# Airtable ### 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 provider:
\|

SELECT {

\[ TOP \ | DISTINCT ]

{

| {

\ \[ \[ AS ] \ ]

| { \ | \ } .*

} \[ , ... ]

}

\[ INTO csv:// \[ filename= ] \ \[ ;delimiter=tab ] ]

{

FROM \ \[ \[ AS ] \ ]

} \[ , ... ]

\[ \[

INNER | { { LEFT | RIGHT | FULL } \[ OUTER ] }

] JOIN \ \[ ON \ ] \[ \[ AS ] \ ]

] \[ ... ]

\[ WHERE \ ]

\[ GROUP BY \ \[ , ... ]

\[ HAVING \ ]

\[ UNION \[ ALL ] \ ]

ORDER BY

\ \[ ASC | DESC ] \[ NULLS FIRST | NULLS LAST ]

]

LIMIT \

{ OFFSET | , }

]

} | SCOPE\_IDENTITY()

\ ::=

| \

| @ \

| ?

| COUNT( \* | { \[ DISTINCT ] \ } )

| { AVG | MAX | MIN | SUM | COUNT } ( \ )

| NULLIF ( \ , \ )

| COALESCE ( \ , ... )

| CASE \

WHEN { \ | \ } THEN { \ | NULL } \[ ... ]

\[ ELSE { \ | NULL } ]

END

| \

\ ::=

{

\ { = | > | < | >= | <= | <> | != | LIKE | NOT LIKE | IN | NOT IN | IS NULL | IS NOT NULL | AND | OR | CONTAINS | BETWEEN } \[ \ ]

} \[ { AND | OR } ... ]

