORDER BY specifies an order in which to return the rows.
  • AS provides an alias which can be used to temporarily rename tables or columns.

Examples

Table "T" Query Result
C1 C2
1 a
2 b
SELECT * FROM T;
C1 C2
1 a
2 b
C1 C2
1 a
2 b
SELECT C1 FROM T;
C1
1
2
C1 C2
1 a
2 b
SELECT * FROM T WHERE C1 = 1;
C1 C2
1 a
C1 C2
1 a
2 b
SELECT * FROM T ORDER BY C1 DESC;
C1 C2
2 b
1 a

Given a table T, the query SELECT * FROM T will result in all the elements of all the rows of the table being shown.

With the same table, the query SELECT C1 FROM T will result in the elements from the column C1 of all the rows of the table being shown. This is similar to a projection in Relational algebra, except that in the general case, the result may contain duplicate rows. This is also known as a Vertical Partition in some database terms, restricting query output to view only specified fields or columns.

With the same table, the query SELECT * FROM T WHERE C1 = 1 will result in all the elements of all the rows where the value of column C1 is '1' being shown — in Relational algebra terms, a selection will be performed, because of the WHERE clause. This is also known as a Horizontal Partition, restricting rows output by a query according to specified conditions.

With more than one table, the result set will be every combination of rows. So if two tables are T1 and T2, SELECT * FROM T1, T2 will result in every combination of T1 rows with every T2 rows. E.g., if T1 has 3 rows and T2 has 5 rows, then 15 rows will result.

The SELECT clause specifies a list of properties (columns) by name, or the wildcard character (“*”) to mean “all properties”.

Limiting result rows

Often it is convenient to indicate a maximum number of rows that are returned. This can be used for testing or to prevent consuming excessive resources if the query returns more information than expected. The approach to do this often varies per vendor.

In ISO SQL:2003, result sets may be limited by using

  • cursors, or
  • By introducing SQL window function to the SELECT-statement

ISO SQL:2008 introduced the FETCH FIRST clause.

According to PostgreSQL v.9 documentation, an SQL Window function performs a calculation across a set of table rows that are somehow related to the current row, in a way similar to aggregate functions. [3] The name recalls signal processing window functions. A window function call always contains an OVER clause.

ROW_NUMBER() window function

ROW_NUMBER() OVER may be used for a simple table on the returned rows, e.g. to return no more than ten rows:

SELECT * FROM
( SELECT
    ROW_NUMBER() OVER (ORDER BY sort_key ASC) AS row_number,
    columns
  FROM tablename
) AS foo
WHERE row_number <= 11

ROW_NUMBER can be non-deterministic: if sort_key is not unique, each time you run the query it is possible to get different row numbers assigned to any rows where sort_key is the same. When sort_key is unique, each row will always get a unique row number.

RANK() window function

The RANK() OVER window function acts like ROW_NUMBER, but may return more or less than n rows in case of tie conditions, e.g. to return the top-10 youngest persons:

SELECT * FROM (
  SELECT
    RANK() OVER (ORDER BY age ASC) AS ranking,
    person_id,
    person_name,
    age
  FROM person
) AS foo
WHERE ranking <= 10

The above code could return more than ten rows, e.g. if there are two people of the same age, it could return eleven rows.

FETCH FIRST clause

Since ISO SQL:2008 results limits can be specified as in the following example using the FETCH FIRST clause.

SELECT * FROM T FETCH FIRST 10 ROWS ONLY

This clause currently is supported by CA DATACOM/DB 11, IBM DB2, SAP SQL Anywhere, PostgreSQL, EffiProz, H2, HSQLDB version 2.0, Oracle 12c and Mimer SQL.

Microsoft SQL Server 2008 and higher supports FETCH FIRST, but it is considered part of the ORDER BY clause. The ORDER BY, OFFSET, and FETCH FIRST clauses are all required for this usage.

