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Limiting the amount of data to display

bmario

Hello!

Currently, the application I'm working on allows the user to preview a report, the idea is that the user can have a glimpse of the report before actually generating a pdf file of 50 pages or more, like for example the first page. I know I can render one page at a time given an rptdocument but I think that makes the preview option really expensive since I need to pretty much generate the whole report and then render one page of it.

I was wondering if there is a way of limiting the amount of pages of a report when it is being generated, like passing a flag parameter for example. I know that I could limit the amount of rows processed by the report if I'm using a scripted dataset with (i.e. with a counter), but can I do the same with another type of dataset? Is there a more generic way to do this? like limiting the amount of rows a table can display for example? or specifically saying how many pages I want the report to have no matter how many data I may end up not displaying?

Thanks

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Hans_vd

Hi Mario, 
 
Let's say you have a boolean parameter smallReport 
Now you can put this small piece of code in the beforeFactory event of the report: 
<pre class='_prettyXprint _lang-auto _linenums:0'>if (params["smallReport"])
reportContext.getReportRunnable().designHandle.getDesignHandle().findDataSet("your_dataset_name").setRowFetchLimit(10);</pre>
 
So that when smallReport evaluates to true, only 10 rows will be fetched. 
 
Hope this helps 
Hans

Yaytay

<blockquote class='ipsBlockquote' data-author="'Hans_vd'" data-cid="94122" data-time="1326487383" data-date="13 January 2012 - 01:43 PM">
<pre class='_prettyXprint _lang-auto _linenums:0'>if (params["smallReport"])
reportContext.getReportRunnable().designHandle.getDesignHandle().findDataSet("your_dataset_name").setRowFetchLimit(10);</pre></blockquote>
 
Be warned that this approach may, depending on your data source/set, not be any quicker than processing the unlimited dataset - i.e. a query that sorts by an aggregate has to process all of the data no matter how many rows are returned. 
An alternative approach, for a preview, would be to replace the data set (and possibly even the data source) with a simpler one (possibly with cached or even fixed data if that's acceptable). 
 
Jim

bmario

<blockquote class='ipsBlockquote' data-author="'Yaytay'" data-cid="94236" data-time="1326693186" data-date="15 January 2012 - 10:53 PM">
Be warned that this approach may, depending on your data source/set, not be any quicker than processing the unlimited dataset - i.e. a query that sorts by an aggregate has to process all of the data no matter how many rows are returned. 
An alternative approach, for a preview, would be to replace the data set (and possibly even the data source) with a simpler one (possibly with cached or even fixed data if that's acceptable). 
 
Jim </blockquote>
 
Oh, I thought it was what I needed. Still is worth a try and hopefully it won't have memory problems when processing really large amounts of data. Can I replace the dataset and datasource in the report? Doesn't that give trouble with the bindings? 
 
Thanks both of you for your reply

Yaytay

<blockquote class='ipsBlockquote' data-author="'bmario'" data-cid="94260" data-time="1326745321" data-date="16 January 2012 - 01:22 PM">
Oh, I thought it was what I needed. Still is worth a try and hopefully it won't have memory problems when processing really large amounts of data. Can I replace the dataset and datasource in the report? Doesn't that give trouble with the bindings? 
 
Thanks both of you for your reply

</blockquote>
 
setRowFetchLimit should absolutely be the first thing you try, I guess all I'm saying is make sure you check that it does have the effect you want 'cos there are circumstances in which it won't. 
 
You can replace anything at all in the report, but some things are simpler than others

All the reports I run have their data source swapped at run time, and that's quite easy to achieve. There are ways to replace the dataset too, but they might need a bit more thought. 
One approach is to put the dataset in a library then swap the library - as long as the two datasets have the same metadata this will work cleanly.