| \| -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | #### Examples 1. Return all columns:
| `SELECT * FROM SampleTable_1` | | ----------------------------- | 2. Rename a column:
| `SELECT [Column1] AS MY_Column1 FROM SampleTable_1` | | --------------------------------------------------- | 3. Cast a column's data as a different data type:
| `SELECT CAST(AnnualRevenue AS VARCHAR) AS Str_AnnualRevenue FROM SampleTable_1` | | ------------------------------------------------------------------------------- | 4. Search data:
| `SELECT * FROM SampleTable_1 WHERE Column2 = 'Bob'` | | --------------------------------------------------- | 5. Return the number of items matching the query criteria:
| `SELECT COUNT(*) AS MyCount FROM SampleTable_1` | | ----------------------------------------------- | 6. Return the number of unique items matching the query criteria:
| `SELECT COUNT(DISTINCT Column1) FROM SampleTable_1` | | --------------------------------------------------- | 7. Return the unique items matching the query criteria:
| `SELECT DISTINCT Column1 FROM SampleTable_1` | | -------------------------------------------- | 8. Summarize data:
| `SELECT Column1, MAX(AnnualRevenue) FROM SampleTable_1 GROUP BY Column1` | | ------------------------------------------------------------------------ | See Aggregate Functions below for details. 9. Retrieve data from multiple tables.
| `SELECT TableA.SampleCol1, TableB.SampleCol2, TableB.SampleCol3, TableB.SampleCol4 FROM TableA INNER JOIN TableB ON TableA.Id = TableB.Id` | | ------------------------------------------------------------------------------------------------------------------------------------------ | See JOIN Queries below for details. 10. Sort a result set in ascending order:
| `SELECT Id, Column1 FROM SampleTable_1 ORDER BY Column1 ASC` | | ------------------------------------------------------------- | 11. Restrict a result set to the specified number of rows:
| `SELECT Id, Column1 FROM SampleTable_1 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 SampleTable_1 WHERE Column2 = @param` | | ---------------------------------------------------- | ### Aggregate Functions #### COUNT Returns the number of rows matching the query criteria.
| `SELECT COUNT(*) FROM SampleTable_1 WHERE Column2 = 'Bob'` | | ---------------------------------------------------------- | #### COUNT(DISTINCT) Returns the number of distinct, non-null field values matching the query criteria.
| `SELECT COUNT(DISTINCT Id) AS DistinctValues FROM SampleTable_1 WHERE Column2 = 'Bob'` | | -------------------------------------------------------------------------------------- | #### AVG Returns the average of the column values.
| `SELECT Column1, AVG(AnnualRevenue) FROM SampleTable_1 WHERE Column2 = 'Bob'` `GROUP BY Column1` | | ------------------------------------------------------------------------------------------------- | #### MIN Returns the minimum column value.
| `SELECT MIN(AnnualRevenue), Column1 FROM SampleTable_1 WHERE Column2 = 'Bob'` `GROUP BY Column1` | | ------------------------------------------------------------------------------------------------ | #### MAX Returns the maximum column value.
| `SELECT Column1, MAX(AnnualRevenue) FROM SampleTable_1 WHERE Column2 = 'Bob'` `GROUP BY Column1` | | ------------------------------------------------------------------------------------------------ | #### SUM Returns the total sum of the column values.
| `SELECT SUM(AnnualRevenue) FROM SampleTable_1 WHERE Column2 = 'Bob'` | | -------------------------------------------------------------------- | ### JOIN Queries The Provider for Airtable supports standard SQL joins like the following examples. #### Inner Join An inner join selects only rows from both tables that match the join condition:
| `SELECT TableA.SampleCol1, TableB.SampleCol2, TableB.SampleCol3, TableB.SampleCol4 FROM TableA INNER JOIN TableB ON TableA.Id = TableB.Id` | | ------------------------------------------------------------------------------------------------------------------------------------------ | #### Left Join A left join selects all rows in the FROM table and only matching rows in the JOIN table:
| `SELECT TableA.SampleCol1, TableB.SampleCol2, TableB.SampleCol3, TableB.SampleCol4 FROM TableA LEFT JOIN TableB ON TableA.Id = TableB.Id` | | ----------------------------------------------------------------------------------------------------------------------------------------- | ### Date Literal Functions The following date literal functions can be used to filter date fields using relative intervals. Note that while the <, >, and = operators are supported for these functions, <= and >= are not. #### L\_TODAY() The current day.
| `SELECT * FROM MyTable WHERE MyDateField = L_TODAY()` | | ----------------------------------------------------- | #### L\_YESTERDAY() The previous day.
| `SELECT * FROM MyTable WHERE MyDateField = L_YESTERDAY()` | | --------------------------------------------------------- | #### L\_TOMORROW() The following day.
| `SELECT * FROM MyTable WHERE MyDateField = L_TOMORROW()` | | -------------------------------------------------------- | #### L\_LAST\_WEEK() Every day in the preceding week.
| `SELECT * FROM MyTable WHERE MyDateField = L_LAST_WEEK()` | | --------------------------------------------------------- | #### L\_THIS\_WEEK() Every day in the current week.
| `SELECT * FROM MyTable WHERE MyDateField = L_THIS_WEEK()` | | --------------------------------------------------------- | #### L\_NEXT\_WEEK() Every day in the following week.
| `SELECT * FROM MyTable WHERE MyDateField = L_NEXT_WEEK()` | | --------------------------------------------------------- | Also available: * L\_LAST/L\_THIS/L\_NEXT MONTH * L\_LAST/L\_THIS/L\_NEXT QUARTER * L\_LAST/L\_THIS/L\_NEXT YEAR #### L\_LAST\_N\_DAYS(n) The previous n days, excluding the current day.
| `SELECT * FROM MyTable WHERE MyDateField = L_LAST_N_DAYS(3)` | | ------------------------------------------------------------ | #### L\_NEXT\_N\_DAYS(n) The following n days, including the current day.
| `SELECT * FROM MyTable WHERE MyDateField = L_NEXT_N_DAYS(3)` | | ------------------------------------------------------------ | Also available: * L\_LAST/L\_NEXT\_90\_DAYS #### L\_LAST\_N\_WEEKS(n) Every day in every week, starting n weeks before current week, and ending in the previous week.
| `SELECT * FROM MyTable WHERE MyDateField = L_LAST_N_WEEKS(3)` | | ------------------------------------------------------------- | #### L\_NEXT\_N\_WEEKS(n) Every day in every week, starting the following week, and ending n weeks in the future.
| `SELECT * FROM MyTable WHERE MyDateField = L_NEXT_N_WEEKS(3)` | | ------------------------------------------------------------- | Also available: * L\_LAST/L\_NEXT\_N\_MONTHS(n) * L\_LAST/L\_NEXT\_N\_QUARTERS(n) * L\_LAST/L\_NEXT\_N\_YEARS(n)