CData Python Connector for Office 365 2019 - Online Help
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SELECT Statements

CData Python Connector for Office 365 2019 - Build 19.0.7416

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 Events
  2. Rename a column:
    SELECT [location_displayName] AS MY_location_displayName FROM Events
  3. Cast a column's data as a different data type:
    SELECT CAST(Reminder AS VARCHAR) AS Str_Reminder FROM Events
  4. Search data:
    SELECT * FROM Events WHERE Id = 'Jq74mCczmFXk1tC10GB';
  5. Return the number of items matching the query criteria:
    SELECT COUNT(*) AS MyCount FROM Events 
  6. Return the number of unique items matching the query criteria:
    SELECT COUNT(DISTINCT location_displayName) FROM Events 
  7. Return the unique items matching the query criteria:
    SELECT DISTINCT location_displayName FROM Events 
  8. Summarize data:
    SELECT location_displayName, MAX(Reminder) FROM Events GROUP BY location_displayName
    See Aggregate Functions for details.
  9. Retrieve data from multiple tables.
    SELECT Groups.displayName, Conversations.Topic FROM Groups, Conversations WHERE Groups.Id=Conversations.GroupId
    See JOIN Queries for details.
  10. Sort a result set in ascending order:
    SELECT Id, location_displayName FROM Events  ORDER BY location_displayName ASC
  11. Restrict a result set to the specified number of rows:
    SELECT Id, location_displayName FROM Events 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 Events WHERE Id = @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 Office 365.

    SELECT * FROM Events WHERE Pseudo = '@Pseudo'
    

 
 
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