CData Python Connector for BigCommerce

Build 21.0.7930

SELECT Statements

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 provider:

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 Customers
  2. Rename a column:
    SELECT [LastName] AS MY_LastName FROM Customers
  3. Cast a column's data as a different data type:
    SELECT CAST(AnnualRevenue AS VARCHAR) AS Str_AnnualRevenue FROM Customers
  4. Search data:
    SELECT * FROM Customers WHERE Column2 = 'Bob';
  5. Return the number of items matching the query criteria:
    SELECT COUNT(*) AS MyCount FROM Customers 
  6. Return the number of unique items matching the query criteria:
    SELECT COUNT(DISTINCT LastName) FROM Customers 
  7. Return the unique items matching the query criteria:
    SELECT DISTINCT LastName FROM Customers 
  8. Summarize data:
    SELECT LastName, MAX(AnnualRevenue) FROM Customers GROUP BY LastName
    See Aggregate Functions for details.
  9. Retrieve data from multiple tables.
    SELECT c.SampleCol1, o.SampleCol2, o.SampleCol3, o.SampleCol4 FROM SampleTable_1 c INNER JOIN SampleTable_2 o ON c.Id = o.Id2
    See JOIN Queries for details.
  10. Sort a result set in ascending order:
    SELECT FirstName, LastName FROM Customers  ORDER BY LastName ASC
  11. Restrict a result set to the specified number of rows:
    SELECT FirstName, LastName FROM Customers 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 Customers WHERE Column2 = @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 BigCommerce.

    SELECT * FROM Customers WHERE Query = 'Column3 > 100'
    

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Build 21.0.7930