secondsky SAP SQLScript Development Guide
When to Use This Skill
Use this skill when writing SQLScript procedures, anonymous blocks, table/scalar functions, AMDP methods, exception handlers, cursor logic, bulk operations, or HANA performance-sensitive database logic that should run close to the data.
For browser-based Datasphere or HANA Cloud SQL editor triage, use sap-browser-automation for manual in-app authentication, consent-gated Edge profile reuse, fresh Edge/CDP startup, auth-state bootstrap, and recovery. Load local references/edge-cdp-control.md for SQLScript-specific boundaries. Use CDP only for local UI inspection, console diagnostics, deployment messages, and approved screenshots; default database validation still belongs in SQL/HANA tooling.
Overview
SQLScript is SAP HANA's procedural extension to SQL, enabling complex data-intensive logic execution directly within the database layer. It follows the code-to-data paradigm, pushing computation to where data resides rather than moving data to the application layer.
Key Characteristics
- Case-insensitive language
- All statements end with semicolons
- Variables use colon prefix when referenced (
:variableName) - No colon when assigning values
- Use
DUMMYtable for single-row operations
Two Logic Types
| Type | Description | Execution |
|---|---|---|
| Declarative | Pure SQL sequences | Converted to data flow graphs, processed in parallel |
| Imperative | Control structures (IF, WHILE, FOR) | Processed sequentially, prevents parallel execution |
Table of Contents
- Overview
- Container Types
- Data Types
- Variable Declaration
- Control Structures
- Table Types
- Cursors
- Exception Handling
- AMDP Integration
- Performance Best Practices
- System Limits
- Debugging Tools
- Quick Reference
- Additional Resources
Container Types
1. Anonymous Blocks
Single-use logic not stored in the database. Useful for testing and ad-hoc execution.
DO [(<parameter_clause>)]
BEGIN [SEQUENTIAL EXECUTION]
<body>
END;
Example:
DO
BEGIN
DECLARE lv_count INTEGER;
SELECT COUNT(*) INTO lv_count FROM "MYTABLE";
SELECT :lv_count AS record_count FROM DUMMY;
END;
2. Stored Procedures
Reusable database objects with input/output parameters.
CREATE [OR REPLACE] PROCEDURE <procedure_name>
(
[IN <param> <datatype>],
[OUT <param> <datatype>],
[INOUT <param> <datatype>]
)
LANGUAGE SQLSCRIPT
[SQL SECURITY {DEFINER | INVOKER}]
[DEFAULT SCHEMA <schema_name>]
[READS SQL DATA | READS SQL DATA WITH RESULT VIEW <view_name>]
AS
BEGIN
<procedure_body>
END;
3. User-Defined Functions
Scalar UDF - Returns single value:
CREATE FUNCTION <function_name> (<input_parameters>)
RETURNS <scalar_type>
LANGUAGE SQLSCRIPT
AS
BEGIN
<function_body>
RETURN <value>;
END;
Table UDF - Returns table (read-only):
CREATE FUNCTION <function_name> (<input_parameters>)
RETURNS TABLE (<column_definitions>)
LANGUAGE SQLSCRIPT
READS SQL DATA
AS
BEGIN
RETURN SELECT ... FROM ...;
END;
Data Types
SQLScript supports comprehensive data types for different use cases. See references/data-types.md for complete documentation including:
- Numeric types (TINYINT, INTEGER, DECIMAL, etc.)
- Character types (VARCHAR, NVARCHAR, CLOB, etc.)
- Date/Time types (DATE, TIME, TIMESTAMP, SECONDDATE)
- Binary types (VARBINARY, BLOB)
- Type conversion functions (CAST, TO_ functions)
- NULL handling patterns
Variable Declaration
Scalar Variables
DECLARE <variable_name> <datatype> [:= <initial_value>];
-- Examples
DECLARE lv_name NVARCHAR(100);
DECLARE lv_count INTEGER := 0;
DECLARE lv_date DATE := CURRENT_DATE;
Note: Uninitialized variables default to NULL.
