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A relational database management system uses SQL conditions or expressions in WHERE clauses and in HAVING clauses to SELECT subsets of data.
| | This article needs additional citations for verification .(December 2009) |
A relational database management system uses SQL conditions or expressions in WHERE clauses and in HAVING clauses to SELECT subsets of data.
 | This section needs expansion. You can help by adding to it. (July 2010) |
EXISTS [1] to determine whether rows exist in a subquery result. [2] To SELECT one row of data from a table called tab with a primary key column (pk) set to 100 — use the condition pk = 100:
SELECT*FROMtabWHEREpk=100To identify whether a table tab has rows of data with a duplicated column dk— use the condition having count(*) > 1:
SELECTdkFROMtabGROUPBYdkHAVINGcount(*)>1A relational database is a digital database based on the relational model of data, as proposed by E. F. Codd in 1970. A software system used to maintain relational databases is a relational database management system (RDBMS). Many relational database systems have an option of using the SQL for querying and maintaining the database.
Transact-SQL (T-SQL) is Microsoft's and Sybase's proprietary extension to the SQL used to interact with relational databases. T-SQL expands on the SQL standard to include procedural programming, local variables, various support functions for string processing, date processing, mathematics, etc. and changes to the DELETE and UPDATE statements.
A join clause in SQL – corresponding to a join operation in relational algebra – combines columns from one or more tables into a new table. ANSI-standard SQL specifies five types of JOIN: INNER, LEFT OUTER, RIGHT OUTER, FULL OUTER and CROSS.
The SQL SELECT statement returns a result set of records, from one or more tables.
A SQL INSERT statement adds one or more records to any single table in a relational database.
An SQL UPDATE statement changes the data of one or more records in a table. Either all the rows can be updated, or a subset may be chosen using a condition.
A database trigger is procedural code that is automatically executed in response to certain events on a particular table or view in a database. The trigger is mostly used for maintaining the integrity of the information on the database. For example, when a new record is added to the employees table, new records should also be created in the tables of the taxes, vacations and salaries. Triggers can also be used to log historical data, for example to keep track of employees' previous salaries.
In a database, a view is the result set of a stored query on the data, which the database users can query just as they would in a persistent database collection object. This pre-established query command is kept in the database dictionary. Unlike ordinary base tables in a relational database, a view does not form part of the physical schema: as a result set, it is a virtual table computed or collated dynamically from data in the database when access to that view is requested. Changes applied to the data in a relevant underlying table are reflected in the data shown in subsequent invocations of the view. In some NoSQL databases, views are the only way to query data.
Null or NULL is a special marker used in Structured Query Language to indicate that a data value does not exist in the database. Introduced by the creator of the relational database model, E. F. Codd, SQL Null serves to fulfil the requirement that all true relational database management systems (RDMS) support a representation of "missing information and inapplicable information". Codd also introduced the use of the lowercase Greek omega (ω) symbol to represent Null in database theory. In SQL, NULL is a reserved word used to identify this marker.
A pivot table is a table of statistics that summarizes the data of a more extensive table. This summary might include sums, averages, or other statistics, which the pivot table groups together in a meaningful way.
A WHERE clause in SQL specifies that a SQL Data Manipulation Language (DML) statement should only affect rows that meet specified criteria. The criteria are expressed in the form of predicates. WHERE clauses are not mandatory clauses of SQL DML statements, but can be used to limit the number of rows affected by a SQL DML statement or returned by a query. In brief SQL WHERE clause is used to extract only those results from a SQL statement, such as: SELECT, INSERT, UPDATE, or DELETE statement.
A relational database management system uses SQL MERGE statements to INSERT new records or UPDATE existing records depending on whether condition matches. It was officially introduced in the SQL:2003 standard, and expanded in the SQL:2008 standard.
A HAVING clause in SQL specifies that an SQL SELECT statement must only return rows where aggregate values meet the specified conditions.
A GROUP BY statement in SQL specifies that a SQL SELECT statement partitions result rows into groups, based on their values in one or several columns. Typically, grouping is used to apply some sort of aggregate function for each group.
The SQL From clause is the source of a rowset to be operated upon in a Data Manipulation Language (DML) statement. From clauses are very common, and will provide the rowset to be exposed through a Select statement, the source of values in an Update statement, and the target rows to be deleted in a Delete statement.
A hierarchical query is a type of SQL query that handles hierarchical model data. They are special cases of more general recursive fixpoint queries, which compute transitive closures.
In a SQL database query, a correlated subquery is a subquery that uses values from the outer query. Because the subquery may be evaluated once for each row processed by the outer query, it can be slow.
A full table scan is a scan made on a database where each row of the table is read in a sequential (serial) order and the columns encountered are checked for the validity of a condition. Full table scans are usually the slowest method of scanning a table due to the heavy amount of I/O reads required from the disk which consists of multiple seeks as well as costly disk to memory transfers.
Apache Hive is a data warehouse software project built on top of Apache Hadoop for providing data query and analysis. Hive gives an SQL-like interface to query data stored in various databases and file systems that integrate with Hadoop. Traditional SQL queries must be implemented in the MapReduce Java API to execute SQL applications and queries over distributed data. Hive provides the necessary SQL abstraction to integrate SQL-like queries (HiveQL) into the underlying Java without the need to implement queries in the low-level Java API. Since most data warehousing applications work with SQL-based querying languages, Hive aids portability of SQL-based applications to Hadoop. While initially developed by Facebook, Apache Hive is used and developed by other companies such as Netflix and the Financial Industry Regulatory Authority (FINRA). Amazon maintains a software fork of Apache Hive included in Amazon Elastic MapReduce on Amazon Web Services.
The syntax of the SQL programming language is defined and maintained by ISO/IEC SC 32 as part of ISO/IEC 9075. This standard is not freely available. Despite the existence of the standard, SQL code is not completely portable among different database systems without adjustments.
SQL Keywords [...] The appendix lists the SQL:2003 standard's reserved and non-reserved keywords. [...] EXISTS [...]
EXISTS and NOT EXISTS [...] look for the existence or nonexistence of rows in a subquery result.