Power BI Connector for Neo4j

Build 23.0.8790

SELECT Statements

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> 
    ]
  ] 
}

<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 ProductCategory
  2. Rename a column:
    SELECT [CategoryName] AS MY_CategoryName FROM ProductCategory
  3. Cast a column's data as a different data type:
    SELECT CAST(AnnualRevenue AS VARCHAR) AS Str_AnnualRevenue FROM ProductCategory
  4. Search data:
    SELECT * FROM ProductCategory WHERE CategoryOwner = 'Bob'
  5. Return the number of items matching the query criteria:
    SELECT COUNT(*) AS MyCount FROM ProductCategory 
  6. Return the number of unique items matching the query criteria:
    SELECT COUNT(DISTINCT CategoryName) FROM ProductCategory 
  7. Return the unique items matching the query criteria:
    SELECT DISTINCT CategoryName FROM ProductCategory 
  8. Sort a result set in ascending order:
    SELECT CategoryId, CategoryName FROM ProductCategory  ORDER BY CategoryName ASC
  9. Restrict a result set to the specified number of rows:
    SELECT CategoryId, CategoryName FROM ProductCategory 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 ProductCategory WHERE CategoryOwner = @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 Neo4j.

    SELECT * FROM ProductCategory WHERE Query = 'CategoryAvgPrice > 100'
    

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.

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Build 23.0.8790