A SELECT statement can consist of the following basic clauses.

• SELECT
• INTO
• FROM
• JOIN
• WHERE
• GROUP BY
• HAVING
• UNION
• ORDER BY
• LIMIT

SELECT Syntax

The following syntax diagram outlines the syntax supported by the SQL engine of the driver:

SELECT {
  [ TOP <numeric_literal> | DISTINCT ]
  { 
    * 
    | { 
        <expression> [ [ AS ] <column_reference> ] 
        | { <table_name> | <correlation_name> } .* 
      } [ , ... ] 
  }
  [ INTO csv:// [ filename= ] <file_path> [ ;delimiter=tab ] ]
  { 
    FROM <table_reference> [ [ AS ] <identifier> ] 
  } [ , ... ]
  [ [  
      INNER | { { LEFT | RIGHT | FULL } [ OUTER ] } 
    ] JOIN <table_reference> [ ON <search_condition> ] [ [ AS ] <identifier> ] 
  ] [ ... ] 
  [ WHERE <search_condition> ]
  [ GROUP BY <column_reference> [ , ... ]
  [ HAVING <search_condition> ]
  [ UNION [ ALL ] <select_statement> ]
  [ 
    ORDER BY 
    <column_reference> [ ASC | DESC ] [ NULLS FIRST | NULLS LAST ]
  ]
  [ 
    LIMIT <expression>
    [ 
      { OFFSET | , }
      <expression> 
    ]
  ] 
} | SCOPE_IDENTITY() 

<expression> ::=
  | <column_reference>
  | @ <parameter> 
  | ?
  | COUNT( * | { [ DISTINCT ] <expression> } )
  | { AVG | MAX | MIN | SUM | COUNT } ( <expression> ) 
  | NULLIF ( <expression> , <expression> ) 
  | COALESCE ( <expression> , ... ) 
  | CASE <expression>
      WHEN { <expression> | <search_condition> } THEN { <expression> | NULL } [ ... ]
    [ ELSE { <expression> | NULL } ]
    END 
  | <literal>
  | <sql_function> 

<search_condition> ::= 
  {
    <expression> { = | > | < | >= | <= | <> | != | LIKE | NOT LIKE | IN | NOT IN | IS NULL | IS NOT NULL | AND | OR | CONTAINS | BETWEEN } [ <expression> ]
  } [ { AND | OR } ... ] 

Examples

1. Return all columns:
   

   SELECT * FROM [testDBS].[public].testTable

2. Rename a column:
   

   SELECT [Name] AS MY_Name FROM [testDBS].[public].testTable

3. Cast a column's data as a different data type:
   

   SELECT CAST(AnnualRevenue AS VARCHAR) AS Str_AnnualRevenue FROM [testDBS].[public].testTable

4. Search data:
   

   SELECT * FROM [testDBS].[public].testTable WHERE Industry = 'Floppy Disks'

5. Return the number of items matching the query criteria:
   

   SELECT COUNT(*) AS MyCount FROM [testDBS].[public].testTable 

6. Return the number of unique items matching the query criteria:
   

   SELECT COUNT(DISTINCT Name) FROM [testDBS].[public].testTable 

7. Return the unique items matching the query criteria:
   

   SELECT DISTINCT Name FROM [testDBS].[public].testTable 

8. Summarize data:
   

   SELECT Name, MAX(AnnualRevenue) FROM [testDBS].[public].testTable GROUP BY Name

   See Aggregate Functions for details.
9. Retrieve data from multiple tables.
   

   SELECT restaurants.name, zips.city FROM restaurants INNER JOIN zips ON restaurants.address_zipcode = zips.C_id

   See JOIN Queries for details.
10. Sort a result set in ascending order:
    

    SELECT Id, Name FROM [testDBS].[public].testTable  ORDER BY Name ASC

11. Restrict a result set to the specified number of rows:
    

    SELECT Id, Name FROM [testDBS].[public].testTable LIMIT 10 

12. Parameterize a query to pass in inputs at execution time. This enables you to create prepared statements and mitigate SQL injection attacks.
    

    SELECT * FROM [testDBS].[public].testTable WHERE Industry = @param

See Explicitly Caching Data for information on using the SELECT statement in offline mode.

Pseudo Columns

Some input-only fields are available in SELECT statements. These fields, called pseudo columns, do not appear as regular columns in the results, yet may be specified as part of the WHERE clause. You can use pseudo columns to access additional features from Vertica.

    SELECT * FROM [testDBS].[public].testTable WHERE Pseudo = '@Pseudo'