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 driver:

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 
  | <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. Summarize data:
   

   SELECT CategoryName, MAX(AnnualRevenue) FROM ProductCategory GROUP BY CategoryName

   See Aggregate Functions for details.
9. Retrieve data from multiple tables.
   

   SELECT p.ProductName, pc.CategoryName, pc.CategoryOwner, opc.CategoryAvgPrice FROM Product p INNER JOIN ProductCategory pc ON p.CategoryID = pc.CategoryID

   See JOIN Queries for details.
10. Sort a result set in ascending order:
    

    SELECT CategoryId, CategoryName FROM ProductCategory  ORDER BY CategoryName ASC

11. Restrict a result set to the specified number of rows:
    

    SELECT CategoryId, CategoryName FROM ProductCategory 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 ProductCategory WHERE CategoryOwner = @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 Neo4j.

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