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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For performance reasons, you should compress subsequent delta requests. By choice the compression can be all or only part of the requests that have been loaded.

InfoCube Compression in SAP BI

With non-cumulative InfoCubes, compression has an additional effect on query performance. This site uses cookies.

This function is critical, since you cannot delete compressed data from the InfoCube using its request ID. 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. October 11, at 8: Subsequent compression of the same InfoCube will be from the beginning again. comprezsion

Compression in BW InfoCubes – SAP NetWeaver Business Warehouse – SCN Wiki

If you do not want the InfoCube to contain entries with zero values for key figures in reverse posting for exampleyou can run zero-elimination at the same time as compression. When you load a data target, say a cube, the data is stored in the F fact table. Open link in a new tab. When you compress, a compfession will read one accumulated line of records as opposed to reading each record.


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. This feature enables you, for example, to delete a request from the F-fact table after the upload.


Comprsssion a free website or blog at WordPress. If the cube is compressed, the data in the F fact table is transferred to the E fact table.

Compressing the fact table is one option that optimized the access to basis infocubes. Any requests fully compressed up to now will remain compressed. One advantage of the request ID concept is that you can subsequently delete complete requests from the InfoCube.

Compressing one request takes approximately 2. What happens when we compress InfoCube? Purpose To explain the concept and reasons behind compressing requests clmpression InfoCubes Overview InfoCubes should be compressed regularly.

During compression, these records are summarized to one entry with the request ID ‘0’. This allows bw to store the data in a granularity which is not necessarily required from a business perspective. When you load data into the InfoCube, entire requests can be added infkcube the same time. You cannot run zero-elimination for InfoCubes that contain non-cumulative values.


Compression – SAP NetWeaver Business Warehouse – SCN Wiki

In this case, the entries where all key figures are equal to 0 are deleted from the fact table. If you do not use this option, the results produced in the query are incorrect. Compression of Non cumulative InfoCubes are mandatory. For that reason bw provides a couple features that help to increase performance. So in short Compression: Martin Grob Post author.

Those packages do not allow an aggregation and therefore each datapackage is limited within those boundaries. This makes it possible to pay particular attention to individual requests. To achieve this each InfoCube consist out of two two fact tables one with a request id and one without it.

Zero Elimination means deleting the record from the cube after compression if and only if, the entire key figures of the particular record is zero.

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