Databases
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    <p>30,000 records is nothing. You should be able to perform a full dump export/import of a database that size in less than 4 seconds, so something seems not right :)</p> <p>If you can provide us with some information about the tables, their relationships and what your report is about, I'm sure we can offer some specific advice on how to improve things.</p> <p><strong>Some general advice on performant reports:</strong> Don't use an ORM-tool for reports, unless the report requirements are very trivial (in which case it would be called a list, not a report). Go for a hand crafted SQL with attitude. </p> <p>Don't listen to the Zealots who forbid you to use vendor specific SQL extensions. You paid (moneywise or time spent) for this specific dbms. <strong>Use it to its fullest!</strong> </p> <p>Do as much work as humanly possible inside the database. (When using the extensions, this becomes much easier). Databases are built for searching, sorting and aggregating data, and they do it very well. A table with 1,000,000 rows at an average row size of 200 bytes will consume less than 200 MB. Assuming that the disk subsystem can deliver 50mb/s, it would take 4 seconds to perform a SUM(value) over the entire table. That's the theoretical upper limit. If you need more, you have to pre-compute data so that the working set becomes smaller (google for "aggregate" and "rollup").</p> <p>This potentially means writing longer and more complicated queries. Long complex SQL often confuses the optimizer so that it comes up with a suboptimal execution plan. Solving this usually requires solid experience with the specific dbms product. Having a normalized database with full referential integrity and constraint checking makes this a less common issue though. </p> <p>Don't run queries in a loop. If your query takes 1 ms to complete, it does not take 1 second to run 1000 queries. Each call has to "pay" for network delay, marshalling/unmarshalling the data, potential locking issues, parsing, fetching, etc.</p> <p><strong>(updated)</strong></p> <p>If the expected (and acceptable) runtime is more than a second or so, you can afford to lookup some values and provide them as literals to help the optimizer. This can be used to remove non-correlated subqueries and joins.</p> <p>Keep user-defined functions to a minimum. They confuse the optimizer and often forces row-processing (which is non-scalable).</p>
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    1. COGreat tips. I will definitely take onboard what you have said and I will create another post to open up a discussion about design considerations regarding my DB archiecture. Many thanks.
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Detail views are divided into sections. All the information in the data section comes from columns in the selected row. The other sections display data from other, related rows.

Related data can be related in a to-one or a to-many fashion. Captions of data related in a to-many fashion link to a list view showing a filtered view of the table.

Try moving around until you find a non-empty to-many entry and click on the label to get to one. You can move back to the root by clicking on the database name in the header.

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