How to Partition ADSOs in SAP BW/4HANA for Better Performance
ADSOs (Advanced DataStore Objects) are physical objects that allow you to store and manage transactional or analytical data in SAP BW/4HANA. ADSOs are based on columnar tables that leverage the performance and compression features of SAP HANA.
However, ADSOs can also become very large and contain billions of records, which can affect the performance and scalability of your data warehouse. To avoid this, you can use partitioning to split a large ADSO into smaller sub-tables based on certain criteria, such as key fields or time intervals.
Partitioning can improve the performance and scalability of your queries by reducing the amount of data to be scanned or processed. Partitioning can also enable horizontal scaling of SAP HANA by distributing the data across different nodes or servers.
In this blog post, we will cover some of the key concepts and best practices for partitioning ADSOs in SAP BW/4HANA, such as:
- The different types and levels of partitioning that you can use for your ADSOs
- The different methods and tools that you can use to create and manage partitions for your ADSOs
- The different scenarios and considerations that you need to take into account when partitioning your ADSOs
Types and Levels of Partitioning
SAP BW/4HANA supports two types of partitioning for ADSOs: hash partitioning and range partitioning.
- Hash Partitioning: This type of partitioning distributes the data evenly across a fixed number of sub-tables based on a hash function applied to one or more key fields. Hash partitioning is suitable for scenarios where the data is not skewed or clustered by certain values or ranges.
- Range Partitioning: This type of partitioning distributes the data according to predefined ranges or intervals based on one or more key fields. Range partitioning is suitable for scenarios where the data is skewed or clustered by certain values or ranges, such as dates or regions.
SAP BW/4HANA also supports two levels of partitioning for ADSOs: first level partitioning and second level partitioning.
- First Level Partitioning: This level of partitioning applies to the whole ADSO table and defines how the data is distributed across different nodes or servers. First level partitioning is mandatory for ADSOs that have more than 2 billion records, as this is the limit for a single HANA database partition.
- Second Level Partitioning: This level of partitioning applies to each sub-table created by the first level partitioning and defines how the data is further split within each node or server. Second level partitioning is optional and can be used to improve the performance of queries that access a large amount of data within a single node or server.
The following table summarizes the types and levels of partitioning for ADSOs in SAP BW/4HANA:
| Type | Level | Description |
|---|---|---|
| Hash | First | Distribute data evenly across a fixed number of sub-tables based on a hash function applied to one or more key fields |
| Range | First | Distribute data according to predefined ranges or intervals based on one or more key fields |
| Hash | Second | Further split data evenly within each sub-table based on a hash function applied to one or more key fields |
| Range | Second | Further split data according to predefined ranges or intervals within each sub-table based on one or more key fields |
Methods and Tools for Partitioning
SAP BW/4HANA provides various methods and tools for creating and managing partitions for ADSOs, such as:
- Automatic Partitioning: This method allows SAP BW/4HANA to create partitions automatically based on the table placement configuration. Automatic partitioning is mainly used for first level partitioning to distribute the data across different nodes or servers. Automatic partitioning uses hash partitioning by default, but can also use range partitioning if specified in the table placement configuration.
- User Defined Partitioning: This method allows you to create partitions manually using SQL commands or graphical editors. User defined partitioning is mainly used for second level partitioning to further split the data within each node or server. User defined partitioning can use either hash or range partitioning depending on your requirements.
- Landscape Redistribution: This tool allows you to adapt the number of partitions for an existing ADSO based on the table placement configuration. Landscape redistribution is used when you need to change the first level partitioning of an ADSO due to changes in the data volume or system landscape. Landscape redistribution can also be used to change the type of first level partitioning from hash to range or vice versa.
The following table summarizes the methods and tools for partitioning ADSOs in SAP BW/4HANA:
| Method | Tool | Description |
|---|---|---|
| Automatic | Table Placement Configuration | Create partitions automatically based on the table placement configuration |
| User Defined | SQL Commands or Graphical Editors | Create partitions manually using SQL commands or graphical editors |
| Landscape Redistribution | Landscape Redistribution Tool | Adapt the number of partitions for an existing ADSO based on the table placement configuration |
Scenarios and Considerations for Partitioning
Partitioning ADSOs in SAP BW/4HANA can have various benefits and challenges depending on your scenarios and requirements. Here are some of the scenarios and considerations that you need to take into account when partitioning your ADSOs:
- Data Volume: The main reason for partitioning ADSOs is to handle large data volumes that exceed the limit of 2 billion records per HANA database partition. If your ADSO has less than 2 billion records, you may not need to partition it at all, unless you have other reasons such as performance or scalability.
- Data Distribution: The type of partitioning that you choose for your ADSO depends on how your data is distributed across different values or ranges. If your data is evenly distributed, you can use hash partitioning to achieve a balanced load across the sub-tables. If your data is skewed or clustered, you can use range partitioning to avoid hotspots or bottlenecks in certain sub-tables.
- Data Access: The level of partitioning that you choose for your ADSO depends on how your data is accessed by your queries. If your queries access data from different nodes or servers, you can use first level partitioning to improve the parallel processing and load balancing of your queries. If your queries access data from a single node or server, you can use second level partitioning to improve the scan speed and memory consumption of your queries.
- Data Maintenance: The number of partitions that you create for your ADSO affects the maintenance and administration of your data warehouse. The more partitions you have, the more complex and time-consuming it is to perform tasks such as activation, compression, or deletion of data. Therefore, you should avoid creating too many partitions that are not necessary or beneficial for your scenarios.
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