SELECT * FROM T ORDER BY acolumn DESC OFFSET 0 ROWS FETCH FIRST 10 ROWS ONLY

Non-standard syntax

Some DBMSs offer non-standard syntax either instead of or in addition to SQL standard syntax. Below, variants of the simple limit query for different DBMSes are listed:

SET ROWCOUNT 10
SELECT * FROM T
MS SQL Server (This also works on Microsoft SQL Server 6.5 while the Select top 10 * from T does not)
SELECT * FROM T LIMIT 10 OFFSET 20 Netezza, MySQL, SAP SQL Anywhere, PostgreSQL (also supports the standard, since version 8.4), SQLite, HSQLDB, H2, Vertica, Polyhedra, Couchbase Server, Snowflake Computing, OpenLink Virtuoso
SELECT * from T WHERE ROWNUM <= 10 Oracle
SELECT FIRST 10 * from T Ingres
SELECT FIRST 10 * FROM T order by a Informix
SELECT SKIP 20 FIRST 10 * FROM T order by c, d Informix (row numbers are filtered after order by is evaluated. SKIP clause was introduced in a v10.00.xC4 fixpack)
SELECT TOP 10 * FROM T MS SQL Server, SAP ASE, MS Access, SAP IQ, Teradata
SELECT * FROM T SAMPLE 10 Teradata
SELECT TOP 20, 10 * FROM T OpenLink Virtuoso (skips 20, delivers next 10)[4]
SELECT TOP 10 START AT 20 * FROM T SAP SQL Anywhere (also supports the standard, since version 9.0.1)
SELECT FIRST 10 SKIP 20 * FROM T Firebird
SELECT * FROM T ROWS 20 TO 30 Firebird (since version 2.1)
SELECT * FROM T
WHERE ID_T > 10 FETCH FIRST 10 ROWS ONLY
DB2
SELECT * FROM T
WHERE ID_T > 20 FETCH FIRST 10 ROWS ONLY
DB2 (new rows are filtered after comparing with key column of table T)

Rows Pagination

Rows Pagination [5] is an approach used to limit and display only a part of the total data of a query in the database. Instead of showing hundreds or thousands of rows at the same time, the server is requested only one page (a limited set of rows, per example only 10 rows), and the user starts navigating by requesting the next page, and then the next one, and so on. It is very useful, specially in web systems, where there is no dedicated connection between the client and the server, so the client does not have to wait to read and display all the rows of the server.

Data in Pagination approach:

  • {rows} = Number of rows in a page
  • {page_number} = Number of the current page
  • {begin_base_0} = Number of the row - 1 where the page starts = (page_number-1) * rows


Simplest method (but very inefficient):
1) Select all rows from the database
2) Read all rows but send to display only when the row_number of the rows read is between {begin_base_0 + 1} and {begin_base_0 + rows}

Select * 
from {table} 
order by {unique_key}


Other simple method (a little more efficient than read all rows):
1) Select all the rows from the beginning of the table to the last row to display ({begin_base_0 + rows})
2) Read the {begin_base_0 + rows} rows but send to display only when the row_number of the rows read is greater than {begin_base_0}

SQL Dialect
select *
from {table}
order by {unique_key}
FETCH FIRST {begin_base_0 + rows} ROWS ONLY
SQL ANSI 2008
Postgresql
SQL Server 2012
Derby
Oracle 12c
DB2 12
Select *
from {table}
order by {unique_key}
LIMIT {begin_base_0 + rows}
MySQL
SQLite
Select TOP {begin_base_0 + rows} * 
from {table} 
order by {unique_key}
SQL Server 2005
SET ROWCOUNT {begin_base_0 + rows}
Select * 
from {table} 
order by {unique_key}
SET ROWCOUNT 0
Sybase, SQL Server 2000
Select *
    FROM (
        SELECT * 
        FROM {table} 
        ORDER BY {unique_key}
    ) a 
where rownum <= {begin_base_0 + rows}
Oracle 11


Method with positioning:
1) Select only <rows> rows starting from the next row to display ({begin_base_0 + 1})
2) Read and send to display all the rows read from the database

SQL Dialect
Select *
from {table}
order by {unique_key}
OFFSET {begin_base_0} ROWS
FETCH NEXT {rows} ROWS ONLY
SQL ANSI 2008
Postgresql
SQL Server 2012
Derby
Oracle 12c
DB2 12
Select *
from {table}
order by {unique_key}
LIMIT {rows} OFFSET {begin_base_0}
MySQL
MariaDB
Postgresql
SQLite
Select * 
from {table} 
order by {unique_key}
LIMIT {begin_base_0}, {rows}
MySQL
MariaDB
SQLite
select TOP {begin_base_0 + rows}
       *,  _offset=identity(10) 
into #temp
from {table}
ORDER BY {unique_key} 
select * from #temp where _offset > {begin_base_0}
DROP TABLE #temp
Sybase 12.5.3:
SET ROWCOUNT {begin_base_0 + rows}
select *,  _offset=identity(10) 
into #temp
from {table}
ORDER BY {unique_key} 
select * from #temp where _offset > {begin_base_0}
DROP TABLE #temp
SET ROWCOUNT 0
Sybase 12.5.2:
select TOP {rows} * 
from (
      select *, ROW_NUMBER() over (order by {unique_key}) as _offset   
      from {table}
) xx 
where _offset > {begin_base_0}