Table Variables
Implicit declaration:
lt_result = SELECT * FROM "MYTABLE" WHERE status = 'A';
Explicit declaration:
DECLARE lt_data TABLE (
id INTEGER,
name NVARCHAR(100),
amount DECIMAL(15,2)
);
Using TABLE LIKE:
DECLARE lt_copy TABLE LIKE :lt_original;
Arrays
DECLARE arr INTEGER ARRAY := ARRAY(1, 2, 3, 4, 5);
-- Access: arr[1], arr[2], etc. (1-based index)
-- Note: Arrays cannot be returned from procedures
Control Structures
IF-ELSE Statement
IF <condition1> THEN
<statements>
[ELSEIF <condition2> THEN
<statements>]
[ELSE
<statements>]
END IF;
Comparison Operators:
| Operator | Meaning |
|---|---|
= |
Equal to |
> |
Greater than |
< |
Less than |
>= |
Greater than or equal |
<= |
Less than or equal |
!=, <> |
Not equal |
Important: IF-ELSE cannot be used within SELECT statements. Use CASE WHEN instead.
WHILE Loop
WHILE <condition> DO
<statements>
END WHILE;
FOR Loop
-- Numeric range
FOR i IN 1..10 DO
<statements>
END FOR;
-- Reverse
FOR i IN REVERSE 10..1 DO
<statements>
END FOR;
-- Cursor iteration
FOR row AS <cursor_name> DO
<statements using row.column_name>
END FOR;
LOOP with EXIT
LOOP
<statements>
IF <condition> THEN
BREAK;
END IF;
END LOOP;
Table Types
Define reusable table structures:
CREATE TYPE <type_name> AS TABLE (
<column1> <datatype>,
<column2> <datatype>,
...
);
Usage in procedures:
CREATE PROCEDURE get_employees (OUT et_result MY_TABLE_TYPE)
LANGUAGE SQLSCRIPT AS
BEGIN
et_result = SELECT * FROM "EMPLOYEES";
END;
Cursors
Cursors handle result sets row by row. Pattern: Declare → Open → Fetch → Close
Performance Note: Cursors bypass the database optimizer and process rows sequentially. Use primarily with primary key-based queries. Prefer set-based operations when possible.
DECLARE CURSOR <cursor_name> FOR
SELECT <columns> FROM <table> [WHERE <condition>];
OPEN <cursor_name>;
FETCH <cursor_name> INTO <variables>;
CLOSE <cursor_name>;
Complete Example:
DO
BEGIN
DECLARE lv_id INTEGER;
DECLARE lv_name NVARCHAR(100);
DECLARE CURSOR cur_employees FOR
SELECT id, name FROM "EMPLOYEES" WHERE dept = 'IT';
OPEN cur_employees;
FETCH cur_employees INTO lv_id, lv_name;
WHILE NOT cur_employees::NOTFOUND DO
-- Process row
SELECT :lv_id, :lv_name FROM DUMMY;
FETCH cur_employees INTO lv_id, lv_name;
END WHILE;
CLOSE cur_employees;
END;
FOR Loop Alternative:
FOR row AS cur_employees DO
SELECT row.id, row.name FROM DUMMY;
END FOR;
Exception Handling
EXIT HANDLER
Suspends execution and performs cleanup when exceptions occur.
