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SELECT Statements

CData Cmdlets for Google BigQuery 2019 - Build 19.0.7354

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 cmdlet:

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 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 unique items matching the query criteria:
    SELECT DISTINCT repository.name FROM publicdata.samples.github_nested 
  8. Summarize data:
    SELECT repository.name, MAX(repository.watchers) FROM publicdata.samples.github_nested  GROUP BY repository.name
    See Aggregate Functions for details.
  9. Retrieve data from multiple tables.
    SELECT * FROM CRMAccounts INNER JOIN ERPCustomers ON CRMAccounts.BillingState = ERPCustomers.BillingState
    See JOIN Queries for details.
  10. Sort a result set in ascending order:
    SELECT actor.attributes.email, repository.name FROM publicdata.samples.github_nested  ORDER BY repository.name ASC
  11. Restrict a result set to the specified number of rows:
    SELECT actor.attributes.email, repository.name FROM publicdata.samples.github_nested 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 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'
    

 
 
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