SQL Server 2005
SET ROWCOUNT {begin_base_0 + rows}
select *,  _offset=identity(int,1,1) 
into #temp
from {table}
ORDER BY {unique-key}
select * from #temp where _offset > {begin_base_0}
DROP TABLE #temp
SET ROWCOUNT 0
SQL Server 2000
SELECT * FROM (
    SELECT rownum-1 as _offset, a.* 
    FROM(
        SELECT * 
        FROM {table} 
        ORDER BY {unique_key}
    ) a 
    WHERE rownum <= {begin_base_0 + cant_regs}
)
WHERE _offset >= {begin_base_0}
Oracle 11


Method with filter (it is more sophisticated but necessary for very big dataset):
1) Select only then <rows> rows with filter:
1.1) First Page: select only the first {rows} rows, depending on the type of database
1.2) Next Page: select only the first {rows} rows, depending on the type of database, where the {unique_key} is greater than {last_val} (the value of the {unique_key} of the last row in the current page)
1.3) Previous Page: sort the data in the reverse order, select only the first {rows} rows, where the {unique_key} is less than {first_val} (the value of the {unique_key} of the first row in the current page), and sort the result in the correct order
2) Read and send to display all the rows read from the database

First Page Next Page Previous Page Dialect
select *
from {table} 
order by {unique_key}
FETCH FIRST {rows} ROWS ONLY
select * 
from {table} 
where {unique_key} > {last_val}
order by {unique_key}
FETCH FIRST {rows} ROWS ONLY
select * 
from (
  Select * 
  from {table} 
  where {unique_key} < {first_val}
  order by {unique_key} DESC
  FETCH FIRST {rows} ROWS ONLY
) a
order by {unique_key}
SQL ANSI 2008
Postgresql
SQL Server 2012
Derby
Oracle 12c
DB2 12
select *
from {table}
order by {unique_key}
LIMIT {rows}
select * 
from {table} 
where {unique_key} > {last_val}
order by {unique_key}
LIMIT {rows}
select * 
from (
  select * 
  from {table} 
  where {unique_key} < {first_val}
  order by {unique_key} DESC
  LIMIT {rows}
) a
order by {unique_key}
MySQL
SQLite
select TOP {rows} * 
from {table} 
order by {unique_key}
select TOP {rows} * 
from {table} 
where {unique_key} > {last_val}
order by {unique_key}
select * 
from (
  select TOP {rows} * 
  from {table} 
  where {unique_key} < {first_val}
  order by {unique_key} DESC
) a
order by {unique_key}
SQL Server 2005
SET ROWCOUNT {rows}
select *
from {table} 
order by {unique_key}
SET ROWCOUNT 0
SET ROWCOUNT {rows}
select *
from {table} 
where {unique_key} > {last_val}
order by {unique_key}
SET ROWCOUNT 0
SET ROWCOUNT {rows}
select *
from (
  select * 
  from {table} 
  where {unique_key} < {first_val}
  order by {unique_key} DESC
) a
order by {unique_key}
SET ROWCOUNT 0
Sybase, SQL Server 2000
select *
from (
    select * 
    from {table} 
    order by {unique_key}
  ) a 
where rownum <= {rows}
select *
from (
  select * 
  from {table} 
  where {unique_key} > {last_val}
  order by {unique_key}
) a 
where rownum <= {rows}
select * 
from (
  select *
  from (
    select * 
    from {table} 
    where {unique_key} < {first_val}
    order by {unique_key} DESC
  ) a1
  where rownum <= {rows}
) a2
order by {unique_key}
Oracle 11


Hierarchical query

Some databases provide specialised syntax for hierarchical data.

A window function in SQL:2003 is an aggregate function applied to a partition of the result set.