DECLARE EXIT HANDLER FOR <condition_value>
<statement>;
Condition values:
SQLEXCEPTION- Any SQL exceptionSQL_ERROR_CODE <number>- Specific error code
Access error details:
::SQL_ERROR_CODE- Numeric error code::SQL_ERROR_MESSAGE- Error message text
Example:
CREATE PROCEDURE safe_insert (IN iv_id INTEGER, IN iv_name NVARCHAR(100))
LANGUAGE SQLSCRIPT AS
BEGIN
DECLARE EXIT HANDLER FOR SQLEXCEPTION
BEGIN
SELECT ::SQL_ERROR_CODE AS err_code,
::SQL_ERROR_MESSAGE AS err_msg FROM DUMMY;
END;
INSERT INTO "MYTABLE" VALUES (:iv_id, :iv_name);
END;
CONDITION
Associate user-defined names with error codes:
DECLARE <condition_name> CONDITION FOR SQL_ERROR_CODE <number>;
-- Example
DECLARE duplicate_key CONDITION FOR SQL_ERROR_CODE 301;
DECLARE EXIT HANDLER FOR duplicate_key
SELECT 'Duplicate key error' FROM DUMMY;
SIGNAL and RESIGNAL
Throw user-defined exceptions (codes 10000-19999):
-- Throw exception
SIGNAL <condition_name> SET MESSAGE_TEXT = '<message>';
-- Re-throw in handler
RESIGNAL [<condition_name>] [SET MESSAGE_TEXT = '<message>'];
Common Error Codes:
| Code | Description |
|---|---|
| 301 | Unique constraint violation |
| 1299 | No data found |
AMDP Integration
ABAP Managed Database Procedures allow SQLScript within ABAP classes.
Class Definition
CLASS zcl_my_amdp DEFINITION PUBLIC FINAL CREATE PUBLIC.
PUBLIC SECTION.
INTERFACES if_amdp_marker_hdb. " Required interface
TYPES: BEGIN OF ty_result,
id TYPE i,
name TYPE string,
END OF ty_result,
tt_result TYPE STANDARD TABLE OF ty_result.
CLASS-METHODS: get_data
IMPORTING VALUE(iv_filter) TYPE string
EXPORTING VALUE(et_result) TYPE tt_result.
ENDCLASS.
Method Implementation
CLASS zcl_my_amdp IMPLEMENTATION.
METHOD get_data BY DATABASE PROCEDURE
FOR HDB
LANGUAGE SQLSCRIPT
OPTIONS READ-ONLY
USING ztable.
et_result = SELECT id, name
FROM ztable
WHERE category = :iv_filter;
ENDMETHOD.
ENDCLASS.
AMDP Restrictions
- Parameters must be pass-by-value (no RETURNING)
- Only scalar types, structures, internal tables allowed
- No nested tables or deep structures
- COMMIT/ROLLBACK not permitted
- Must use Eclipse ADT for development
- Auto-created on first invocation
Performance Best Practices
1. Reduce Data Volume Early
-- Good: Filter and project early
lt_filtered = SELECT col1, col2 FROM "BIGTABLE" WHERE status = 'A';
lt_result = SELECT a.col1, b.name
FROM :lt_filtered AS a
JOIN "LOOKUP" AS b ON a.id = b.id;
-- Bad: Join then filter
lt_result = SELECT a.col1, b.name
FROM "BIGTABLE" AS a
JOIN "LOOKUP" AS b ON a.id = b.id
WHERE a.status = 'A';
2. Prefer Declarative Over Imperative
-- Good: Set-based operation
lt_result = SELECT id, amount * 1.1 AS new_amount FROM "ORDERS";
-- Bad: Row-by-row processing
FOR row AS cur_orders DO
UPDATE "ORDERS" SET amount = row.amount * 1.1 WHERE id = row.id;
END FOR;
3. Avoid Engine Mixing
- Don't mix Row Store and Column Store tables in same query
- Avoid Calculation Engine functions with pure SQL
- Use consistent storage types
4. Use UNION ALL Instead of UNION
-- Faster when duplicates impossible or acceptable
SELECT * FROM table1 UNION ALL SELECT * FROM table2;
-- Slower: removes duplicates
SELECT * FROM table1 UNION SELECT * FROM table2;
5. Avoid Dynamic SQL
-- Bad: Re-optimized each execution
EXECUTE IMMEDIATE 'SELECT * FROM ' || :lv_table;
-- Good: Static SQL with parameters
SELECT * FROM "MYTABLE" WHERE id = :lv_id;
6. Position Imperative Logic Last
Place control structures at the end of procedures to maximize parallel processing of declarative statements.
