21 September, 2018
Essbase dimensions are classified as standard dimensions and attribute dimensions . standard dimensions are further classified into sparse and dense dimensions. For every unique sparse member combination , an index will get formed and block will be form for the same combination Number of potential indexes=number of potential blocks = number of members from one sparse dimension with Number of members from other sparse dimension and so on In the below example , assi9gned products is sold on one month and it is not sold in other months , we have two measures , sales and this company cells the products in all states . sample data Jan2007 coke ap sales 1000 feb2007 pepsi ap sales 1000 mar2007 mdew ap sales 1000 apr2007 orange ap sales 1000 may2007 mango ap sales 1000 imagine the same data UP,TN DELHI,. So there are 40 records in the source file . MARKET&MEASURES ARE DENSE DIMENSIONS (ASSUME) PRODUCT&TIME ARE SPARSE DIMENSIONS (ASSUME) THERE ARE 5 unique sparse combinations (jan 2007, coke feb 2007 pepsi Mar2007 mdew Apr2007 mango May2007 , orange) Potential indexes are 25 . potential blocksare25 Actual indexs are 5, actual blocks are 5
data exits for majority of the member combinations . dense dimensions with member combination . dense dimensions effect the size of block. Number of cells =multiply the number of members one dense dimension with number of members from other dense dimension and so on Each cell occupies 8 bytes Block size = number of cells *1. The ideal block size 8k to 100k Dense dimension will decide the number of cells and block size.in the above example let’s assume to members from measures dimension and 4 members from market dimension . there will be 8 cells per block and each cell occupies 8 bytes . the total block size is 64 bits
The dimensions are characteristics of other standard dimensions . attribute cannot exits on its own always associated with a base standard dimension . attributes cannot exits on it own . always associated with a base standard dimension . attributes are always sparse of nature . we don’t load data for attributes member combinations . we load data in standard number combination .
To create attribute dimension: Select the lost dimension in the outline and select “ATTRIBUTE” from the tool bar. To associate to a base member: Select a standard space member, Right click and click Edit member properties and click attributes tab. Select the attribute dimension from the right hand side window and click assign. Click ok. To Associate attribute member to base members: Right click on the level 0 member from standard space dimension (from the above step). Click edit member properties. Click associate tab. Select level 0 members from right hand side and select again. Click ok. Creating Attribute members using Rules files: This rules file create members under base dimension, creates member under attribute dimension and also associates attribute members to base members. SODA COKE COKE-1L 1L SODA COKE COKE-2L 2L SODA PEPSI PEPSI-1L 1L SODA PEPSI PEPSI-2L 2L
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