For example,

sum(population) OVER( PARTITION BY city )

calculates the sum of the populations of all rows having the same city value as the current row.

Partitions are specified using the OVER clause which modifies the aggregate. Syntax:

<OVER_CLAUSE> :: =
   OVER ( [ PARTITION BY <expr>, ... ]
          [ ORDER BY <expression> ] )

The OVER clause can partition and order the result set. Ordering is used for order-relative functions such as row_number.

Query evaluation ANSI

The processing of a SELECT statement according to ANSI SQL would be the following:[6]

  1. select g.*
    from users u inner join groups g on g.Userid = u.Userid
    where u.LastName = 'Smith'
    and u.FirstName = 'John'
    
  2. the FROM clause is evaluated, a cross join or Cartesian product is produced for the first two tables in the FROM clause resulting in a virtual table as Vtable1
  3. the ON clause is evaluated for vtable1; only records which meet the join condition g.Userid = u.Userid are inserted into Vtable2
  4. If an outer join is specified, records which were dropped from vTable2 are added into VTable 3, for instance if the above query were:
    select u.*
    from users u left join groups g on g.Userid = u.Userid
    where u.LastName = 'Smith'
    and u.FirstName = 'John'
    
    all users who did not belong to any groups would be added back into Vtable3
  5. the WHERE clause is evaluated, in this case only group information for user John Smith would be added to vTable4
  6. the GROUP BY is evaluated; if the above query were:
    select g.GroupName, count(g.*) as NumberOfMembers
    from users u inner join groups g on g.Userid = u.Userid
    group by GroupName
    
    vTable5 would consist of members returned from vTable4 arranged by the grouping, in this case the GroupName
  7. the HAVING clause is evaluated for groups for which the HAVING clause is true and inserted into vTable6. For example:
    select g.GroupName, count(g.*) as NumberOfMembers
    from users u inner join groups g on g.Userid = u.Userid
    group by GroupName
    having count(g.*) > 5
    
  8. the SELECT list is evaluated and returned as Vtable 7
  9. the DISTINCT clause is evaluated; duplicate rows are removed and returned as Vtable 8
  10. the ORDER BY clause is evaluated, ordering the rows and returning VCursor9. This is a cursor and not a table because ANSI defines a cursor as an ordered set of rows (not relational).

Window function support by RDBMS vendors

The implementation of window function features by vendors of relational databases and SQL engines differs wildly. Most databases support at least some flavour of window functions. However, when we take a closer look it becomes clear that most vendors only implement a subset of the standard. Let's take the powerful RANGE clause as an example. Only Oracle, DB2, Spark/Hive, and Google Big Query fully implement this feature. More recently, vendors have added new extensions to the standard, e.g. array aggregation functions. These are particularly useful in the context of running SQL against a distributed file system (Hadoop, Spark, Google BigQuery) where we have weaker data co-locality guarantees than on a distributed relational database (MPP). Rather than evenly distributing the data across all nodes, SQL engines running queries against a distributed filesystem can achieve data co-locality guarantees by nesting data and thus avoiding potentially expensive joins involving heavy shuffling across the network. User-defined aggregate functions that can be used in window functions are another extremely powerful feature.

Generating data in T-SQL

Method to generate data based on the union all

select 1 a, 1 b union all
select 1, 2 union all
select 1, 3 union all
select 2, 1 union all
select 5, 1

SQL Server 2008 supports the "row constructor" specified in the SQL3 ("SQL:1999") standard

select *
from (values (1, 1), (1, 2), (1, 3), (2, 1), (5, 1)) as x(a, b)

References

  1. ^ Microsoft. "Transact-SQL Syntax Conventions".
  2. ^ MySQL. "SQL SELECT Syntax".
  3. ^ PostgreSQL 9.1.24 Documentation - Chapter 3. Advanced Features
  4. ^ OpenLink Software. "9.19.10. The TOP SELECT Option". docs.openlinksw.com (in EN_US). Retrieved 1 October 2019.{{cite web}}: CS1 maint: unrecognized language (link)
  5. ^ Ing. Óscar Bonilla, MBA
  6. ^ Inside Microsoft SQL Server 2005: T-SQL Querying by Itzik Ben-Gan, Lubor Kollar, and Dejan Sarka

Sources

  • Horizontal & Vertical Partitioning, Microsoft SQL Server 2000 Books Online.

External links