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MySQL

I’ve been using MySQL since it became a mature DBMS, and therefore use it in virtually every project I execute. Here are a number of areas within MySQL that I have deep experience which prove useful in business, ecommerce, and web application design and execution. For clarification and expansion, please contact me and I will be happy to go into more detail and offer case studies.

  • Deep usage of MySQL as a DBMS from version 3.23 forward
  • MySQL installation utilizing source compilation, RPMs, and ports (BSD)
  • MySQL optimization and tuning at source code level, including enhanced patching
  • Experience in advanced MySQL configuration
  • Daily work in database security, query optimization, full-text search indexing, de-normalization (where appropriate)
  • Development and optimization of physical and logical design of MySQL database systems
  • Database monitoring (usage and health) utilizing a variety of tools, including the MySQL Enterprise packages
  • Daily usage of a variety of MySQL tools, including MySQL AB’s own, as well as third-party packages
  • Creating and execution of daily/weekly/monthly database backup/restore processes
  • Design and implementation of complex database structures with optimal indexing and table design
  • Frequent design and implementation of rollup tables to expedite web apps/reporting/database access
  • Deep experience in the design and implementation of complex replication schemes, including master-master replication (multiple data entry points)
  • Design, creation, and implementation of n-tiered development environments using 30+ database servers
  • Development of application-specific fault-tolerant distributed database mechanisms
  • Expert in utilizing crontabs to execute repetitive tasks in a clean, monitored, and repeatable fashion
  • Expert in utilizing system-level utilities to create and summarize database activity for daily/weekly reporting both in detail and at the summarized level
  • Heavy background in shell scripting (bash, csh, awk, sed, PERL, etc.)
  • Daily usage and experience with large data sets (100M rows+)
  • Data warehouse (OLAP) background