Performance

A variety of functions are provided to help you improve the performance of your BW system. The main functions are:

• Integration with In-Memory Technologies

  In-Memory technologies provide you with a particularly effective way of processing scenarios, especially when they are complicated and have unpredictable query types, large data volumes and high query frequency.

  • If you use a database to persist data, you can make it possible to access the data for a BW object faster by storing this data as an index in SAP NetWeaver Business Warehouse Accelerator. It is available with installed and preconfigured software on specific hardware.
  • Alongside the performance benefits it offers, using the database for data persistence offers further benefits when executing analysis and planning scenarios. In particular, you do not need a SAP NetWeaver BW Accelerator to improve performance.
• Aggregates

  Relational aggregates are another way in which you can improve the read performance of queries when reading data from an InfoCube. The data in an InfoCube is saved in relational aggregates in aggregated form. Relational aggregates are useful if you want to improve the performance of one or more specific queries, or make specific improvements to reporting with characteristic hierarchies.

  Caution

  Note that the system does not support using aggregates if you use your BW system with the SAP database, as aggregates would not improve performance in this case.

• Non-Cumulatives

  A non-cumulative key figure is modeled in BW using the corresponding field for the non-cumulative value change or the corresponding fields for inflows or outflows. You can determine the current non-cumulative or the non-cumulative at a particular point in time. To do this, you use the current, end non-cumulative and the non-cumulative changes and/or the inflows and outflows.

  The purpose of the special folder for non-cumulative key figures is to optimize data transport into the BW system, to retain data, and to access the database when evaluating in reporting in the BW system.

• OLAP Cache

  The OLAP Processor accesses two types of cache, the local cache and the global cache.

  At runtime, all drilldown states of the query - from a given calculation level - are cached locally to start with and then stored globally if required. The entries in the local cache are generated from the local runtime (cache) objects. Various cache modes are supported for the global cache. These differ in terms of their persistence medium - the storage medium - and in the structure of the cache hierarchy that OLAP Processor uses to locate the individual objects in the cache. In the default setting, cache mode Query Aggregate (5) is set (also known as BLOB/Cluster Enhanced). Cache mode Main Memory Without Swapping (1) is the second most common cache mode.

  The OLAP Cache Monitor can be monitor query performance and the cache parameter settings for results and navigation states of queries calculated using the OLAP Processor.