CData Python Connector for Google BigQuery

Build 23.0.8839

SELECT Statements

Google BigQuery API Syntax

The Google BigQuery API offers additional SQL operators and functions. A complete list of the available syntax is located at: https://cloud.google.com/bigquery/query-reference

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 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 
  | {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 [publicdata].[samples].github_nested
  2. Rename a column:
    SELECT [repository.name] AS MY_repository.name FROM [publicdata].[samples].github_nested
  3. Cast a column's data as a different data type:
    SELECT CAST(repository.watchers AS VARCHAR) AS Str_repository.watchers FROM [publicdata].[samples].github_nested
  4. Search data:
    SELECT * FROM [publicdata].[samples].github_nested WHERE repository.name = 'EntityFramework'
  5. The Google BigQuery APIs support the following operators in the WHERE clause: =, >, <, >=, <=, <>, !=, LIKE, NOT LIKE, IN, NOT IN, IS NULL, IS NOT NULL, AND, OR, +, -, *, /, %, ||.
    SELECT * FROM [publicdata].[samples].github_nested WHERE repository.name = 'EntityFramework';
  6. Return the number of items matching the query criteria:
    SELECT COUNT(*) AS MyCount FROM [publicdata].[samples].github_nested 
  7. Return the number of unique items matching the query criteria:
    SELECT COUNT(DISTINCT repository.name) FROM [publicdata].[samples].github_nested 
  8. Return the unique items matching the query criteria:
    SELECT DISTINCT repository.name FROM [publicdata].[samples].github_nested 
  9. Sort a result set in ascending order:
    SELECT actor.attributes.email, repository.name FROM [publicdata].[samples].github_nested  ORDER BY repository.name ASC
  10. Restrict a result set to the specified number of rows:
    SELECT actor.attributes.email, repository.name FROM [publicdata].[samples].github_nested LIMIT 10 
  11. Parameterize a query to pass in inputs at execution time. This enables you to create prepared statements and mitigate SQL injection attacks.
    SELECT * FROM [publicdata].[samples].github_nested WHERE repository.name = @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 Google BigQuery.

    SELECT * FROM [publicdata].[samples].github_nested 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.

Projection Functions

See Projection Functions for SELECT examples with projection functions.

Predicate Functions

For SELECT examples using predicate functions, see Predicate Functions.

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Build 23.0.8839