Mar 19

InnoDB executes a lot of transactions for MySQL users. And users and technical experts in the InnoDB community exchange lots of information about InnoDB … transacting in ideas … all the time. A great opportunity to participate in some of these transactions is the upcoming MySQL Conference and Expo.

Does your InnoDB-based application need more transactions to execute more quickly and reliably? Come hear these noted speakers present information that can help you get the most out of InnoDB:

Mar 11

Why should you care about the latest “early adopter” release of the InnoDB Plugin, version 1.0.3?   One word: performance! The release introduces these features:

  • Enhanced concurrency & scalability: the “Google SMP patch” using atomic instructions for mutexing
  • More efficient memory allocation: ability to use more scalable platform memory allocator
  • Improved out-of-the-box scalability: unlimited concurrent thread execution by default
  • Dynamic tuning: at run-time, enable or disable insert buffering and adaptive hash indexing

These new performance features can yield up to twice the throughput or more, depending on your workload, platform and other tuning considerations. In another post, we explore some details about these changes, but first, what do these enhancements mean for performance and scalability?

In brief, we’ve tested three different workloads (joins, DBT2 OLTP and a modified sysbench) using a memory-resident database. In all cases, the InnoDB Plugin scales significantly better than the built-in InnoDB in MySQL 5.1. And in some cases, the absolute level of performance is dramatically higher too! The charts below illustrate the kinds of performance gains we’ve measured with release 1.0.3 of the InnoDB Plugin. Your mileage may vary, of course. See the InnoDB website for all the details on these tests.

This release of the InnoDB Plugin incorporates a patch made by Ben Handy and Mark Callaghan at Google to improve multi-core scalability by using more efficient synchronization methods (mutexing and rw-locks) to reduce cpu utilization and contention. We’re grateful for this contribution, and you will be too!

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