Power BI Connector for Azure Data Lake Storage

Build 24.0.9060

SELECT Statements

A SELECT statement can consist of the following basic clauses. You can access this statement by 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> } .* 
      } [ , ... ] 
  }
  { 
    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> 
    ]
  ] 
}

<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 
  | {RANK() | DENSE_RANK()} OVER ([PARTITION BY <column_reference>] {ORDER BY <column_reference>})
  | <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 Resources
  2. Rename a column:
    SELECT [Permission] AS MY_Permission FROM Resources
  3. Cast a column's data as a different data type:
    SELECT CAST(AnnualRevenue AS VARCHAR) AS Str_AnnualRevenue FROM Resources
  4. Search data:
    SELECT * FROM Resources WHERE Type = 'FILE'
  5. Return the number of items matching the query criteria:
    SELECT COUNT(*) AS MyCount FROM Resources 
  6. Return the number of unique items matching the query criteria:
    SELECT COUNT(DISTINCT Permission) FROM Resources 
  7. Return the unique items matching the query criteria:
    SELECT DISTINCT Permission FROM Resources 
  8. Sort a result set in ascending order:
    SELECT FullPath, Permission FROM Resources  ORDER BY Permission ASC
  9. Restrict a result set to the specified number of rows:
    SELECT FullPath, Permission FROM Resources LIMIT 10 
  10. Parameterize a query to pass in inputs at execution time. This enables you to create prepared statements and mitigate SQL injection attacks.
    SELECT * FROM Resources WHERE Type = @param

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 Azure Data Lake Storage.

    SELECT * FROM Resources WHERE Pseudo = '@Pseudo'
    

Aggregate Functions

For SELECT examples using aggregate functions, see Aggregate Functions.

JOIN Queries

See JOIN Queries for SELECT query examples using JOINs.

Date Literal Functions

Date Literal Functions contains SELECT examples with date literal functions.

Window Functions

See Window Functions for SELECT examples containing window functions.

Table-Valued Functions

See Table-Valued Functions for SELECT examples with table-valued functions.

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Build 24.0.9060