At Kscope this year, I attended a half day in-depth session entitled Data Warehousing Performance Best Practices, given by Maria Colgan of Oracle. My impression, which was confirmed by folks in the Oracle world, is that she knows her way around the Oracle optimizer.
See part 1 for the introduction and talking about power and hardware. This part will go over the 2nd “P”, partitioning. Learning about Oracle’s partitioning has gotten me more interested in how MySQL’s partitioning works, and I do hope that MySQL partitioning will develop to the level that Oracle partitioning does, because Oracle’s partitioning looks very nice (then again, that’s why it costs so much I guess). Read the rest of this entry . . .
At Kscope this year, I attended a half day in-depth session entitled Data Warehousing Performance Best Practices, given by Maria Colgan of Oracle. My impression, which was confirmed by folks in the Oracle world, is that she knows her way around the Oracle optimizer.
These are my notes from the session, which include comparisons of how Oracle works (which Maria gave) and how MySQL works (which I researched to figure out the difference, which is why this blog post took a month after the conference to write). Note that I am not an expert on data warehousing in either Oracle or MySQL, so these are more concepts to think about than hard-and-fast advice. In some places, I still have questions, and I am happy to have folks comment and contribute what they know. Read the rest of this entry . . .
This is the 182nd edition of Log Buffer, the weekly review of database blogs. Make sure to read the whole edition so you do not miss where to submit your SQL limerick!
This week started out with me posting about International Women’s Day, and has me personally attending Confoo (Montreal) which is an excellent conference I hope to return to next year. I learned a lot from confoo, especially the blending nosql and sql session I attended.
At the March Boston MySQL User Group meeting, Jacob Nikom of MIT’s Lincoln Laboratory presented “Optimizing Concurrent Storage and Retrieval Operations for Real-Time Surveillance Applications.” In the middle of the talk, Jacob said he sometimes calls what he did in this application as “real-time data warehousing”, which was so accurate I decided to give that title to this blog post.
This article will discuss how to make many-to-many relationships in data warehousing easily queried by novice SQL users using point-and-click query tools.
This is a big problem with Oracle Discoverer-like tools where the metadata layer is basically a set of pre-joined tables from which the user simply clicks on columns and hits the run button. You can create custom complex queries that they can run, but then every query is custom, which defeats the purpose of the tool in the first place.
The design goal is to create a structure that is simple for the end user and which normally translates to something as flat as possible. This article will go through the different methods of implementing many-to-many relationships, and look at their effect on query complexity, especially for someone who use a tool that hides the SQL.
