Hyperion Smart View Optimization

March 3, 2018 | Author: Parmit Choudhury | Category: Microsoft Excel, Application Software, Data Management, Areas Of Computer Science, Digital Technology
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Hyperion Smartview Optimization...

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Hyperion Smart View Optimization

Oracle’s Hyperion Smart View product is great for retrieving data from Essbase, Planning, or HFM applications, but most users have experienced issues with retrieve performance at one point or another. The following is a list of tips and tricks that will help to increase Smart View performance.  Retrieval time will be fastest when using a new Excel sheet. Every time we perform a Refresh, Smart View caches the activity (this is why we can press “Undo” so many times). Repeatedly running retrieves off of the same Excel sheet will therefore cause performance to slowly diminish over time. If performance becomes noticeably slower after using the same sheet for an extended period of time, open a blank Excel workbook and recreate the query.  Select the option to Use Excel Formatting. Without this option, Smart View will reformat each cell based on the grid operations we perform. It will also mark cells as “dirty” each time we change data values. These activities add system overhead to all Refreshes, making them take longer.

 The most efficient performance will result from small, focused queries on a specific subset of data. Zooming in on extremely large dimensions will cause slow performance. If we absolutely must zoom in on larger dimensions, suppressing rows that have no data or zero data will help.

 Keeping the default options for displaying No Data, No Access, and Invalid cells will decrease the time needed for a retrieve. The difference in retrieval timing is much more noticeable when using very large (10,000+ rows) queries.

 The bigger our Excel workbook, the slower our Smart View queries will run. This is why running a query in an Excel workbook that has many other worksheets can take a long, long time.  Retrieval performance will be optimized if the Smart View query is the only tab in the workbook. If other worksheets are being used, the overall size of the file itself will have the biggest impact on performance. Queries used in larger files (over 10 MB) are very likely to run slowly.  Turn off the preserve formulas option when retrieving against an ASO Essbase cube. This has been known to make retrieves take much longer than normal. Interestingly enough, it also can dramatically increase the size of the Excel file itself when this setting is turned on. It does not seem to do this against a BSO or Planning cube.

 The Excel Auto Recover option can create performance issues or even cause the query to crash. For example, if the Auto Recover option is set to every 3 minutes, a query that takes longer than 3 minutes to retrieve will cause Excel to crash. Disable this option if we are using large queries.

 If we have users that rely on Smart View to pull data from our Essbase and Planning application, many of them may have large spreadsheets. One way to improve the perception of the performance of Essbase is the method in which Smart View (client side) communicates with the server.  APS [Analytic Provider Services], Planning, and HFM have the ability to take advantage of compression during the communication process. When large queries, retrieving and submitting data, are initiated, the performance can be significant.  The default compression settings for APS and Planning are not turned on.  Find the essbase.properties file on the APS server and change it to false. The path to this file is different in versions 9 and 11. In 11, the path is \Products\Essbase\aps\bin. smartview.webservice.gzip.compression.disable=false  Open the Hyperion Planning application and change the SMARTVIEW_COMPRESSION_THRESHOLD in the System Properties (Administration/Manage Properties – System Properties tab) to a value not less than 1.  This threshold is the minimum size of the query in which compression will be used. So, a value of 1000 would mean compression would be used for anything greater than 1,000 bytes.  For smaller queries, compression may not be necessary. It may even decrease performance because of the overhead to compress and uncompress the data.

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