# Amazon Marketplace
### 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 Orders` |
| ---------------------- |
2. Rename a column:
| `SELECT [SellerOrderId] AS MY_SellerOrderId FROM Orders` |
| -------------------------------------------------------- |
3. Cast a column's data as a different data type:
| `SELECT CAST(AnnualRevenue AS VARCHAR) AS Str_AnnualRevenue FROM Orders` |
| ------------------------------------------------------------------------ |
4. Search data:
| `SELECT * FROM Orders WHERE BuyerEmail = 'bob@gmail.com'` |
| --------------------------------------------------------- |
5. Return the number of items matching the query criteria:
| `SELECT COUNT(*) AS MyCount FROM Orders` |
| ---------------------------------------- |
6. Return the number of unique items matching the query criteria:
| `SELECT COUNT(DISTINCT SellerOrderId) FROM Orders` |
| -------------------------------------------------- |
7. Return the unique items matching the query criteria:
| `SELECT DISTINCT SellerOrderId FROM Orders` |
| ------------------------------------------- |
8. Summarize data:
| `SELECT SellerOrderId, MAX(AnnualRevenue) FROM Orders GROUP BY SellerOrderId` |
| ----------------------------------------------------------------------------- |
See Aggregate Functions below for details.
9. Retrieve data from multiple tables.
| `SELECT c.SellerOrderId, o.SellerSKU, o.NumberOfItems, o.QuantityShipped FROM Orders c INNER JOIN OrderItems o ON c.AmazonOrderId = o.AmazonOrderId` |
| ---------------------------------------------------------------------------------------------------------------------------------------------------- |
See JOIN Queries below for details.
10. Sort a result set in ascending order:
| `SELECT Id, SellerOrderId FROM Orders ORDER BY SellerOrderId ASC` |
| ------------------------------------------------------------------ |
11. Restrict a result set to the specified number of rows:
| `SELECT Id, SellerOrderId FROM Orders 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 Orders WHERE BuyerEmail = @param` |
| ------------------------------------------------ |
### Aggregate Functions
#### COUNT
Returns the number of rows matching the query criteria.
| `SELECT COUNT(*) FROM Orders WHERE BuyerEmail = 'bob@gmail.com'` |
| ---------------------------------------------------------------- |
#### COUNT(DISTINCT)
Returns the number of distinct, non-null field values matching the query criteria.
| `SELECT COUNT(DISTINCT Id) AS DistinctValues FROM Orders WHERE BuyerEmail = 'bob@gmail.com'` |
| -------------------------------------------------------------------------------------------- |
#### AVG
Returns the average of the column values.
| `SELECT SellerOrderId, AVG(AnnualRevenue) FROM Orders WHERE BuyerEmail = 'bob@gmail.com'` `GROUP BY SellerOrderId` |
| ------------------------------------------------------------------------------------------------------------------- |
#### MIN
Returns the minimum column value.
| `SELECT MIN(AnnualRevenue), SellerOrderId FROM Orders WHERE BuyerEmail = 'bob@gmail.com'` `GROUP BY SellerOrderId` |
| ------------------------------------------------------------------------------------------------------------------ |
#### MAX
Returns the maximum column value.
| `SELECT SellerOrderId, MAX(AnnualRevenue) FROM Orders WHERE BuyerEmail = 'bob@gmail.com'` `GROUP BY SellerOrderId` |
| ------------------------------------------------------------------------------------------------------------------ |
#### SUM
Returns the total sum of the column values.
| `SELECT SUM(AnnualRevenue) FROM Orders WHERE BuyerEmail = 'bob@gmail.com'` |
| -------------------------------------------------------------------------- |
### JOIN Queries
The Provider for Amazon Marketplace 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 c.SellerOrderId, o.SellerSKU, o.NumberOfItems, o.QuantityShipped FROM Orders c INNER JOIN OrderItems o ON c.AmazonOrderId = o.AmazonOrderId` |
| ---------------------------------------------------------------------------------------------------------------------------------------------------- |
#### Left Join
A left join selects all rows in the FROM table and only matching rows in the JOIN table:
| `SELECT c.SellerOrderId, o.SellerSKU, o.NumberOfItems, o.QuantityShipped FROM Orders c LEFT JOIN OrderItems o ON c.AmazonOrderId = o.AmazonOrderId` |
| --------------------------------------------------------------------------------------------------------------------------------------------------- |
### 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)
---
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