CData Python Connector for Microsoft Dynamics 365

Build 22.0.8462

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 GoalHeadings
  2. Rename a column:
    SELECT [GoalHeadingId] AS MY_GoalHeadingId FROM GoalHeadings
  3. Cast a column's data as a different data type:
    SELECT CAST(AnnualRevenue AS VARCHAR) AS Str_AnnualRevenue FROM GoalHeadings
  4. Search data:
    SELECT * FROM GoalHeadings WHERE Name <> 'MyAccount'
  5. Return the number of items matching the query criteria:
    SELECT COUNT(*) AS MyCount FROM GoalHeadings 
  6. Return the number of unique items matching the query criteria:
    SELECT COUNT(DISTINCT GoalHeadingId) FROM GoalHeadings 
  7. Return the unique items matching the query criteria:
    SELECT DISTINCT GoalHeadingId FROM GoalHeadings 
  8. Summarize data:
    SELECT GoalHeadingId, MAX(AnnualRevenue) FROM GoalHeadings GROUP BY GoalHeadingId
    See Aggregate Functions for details.
  9. Retrieve data from multiple tables.
    SELECT Accounts.Name, Contracts.ContractNumber FROM Accounts, Contracts WHERE Accounts.AccountId=Contracts._AccountId_Value
    See JOIN Queries for details.
  10. Sort a result set in ascending order:
    SELECT GoalHeadingId, GoalHeadingId FROM GoalHeadings  ORDER BY GoalHeadingId ASC
  11. Restrict a result set to the specified number of rows:
    SELECT GoalHeadingId, GoalHeadingId FROM GoalHeadings 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 GoalHeadings WHERE Name = @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 Microsoft Dynamics 365.

    SELECT * FROM GoalHeadings WHERE Pseudo = '@Pseudo'
    

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Build 22.0.8462