SAP HANA News by XLC
When it comes to optimizing SAP HANA, the balance between performance and cost efficiency is critical. I am happy to share a success story where we used the Native Storage Extension (NSE) to significantly optimize memory usage while being able to adjust the sizing at the end.
The Challenge: Our client was operating on a 4 TB memory SAP HANA system, where increasing data loads were driving up costs and memory usage. They needed a solution to right-size their system without compromising performance or scalability. The client wanted to use less hardware in the future.
The Solution: We implemented NSE to offload less frequently accessed data from memory. The activation was customized based on table usage patterns:
6 tables fully transitioned to NSE
1 table partially transitioned (single partition)
1 table transitioned by specific columns
SAP NSE was introduced with HANA 2.0 SPS04 and based on a similar approach like data aging. Data aging based on a application level approach which has a side effect if you are using a lot of Z-coding. You have to use special BADI's to access the correct data. This means you have to adapt your coding if you are using it for Z-tables or using not SAP standard functions for accessing the data in your Z-coding. In this blog we will talk about the technical aspects in more detail.
The SAP Enterprise Cloud Services Private Cloud Customer Center (PC3) - a new digital delivery engagement model dedicated to manage service delivery for RISE with SAP S/4HANA Cloud, private edition customers.
Proactive maintenance for SAP RISE will start now in 2025 with minor tasks like updating SPAM/SAINT and ST-PI / ST-A/PI. For those companies which are familiar with frequent maintenance windows, they are good to have such time frames to hold the systems up-to-date and secure. However, for larger companies where such frequent maintenance windows are not common because every minute of downtime is costly and may only really be necessary once, the situation is quite different.
Dynamic Aging makes it possible to automatically manage at which point in time older partitions can be moved to the 'warm' data store.
The data in a new OTHERS partition is 'hot' data, that is, stored in memory with the load-unit attribute implicitly set to COLUMN LOADABLE. As an extension of the Dynamic Range Partitioning feature Dynamic Aging makes it possible to automatically manage when older partitions can be moved to the 'warm' data store (Native Storage Extension) with the load-unit attribute for the partition set to PAGE LOADABLE. Warm data is then stored on disk and only loaded to memory when required.
Dynamic Aging can be used with both THRESHOLD mode (defining a maximum row count number in partition OTHERS) and INTERVAL mode (defining a maximum time or other numeric interval between each new partition). For example, for a partitioned table which is managed by dynamic partitioning and containing date/time information, you can specify an age limit (for example six months) so that when data in an ol
You can create partitions with a dynamic others partition by including the DYNAMIC keyword in the command when you create the partition, this can be used with either a THRESHOLD value to define a maximum row count number or an INTERVAL value which can be used to define a maximum time or other numeric 'distance' value. The partition can be either a single level or a second level RANGE partition and dynamic ranges can be used with both balanced and heterogeneous partitioning scenarios.
For heterogeneous partitioning schemas Dynamic Range Partitioning is available to support the automatic maintenance of the 'others' partition.
When you create an OTHERS partition there is a risk that over time it could overflow and require further maintenance. Using the dynamic range feature the others partition is monitored by a background job and will be automatically split into an additional range partition when it reaches a predefined size threshold. The background job also checks for empty partitions and if a range partition is found to be empty it is automatically merged to neighboring empty partitions (the others partition is never automatically deleted).
A success story regarding BW/4HANA and different data tiering and optimization methodes.
1) Removed overhead in key attributes which reduced the PK size (often more than 50% of the overall table size)
2) optimized the partitioning design
3) used NSE for write optimized ADSOs
4) introduced NSE for several ADSOs
5) optimized usage of inverted individual indexes
ACDOCA table growth - how to handle it in a S/4HANA system
SAP HANA 2.0 SPS08 Roadmap and features Q4 2024