According to the SAP HANA Performance Guide for Developers1, the SQL Analyzer tool can help you understand and analyze the execution plan of a SQL statement, and identify potential bottlenecks and optimizations. Some of the possible optimizations are:
* Modify SQL hints: SQL hints are directives that you can add to a SQL statement to influence the behavior of the SQL optimizer. For example, you can use hints to specify a join type, a join order, a join condition, a table distribution, or a parallel degree. SQL hints can help you improve the performance of a query by overriding the default choices of the optimizer, or by providing additional information that the optimizer cannot infer from the data or statistics. However, SQL hints should be used with caution, as they can also have negative effects if they are not compatible with the data characteristics or the system configuration. Therefore, you should always test the impact of SQL hints on the query execution time and resource consumption, and compare the results with the original query without hints. You can use the SQL Analyzer tool to view the effect of SQL hints on the execution plan, and modify them accordingly. For more information on SQL hints, see [SAP HANA SQL and System Views Reference].
* Change the data model: The data model is the logical representation of the data and the relationships among them. The data model can have a significant impact on the performance of a query, as it determines how the data is stored, accessed, and processed by the database. A well-designed data model can reduce the complexity and cost of a query, and enable the use of efficient operators and algorithms.
On the other hand, a poorly-designed data model can lead to redundant or inconsistent data, unnecessary joins or aggregations, or suboptimal access paths. Therefore, you should always review the data model and consider changing it if it does not meet the requirements of the query or the application. For example, you can use different types of views, such as calculation views, analytical views, or attribute views, to model the data according to the business logic and the analytical needs. You can also use different types of tables, such as column tables, row tables, or partitioned tables, to store the data according to the access patterns and the distribution strategies. You can use the SQL Analyzer tool to view the data model of the query, and identify the possible changes that can improve the performance.
For more information on data modeling, see [SAP HANA Modeling Guide].
References: 1: SAP HANA Performance Guide for Developers : SAP HANA SQL and System Views Reference : SAP HANA Modeling Guide