SELECT Statements

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 component:

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

Return all columns:
```
SELECT * FROM Schemas
```

Rename a column:

SELECT [DatasetName] AS MY_DatasetName FROM Schemas

Cast a column's data as a different data type:

SELECT CAST(AnnualRevenue AS VARCHAR) AS Str_AnnualRevenue FROM Schemas

Search data:

SELECT * FROM Schemas WHERE ProjectId = 'bigquery-public-data'

Return the number of items matching the query criteria:
```
SELECT COUNT(*) AS MyCount FROM Schemas 
```
Return the number of unique items matching the query criteria:
```
SELECT COUNT(DISTINCT DatasetName) FROM Schemas 
```
Return the unique items matching the query criteria:
```
SELECT DISTINCT DatasetName FROM Schemas 
```

Sort a result set in ascending order:

SELECT Type, DatasetName FROM Schemas  ORDER BY DatasetName ASC

Restrict a result set to the specified number of rows:
```
SELECT Type, DatasetName FROM Schemas LIMIT 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 Schemas WHERE ProjectId = @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 Google Data Catalog.

    SELECT * FROM Schemas WHERE CreatedTime = '2018-08-13 18:39:00'

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.

SSIS Components for Google Data Catalog