System Limits
| Limit | Value |
|---|---|
| Table locks per transaction | 16,383 |
| Tables in a statement | 4,095 |
| SQL statement length | 2 GB |
| Procedure size | Bounded by SQL statement length (2 GB) |
Note: Actual limits may vary by HANA version. Consult SAP documentation for version-specific limits.
Debugging Tools
- SQLScript Debugger - SAP Web IDE / Business Application Studio
- Plan Visualizer - Analyze execution plans
- Expensive Statement Trace - Identify bottlenecks
- SQL Analyzer - Query optimization recommendations
Quick Reference
String Concatenation
lv_result = lv_str1 || ' ' || lv_str2;
NULL Handling
COALESCE(value, default_value)
IFNULL(value, default_value)
NULLIF(value1, value2)
Date Operations
ADD_DAYS(date, n)
ADD_MONTHS(date, n)
DAYS_BETWEEN(date1, date2)
CURRENT_DATE
CURRENT_TIMESTAMP
Type Conversion
CAST(value AS datatype)
TO_VARCHAR(value)
TO_INTEGER(value)
TO_DATE(string, 'YYYY-MM-DD')
TO_TIMESTAMP(string, 'YYYY-MM-DD HH24:MI:SS')
Related Skills
For comprehensive SAP development, combine this skill with:
| Skill | Use Case |
|---|---|
| sap-abap | ABAP programming patterns for AMDP context |
| sap-abap-cds | CDS views that consume SQLScript procedures |
| sap-cap-capire | CAP framework database procedures integration |
| sap-hana-cli | HANA CLI for procedure deployment and testing |
| sap-btp-cloud-platform | BTP deployment of HANA artifacts |
Bundled Resources
Reference Documentation
references/skill-reference-guide.md- Index of all references with quick navigationreferences/glossary.md- SQLScript terminology and conceptsreferences/syntax-reference.md- Complete SQLScript syntax referencereferences/built-in-functions.md- Built-in functions catalogreferences/data-types.md- Data types and conversionreferences/exception-handling.md- Exception handling patternsreferences/amdp-integration.md- AMDP integration patternsreferences/performance-guide.md- Optimization techniquesreferences/advanced-features.md- Lateral joins, JSON, query hints, currency conversionreferences/troubleshooting.md- Common errors and solutionsreferences/edge-cdp-control.md- SQLScript-specific add-on for the sharedsap-browser-automationEdge/CDP and authentication layer
Production-Ready Templates
Copy and customize these templates for common patterns:
templates/simple-procedure.sql- Basic stored procedure with error handlingtemplates/procedure-with-error-handling.sql- Comprehensive error handling patternstemplates/table-function.sql- Table UDF with validationtemplates/scalar-function.sql- Scalar UDF examplestemplates/amdp-class.abap- Complete AMDP class boilerplatetemplates/amdp-procedure.sql- AMDP implementation templatetemplates/cursor-iteration.sql- Cursor patterns (classic and FOR loop)templates/bulk-operations.sql- High-performance bulk operations
Specialized Agents
- sqlscript-analyzer - Analyze code for performance issues and best practices
- procedure-generator - Generate procedures interactively from requirements
- amdp-helper - Assist with AMDP class creation and debugging
Slash Commands
/sqlscript-validate- Validate code with auto-fix capability/sqlscript-optimize- Performance analysis and optimization suggestions/sqlscript-convert- Convert between standalone and AMDP formats
Validation Hooks
Automatic code quality checks on Write/Edit operations:
- Error handling completeness
- Security vulnerabilities
- Performance anti-patterns
- Naming conventions
- AMDP compliance