Compression has in general the following advantages: BW on SAP HANA: Performance of InfoCube compression; SAP. What Is an Infocube in SAP BI/BW? How To Create One? What is Infocube? Infocube is data storage area in which we maintain data which we are extracting . Posts about Infocube Compression written by Rahul Sindhwani.

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You can eliminate these disadvantages by compressing data and bringing data from different requests together into one single request request ID 0.

If you are loading historic changes to non-cumulative values into an InfoCube after initialization has already taken place using the current non-cumulative, you have to use this option.

Activities For performance reasons, and to save space on the memory, compress a request as soon as you have established that it is correct and is not to be removed from the InfoCube. A t tachments 0 Page History. If you are using an Oracle database as your infoocube, you can also execute queries on the relevant InfoCube while compression is running.

Any requests fully compressed up to now will remain compressed. Each of these requests has its own request ID, which is included in the fact table in the package dimension. Compressing one request takes approximately 2. April 26, at 6: This makes it possible to pay particular attention to individual requests.


Zero Elimination means deleting the record from the cube after compression if and only if, the entire key figures of the compression record is zero. Create a free website or blog at WordPress. You cannot run zero-elimination for Ocmpression that contain non-cumulative values.


Conclusion There are a couple of advantages and disadvantages compressing an InfoCube or not. Subsequent compression of the same InfoCube will be from the beginning again. This feature enables you, for example, to delete a request from the F-fact table after the upload. Doing a compression can have an impact on the daily business and also affects reporting during this time.

Improve performance – by compressing the fact table #SAP #BW

This unnecessarily increases the volume of data and affects system performance when you analyze data, since each time you execute a query, the system has to perform aggregation using the request ID.

If you do not want the InfoCube to contain entries with zero cpmpression for key figures in reverse posting for exampleyou can run zero-elimination at the same time as compression. This means that less data has to be read for a non-cumulative query which reduces the response time. By continuing to use this website, you agree to their use.

SAP infocube compression tables

You can choose request IDs and release them to be compressed. Yes, you can kill the compression. An InfoCube is loaded request by request, i. Improve performance further with partitioning the fact table.


When you compress, a query will read one accumulated line of records as opposed to reading each record. Nice information for fresher…. Hi Martin, Nice document. If you perform compression for a non-cumulative InfoCube, the compression time including the time to update the markers is about 5 ms per data record. You can schedule the function immediately or in the background.

During upload of data, a full request will always be inserted into the F-fact table. Those packages do not allow an aggregation and therefore each datapackage is limited within those boundaries.

For that reason bw provides a couple features that help to increase performance. For performance reasons, you should compress subsequent delta requests.

You must be absolutely certain that the data loaded into the InfoCube is correct. The data in the E fact table is compressed and occupies lesser space than F fact table. Collapse data by request id Compressing a fact table is done in the InfoCube administration and is based on the request id number. If the cube is compressed, the data ckmpression the F fact table is transferred to the E fact table.