Search Results for: data retrieval mysql

Django with time zone support and MySQL

This is yet another story of Django web-framework with time zone support and pain dealing with python datetimes and MySQL on the backend. In other words, offset-naive vs offset-aware datetimes. Shortly, more about the problem. After reading the official documentation about the time zones, it makes clear that in order to reflect python datetime in […]

MySQL and Hadoop integration

Dolphin and Elephant: an Introduction This post is intended for MySQL DBAs or Sysadmins who need to start using Apache Hadoop and want to integrate those 2 solutions. In this post I will cover some basic information about the Hadoop, focusing on Hive as well as MySQL and Hadoop/Hive integration. First of all, if you […]

Active Cache for MySQL

One of the problems I have with Memcache is this cache is passive, this means it only stores cached data. This means application using Memcache has to has to special logic to handle misses from the cache, being careful updating the cache – you may have multiple data modifications happening at the same time. Finally […]

MySQL Architecture meeting at Google

Friday after MySQL Users Conference we had a smaller meeting at Google campus to talk about MySQL architecture mainly focusing on storage engine vendors and other extension areas. It was very interesting to see all these storage engine interface extensions which are planned for MySQL 6.0 and beyond – abilities to intercept query execution or […]

MySQL Blob Compression performance benefits

When you’re storing text of significant size in the table it often makes sense to keep it compressed. Unfortunately MySQL does not provide compressed BLOB/TEXT columns (I would really love to have COMPRESSED attribute for the BLOB/TEXT columns which would make them transparently compressed) but you well can do it yourself by using COMPRESS/UNCOMPRESS functions […]

Why MySQL could be slow with large tables ?

If you’ve been reading enough database related forums, mailing lists or blogs you probably heard complains about MySQL being unable to handle more than 1.000.000 (or select any other number) rows by some of the users. On other hand it is well known with customers like Google, Yahoo, LiveJournal,Technocarati MySQL has installations with many billions […]

Illustrating Primary Key models in InnoDB and their impact on disk usage

On a recent engagement I worked¬†with a customer who makes extensive use of UUID() values for their Primary Key and stores it as char(36), and their row count on this example table has grown to over 1 billion rows. The table is INSERT-only (no UPDATEs or DELETEs), and the bulk of their retrieval are PK […]