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MySQL Partitioning and its Confusing Syntax
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While looking at partitioning I recently made a mistake which I guess can happen to others. Often this is due to not fully reading the documentation or scanning it too quickly and misunderstanding what’s being said.

So this post is to complain about the MySQL partitioning syntax and to warn others who may easily make the same mistake without realising.

First we probably need to ask why we are partitioning a table in the first place. The main reasons for this are I think:

  • to improve query performance
  • to reduce individual .ibd file sizes for large tables (if using innodb_file_per_table)

In my case I wanted to do both. I had a several tables which store a large number of rows (batches of data) based on an incremental batch number. One of these tables was around 40 GB and had about 500,000,000 rows in it.  When processing

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Data Warehousing Best Practices: Comparing Oracle to MySQL pt 2
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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

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The replication poll and our plans for the future
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We've been running replication poll and we've got some answers, so I thought I would comment a little on the results of the poll and what our future plans with respect to replication is as a result of the feedback. As I commented in the previous post, there are some items that require a significant development effort, but the feedback we got helps us to prioritize.

The top five items from the poll above stands out, so I thought that I would comment on each of them in turn. The results of the poll were (when this post were written):

Online check that Master and Slave tables are consistent 45.4% Multi-source replication: replicating from several masters to one slave 36.3%

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