Big data companies frequently contact us seeking solutions to their SAP database performance woes, even those with modern applications that allow for greater scalability, with their three-tier client/server environments that are designed to lessen the database workload. If your database’s capabilities have been stretched to its limits only to remain the weakest part of your IT system, and you need solutions to managing data growth, then you have three options:
Unnecessarily expanding your systems can be costly, and deleting the data is frequently impractical due to the need for read access to individual data objects. Therefore, the solution is to relocate the data in such a way that it remains accessible when needed. Data archiving is less risky than haphazardly deleting your unused or infrequently accessed data, and a smarter long-term storage solution than simply expanding your systems.
Data archiving shrinks storage requirements by removing unused or infrequently accessed data from the database, and archiving it to more cost-efficient media. When performed routinely, data archiving plays a significant role in controlling the growth of SAP data, resulting in a decreased total cost of ownership (TCO).
In addition to these benefits, companies frequently deploy data archiving to remedy system performance issues, mistakenly signing off on archiving projects under the assumption that improved performance is a given. However, archiving for improved system performance without a proper strategy in place will likely lead to disappointing results at best. It is not uncommon for a data archiving project that results in the significant reduction of data in the system to keep performance levels the same as they were prior to archiving.
So how does one improve system performance by way of an SAP data archiving project?
It’s a common conclusion that many companies reach in thinking that SAP system performance inherently improves once data archiving lessons the burden on the data system. But does less work necessarily equate to increased performance?
It is safe to say that:
This ensures that data blocks containing old data will not require accessibility in daily operations and will not affect the I/O rate. Both table and index blocks are vulnerable to a mixture of new and old data. Old data shouldn’t be migrated to the application; therefore, it has no effect on system performance.
When archiving for performance, one of the most important factors to consider in selecting which data to archive first, is index layout. This is due to the fact that every system creates indexes upon data insertion, and the index type used to access data plays a role in the I/O rate.
Table fragmentation can substantially affect your system performance gains derived from data archiving. Before you can maximize performance, you must identify data blocks containing both new and old data. Blocks of unused data will only take up space in the database.
These mixed data blocks can be found. If during the insertion of new data, table blocks that are not completely empty are being reused, then you have identified mixed data. It’s worth noting that if your company has never archived or deleted, there is no way that table blocks can be fragmented.
Mixed data occurs in index blocks when the index is not chronologically sorted. In this circumstance, the position in the index and subsequently the data block which the entry is inserted is dependent upon the order of the indexed fields.
Index data can be sorted in two ways:
In order to enjoy maximum performance gains from your SAP data archiving project, look for the statements that yield high I/O rates for your database in order to improve performance. Data archiving is the only means to reduce rates if your high I/O yielding statements are supported by a non-chronological index.
Understand that improvement in system performance hinge largely in part on the percentage of the chronologically sorted to non-chronologically sorted indexes. It’s also important to take into account the quantity of accesses executed on specific data. Naturally, these factors vary considerably from table to table and system to system.
As previously noted, system performance is most impacted by identifying and archiving tables with the highest I/O rates that use non-chronologically sorted indexes. Therefore, if you intend to improve SAP system performance, begin your project with the tables that show the highest I/O rate, rather than the common approach of archiving the largest system tables first.
While data archiving can play a significant role in improving SAP system performance, it is imperative to understand how to identify and target data for archiving in order to realize performance goals. If you are considering embarking on an archiving project for performance-enhancing results, it is recommended that you review your indexes, particularly those that are non-chronologically sorted in order to set attainable expectations. Many properly maintained SAP systems have unidentified quantities of data that fit company parameters for transfer to long-term storage solutions. Archiving such data can have a palpable impact on overall performance. You may be surprised by what opportunities you uncover.
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Unnecessarily expanding your systems can be costly, and deleting the data is frequently impractical due to the need for read access to individual data objects.