× The internal search function is temporarily non-functional. The current search engine is no longer viable and we are researching alternatives.
As a stop gap measure, we are using Google's custom search engine service.
If you know of an easy to use, open source, search engine ... please contact support@midrange.com.



From: Brian Piotrowski

I don't want to start a whole new flame war on the merits of SQL vs.
READ/DELETE,

Hee hee! (oiling up the torches, getting out the pitchforks)


but I wanted to get some opinions as to the best way to
tackle a problem.

I have quite a few tables that have a large number of records in them
("large" to us is 13 million). I have two methods I am currently
testing and I wanted to know which is the best method to get rid of old
records:

Method #1 - Perform a mass delete using set criteria in an SQL
statement:

Method #2 - Start at the beginning of the PF and examine each record.
Delete out those that meet the criteria:

You know me, I'm the strident voice against the overuse of SQL. However, in
the spirit of the right tool for the job, this is really the perfect problem
domain for SQL. You are talking about set processing, and SQL shines at
this.

You either have an appropriate view over the data (in the form of a logical
view or SQL INDEX) or you don't. In either case, the system will have to do
the same work: either process by key within limits if an index exists, or
else read every record and test if one doesn't. But with SQL, you will
avoid bouncing back and forth between the low-level database code and the
higher level of an HLL program. Unless I'm missing something fundamental, I
to believe that SQL will be faster (possibly MUCH faster) in this case.

Joe



As an Amazon Associate we earn from qualifying purchases.

This thread ...

Follow-Ups:
Replies:

Follow On AppleNews
Return to Archive home page | Return to MIDRANGE.COM home page

This mailing list archive is Copyright 1997-2024 by midrange.com and David Gibbs as a compilation work. Use of the archive is restricted to research of a business or technical nature. Any other uses are prohibited. Full details are available on our policy page. If you have questions about this, please contact [javascript protected email address].

Operating expenses for this site are earned using the Amazon Associate program and Google Adsense.