Maintaining InfoCube Data - SAP BW

To answer the other questions raised at the beginning of this chapter,from Administrator Workbench right-click the concerned InfoCube (IC_NEWBC2 in our example),and then select Manage. Screen appears.

Screen contains six areas:

  • Contents,where we can display and delete InfoCube data
  • Performance,where we can check,delete,and create indices and statistics
  • Requests,where we can manage individual data load requests
  • Rollup,where we can roll up data per load requests into aggregates
  • Collapse,where we can compress data in multiple load requests into a single request
  • Reconstruct,where we can reconstruct the InfoCube using load requests in PSA

We will discuss each of these topics in turn.

InfoCube Contents:
The first tab in Screen is Contents. Here we can display and delete the InfoCube's contents.

Work Instructions:
Step 1. To display the InfoCube contents,clickinfo-cube Content.
Manage Data Targets

Step 2. In Screen,we specify conditions regarding what contents to be displayed. Here are some options:

  • Choose Do not use any conversion to display the data in the database formats.
  • Choose Use mat. aggregates to display the data from an aggregate instead of the fact table if an appropriate aggregate exists.
  • Choose Use DB aggregation to allow aggregation on the fields that are not the selection conditions.
  • Choose Output number of hits to add a new column in the display to show how many records in the fact table are used to produce each display row.
  • Choose Display modified structures to display the M version master data. Use this option to check how the result would look in BEx should the characteristic data be activated.

Info cube browser:Info cube

Step 3. To delete data from the InfoCube,clickselective-deletion.
Manage data targets

Step 4. In this pop-up window,we can specify the data to be deleted and how to delete them by clickingdeletion-selection .
Selective deletion for Info cube IC_NEWBC2

Step 5. Besides the conditions used to specify the data to be deleted,in this window,we can also do the following:

  • Select Restructuring aggregates to rebuild aggregates after the data are deleted.
  • Select Parallelity deg. with recreati field to enter the number of parallel processes to be used in reconstructing the table.
  • Select Switch off logging when recrea to improve performance without logging the changes.
  • Select Display generated report to display the ABAP program used to delete the data.

Deleting Entries from the fact table for info cubes

Indices and Statistics:
The second tab in Screen is related to performance. Here we can check,delete,and create indices and statistics.

Work Instructions
Step 1. The status lights on the right should be green. If no index/ statistics data exist,the status lights will be red.
To delete indices from the fact table,clickdeletion-index.
Manage data targets

Step 2. Now the left status light turns red. To create the indices,clickrepair-indexes.
Manage data targets

Step 3. ClickClick to continue.

Step 4. Click Clickto continue.
Index recalculation is running

Step 5. Depending on the size of the InfoCube,it may take a while for the status light to turn green.
To improve data loading performance,it is a good practice to delete the indices,load the data,and then recreate the indices. To automate this job,click create-index.
Manage data targets

Note:Rolling up aggregates will automatically repair the aggregates' indices.

Step 6. Check all options,and then click Clickto save the settings and continue.
Create Index for Info cube Ic

The next time when we load data into this InfoCube,we will receive a message like the one in Screen To continue the data loading operation,clickYes.

In the same way,we can check,delete,and create the BW statistics.

Step 7. If the DB statistics status light is red,clickstatistics.
Manage data targets

Step 8. ClickClick to continue.

Step 9. ClickClick to continue.
DB Statistics recalculation running

Step 10. Depending on the size of the InfoCube,it may take a while for the status light to turn green.
Each time when new data are loaded into the fact table,statistics should be refreshed. To automate this process,clickcreate-statistics.
Manage data targets

Step 11. Check both options,and then clickClick to save the settings and continue.
From now on,the DB statistics will be refreshed after each data load and each delta load.
Create Statistics for Info cube

Data Load Requests
The third tab in Screen,Requests, allows us to manage individual data load requests.
In BW,each data load from BW Scheduler counts as a request and is assigned a unique request number consisting of 30 characters. This request number is stored as an integer value called a request ID,in the data packet dimension of the InfoCube.As an example,Screen displays the contents of the data packet dimension table,/BIC/DIC_NEWBC2P. It shows the relationships among the request IDs (473, 474, and 479) and DIMIDs (1, 2, and 3).
Data Load Requests

The DIMIDs (41,42,and 43) are used in the fact table /BIC/FIC_NEWBC2 for the request IDs.
Data browser table/BIC/FIC_NEWBC2 Select Entries

As shown in Screen,if an InfoCube has aggregates,then a request is not available for reporting until it is rolled up into the aggregates.
To delete a request from the InfoCube,clickdelete . If the request has been rolled up into an aggregate or compressed,however,then you cannot delete it. If it has been rolled up,then the aggregate must be deactivated first. If it has been compressed,then all data in the fact table must be deleted first.
Manage data targets

BW provides a useful function that allows us to check whether one data load request overlaps with another. The following is an example for request 474.

