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 <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 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 = '[e-mail]'

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 = '[e-mail]'

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 = '[e-mail]'

AVG

Returns the average of the column values.

SELECT SellerOrderId, AVG(AnnualRevenue) FROM Orders WHERE BuyerEmail = '[e-mail]' GROUP BY SellerOrderId

MIN

Returns the minimum column value.

SELECT MIN(AnnualRevenue), SellerOrderId FROM Orders WHERE BuyerEmail = '[e-mail]' GROUP BY SellerOrderId

MAX

Returns the maximum column value.

SELECT SellerOrderId, MAX(AnnualRevenue) FROM Orders WHERE BuyerEmail = '[e-mail]' GROUP BY SellerOrderId

SUM

Returns the total sum of the column values.

SELECT SUM(AnnualRevenue) FROM Orders WHERE BuyerEmail = '[e-mail]'

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)