CData Power BI Connector for AWS Data Management 2019 - Online Help
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SELECT Statements

CData Power BI Connector for AWS Data Management 2019 - Build 19.0.7362

A SELECT statement can consist of the following basic clauses. This statement can be accessed using the Odbc.Query function in the M formula language.

  • 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 connector:

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 NorthwindProducts
  2. Rename a column:
    SELECT [Name] AS MY_Name FROM NorthwindProducts
  3. Cast a column's data as a different data type:
    SELECT CAST(Price AS VARCHAR) AS Str_Price FROM NorthwindProducts
  4. Search data:
    SELECT * FROM NorthwindProducts WHERE Industry = 'Floppy Disks';
  5. Return the number of items matching the query criteria:
    SELECT COUNT(*) AS MyCount FROM NorthwindProducts 
  6. Return the number of unique items matching the query criteria:
    SELECT COUNT(DISTINCT Name) FROM NorthwindProducts 
  7. Return the unique items matching the query criteria:
    SELECT DISTINCT Name FROM NorthwindProducts 
  8. Summarize data:
    SELECT Name, MAX(Price) FROM NorthwindProducts GROUP BY Name
    See Aggregate Functions for details.
  9. Retrieve data from multiple tables.
    SELECT Customers.ContactName, Orders.OrderDate FROM Customers, Orders WHERE Customers.CustomerId=Orders.CustomerId
    See JOIN Queries for details.
  10. Sort a result set in ascending order:
    SELECT PartitionKey, Name FROM NorthwindProducts  ORDER BY Name ASC
  11. Restrict a result set to the specified number of rows:
    SELECT PartitionKey, Name FROM NorthwindProducts 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 NorthwindProducts 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 AWSDataManagement.

    SELECT * FROM NorthwindProducts WHERE Pseudo = '@Pseudo'
    

 
 
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