SAP NetWeaver

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 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 c.SampleCol1, o.SampleCol2, o.SampleCol3, o.SampleCol4 FROM SampleTable_1 c INNER JOIN SampleTable_2 o ON c.Id = o.Id2

    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 SAP Gateway 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.SampleCol1, o.SampleCol2, o.SampleCol3, o.SampleCol4 FROM SampleTable_1 c INNER JOIN SampleTable_2 o ON c.Id = o.Id2

Left Join

A left join selects all rows in the FROM table and only matching rows in the JOIN table:

SELECT c.SampleCol1, o.SampleCol2, o.SampleCol3, o.SampleCol4 FROM SampleTable_1 c LEFT JOIN SampleTable_2 o ON c.Id = o.Id2

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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