Step 1. Select request 474,and then clickclick.
Manage data targets

Step 2. A new session window opens and displays the request's 30-character request number,REQU_3I4VT73UXJDCQIO47YE4Q4QAI.

Click Clickto check the overlapping.
Request Check on Consistency/Overlapping of the data selections

The result contains information about the overlapping. If overlapping is present,the result also tells us whether we can delete the request (Screen).
Request Check on Consistency/Overlapping of the data selections

Aggregate Rollup:
The fourth tab,Rollup,in Screen deals with the aggregate rollup. When we roll up data load requests,we roll them up into all the aggregates of the InfoCube.

Work Instructions:
Step 1. To roll up request 479,enter 479 into the Request ID and then clickexecute . BW will roll up request 479 and other requests below 479 into the aggregates.
Manage data targets

Returning to the Requests tab and clickingResult to refresh the screen,notice that request 479 has been rolled up. Now it is available for reporting.
Manage data targets

InfoCube Compression:
The fifth tab in Screen,Collapse,focuses on the InfoCube compression.Each InfoCube has two fact tables: the F fact table and the E fact table. We load data into the F fact table,where the data are grouped according to the individual load among requests. The F table allows us to check for overlapping requests and to delete unnecessary requests.

The F fact table degrades query performance,however. When executing a query,the OLAP processor must aggregate key figures to eliminate the request information in the data packet dimension.To overcome this drawback,BW allows us to aggregate the F fact table and save the aggregated data in the E fact table in a process called the InfoCube compression. After the InfoCube compression,the OLAP processor will go to the E fact table to retrieve data. The procedure for performing this compression appears next.

Work Instructions:
Step 1. To compress request 479,enter 479 into the Request ID and then clickrelease. BW will compress request 479 and other requests below 479.

Note:To delete records whose key figures are all 0,select the With zero elimination option.
Manage data targets

After the compression,the F fact table /BIC/FIC_NEWBC2 contains no more data. Instead,the compressed data now appear in the E fact table,/BIC/EIC_NEWBC2. The E fact table has only 24 records of data,instead of 72 as shown in Screen. The data packet dimension column KEY_IC_NEWBC2P contains only zeros.
Data Browser : Table /Bic/EIC_NewBC2 select entries

Note:For performance and disk space reasons,it is recommended that you roll up a request as soon as possible and then compress the InfoCube.

To roll up or compress a request automatically when data are loaded into an InfoCube,select the Automatic request processing… item from the Environment menu on the InfoCube definition screen.
Manage data targets

In the pop-up window (Screen),check all options and clicksave.

Caution:The order in which requests are rolled up and compressed is very important. After their compression into the E table,requests are no longer available in the F fact table and therefore cannot be rolled up into the aggregates. If we roll up requests after compressing them,the status under the Requests tab will indicate these requests are now in the aggregates—that is not true.

To delete a compressed request,we must either delete all of the E fact table data or use the request reverse posting function is screen by clicking.
Mainteinance of the automatisms

InfoCube Reconstruction:
The last tab in Screen,Reconstruct,allows us to reconstruct InfoCubes. Here we can reinsert the requests in PSA back into the InfoCube. The procedure follows.

Note:Using this feature,we can also fill other InfoCubes with the requests,as long as the requests remain in PSA. This feature is particularly useful when the requests call for delta loads because we cannot request the same delta loads again from the source system.

Work Instructions:
Step 1. Repeat the Screen step to delete the IC_NEWBC2 data. BW removes all three requests (473,474,and 479) from Screen.
To reconstruct the InfoCube using the requests (473,474,and 479) that remain in PSA,select the requests and click.
Manage data targets

Returning to the Requests tab and clickingResult to refresh the view,we see that the three requests have returned to the InfoCube. They are not rolled up and compressed,but are available for reporting.
Manage data targets

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