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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Open link in a new tab. Subsequent compression of the same InfoCube will be from the beginning again. Compression of Non cumulative InfoCubes are mandatory. Yes, you can kill the compression.
April 26, at 6: One advantage of the request ID concept is that you can subsequently delete complete requests from the InfoCube. Martin Grob Post author.
This function is critical, since you cannot delete compressed data infocuube the InfoCube using its request ID. 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. When you compress, a query will read one accumulated line of records as opposed to reading each record.
During compression, these records are summarized to one entry with the request ID ‘0’. You can eliminate these disadvantages by compressing data and bringing data from different requests together into one single request request ID 0.
This makes it possible to pay particular attention to individual requests. When you load a data target, say a cube, the data is stored in infocubbe F fact table.
SAP infocube compression tables
Search or use up and down arrow keys to select an item. An InfoCube is loaded request by request, i. Depending on the datamodel of the InfoCube and the frequency of loads as well as the content of the loaded data this can have a significant impact on the datavolume.
The data in the E fact table is compressed and occupies lesser space than F fact table. Hi Martin, Nice document.
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.
Comments Leave a Comment Categories Uncategorized. Improve performance further with partitioning the fact table. You must be absolutely certain that the data loaded into the InfoCube is correct. By choice the compression can be all or only part of the requests that have been loaded.
SAP infocube compression tables
Index, Primary Index The primary index is created automatically when the table is created in the database. Purpose To explain the concept and reasons behind compressing requests in InfoCubes Overview InfoCubes should be compressed regularly.
Every InfoCube has a datapackage dimension that holds the request id. 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. Can I kill a compression?
Features You can choose request IDs and release them to be compressed. 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 Ocmpression.
Infocube Compression | SAP BW Overview
Compressing a fact table is done in the InfoCube administration and is based on the request id number. Any request mid-compression will be rolled back. If you perform compression for a non-cumulative InfoCube, the compression time including the time to update the markers is compresaion 5 ms per data record.
Can comprezsion compression be run in a way, that reporting stays available while it is executed? To find out more, including how to control cookies, see here: