The most efficient performance optimization of a SQL statement is to eliminate it. Cary Millsap’s recent Kaleidoscope presentation again highlighted that improving performance is function of code path. Removing code will improve performance.

You may think that it could be hard to eliminate SQL, however when you know every SQL statement that is executed in your code path obvious improvements may be possible. In the sequence SQL was implemented sometimes easy observations can lead to great gains. Let me provide some actual client examples that were discovered by using the MySQL General Log.

Example 1

5 Query   SELECT *  FROM `artist`
5 Query   SELECT *  FROM `artist`
5 Query …

If you haven't already heard PBMS is now part of the Drizzle tree.

Getting it there was a fair bit of work but not as much as I had thought it would be. The process of getting it to work with Drizzle and running it thorough Hudson has improved the code a lot. It is amazing what some compilers will catch that others will let by. I am now a firm believer in treating all compiler warnings as errors.

I am just in the process of updating the PBMS plugin so that it will build and install the PBMS client library (libpbmscl.so) as well as the plugin. The PBMS client library is a standalone library that can be used to access the PBMS daemon weather it is running as part of MySQL or Drizzle. So a PBMS client library built with Drizzle can be used to access a PBMS daemon running as part of MySQL and vice-versa.

There is also PHP extension for PBMS that is basically just a wrapper for the library. Currently this is …

One role of a MySQL consultant is to review an existing production system. Sometimes you have sufficient time and access, and other times you don’t. If I am given a limited time here is a general list of things I look at.

1. Review Server architecture, OS, Memory, Disks (including raid and partition type), Network etc
2. Review server load and identify physical bottleneck
3. Look at all running processes
4. Look specifically at MySQL processes
5. Review MySQL Error Log
6. Determine MySQL version
7. Look at MySQL configuration (e.g. /etc/my.cnf)
8. Look at running MySQL Variables
9. Look at running MySQL status (x n times)
10. Look at running MySQL INNODB status (x n times) if used
11. Get Database and Schema Sizes
12. Get Database Schema
13. Review Slow Query Log
14. Capture query sample via SHOW FULL PROCESSLIST (locked …

A live recording of my LinuxTag 2010 presentation entitled Storage Done Right: Building a Resilient, Distributed, Highly Available Open Source iSCSI SAN is now available from our web site. If you want to find out how to build a complete SAN from 100% open source, do take a look!

I do apologize for the less-than-optimal sound quality. I did the recording myself with my laptop mike, so unfortunately there’s quite a bit of clipping in the audio track. I hope my ramblings are still somewhat audible.

…

Mikeal Rogers wrote a blog post on MongoDB performance and durability. In one of the sections, he writes about the request/response model, and makes the following statement:

MongoDB, by default, doesn’t actually have a response for writes.

In response, one of 10gen employees (the company behind MongoDB) made the following comment on Hacker News:

We did this to make MongoDB look good in stupid benchmarks.

The benchmark in question shows a single graph, which demonstrates that MongoDB is 27 times faster than CouchDB on inserting one million rows. At the first glance, the benchmark immediately looks silly if you've ever done serious benchmarking before. CouchDB people are smart, inserting …

I was configuring MySQL Cluster where the application servers use a properties file to connect to the MySQL Data/Storage node (I configured both Data and Storage nodes on same physical server).
I want the application to use a single IP address, to access the DB servers in cluster. Since if any of the nodes fail, the application servers should still be able to query the databases.
Hence I thought of using LVS so that multiple application servers can access the DB servers through VIP. To achieve the same I have configured LVS, thought of sharing the same.

RHEL Linux LVS setup:
=====================

Pre-Requisites:
===============

REDHAT Linux Cluster Packages
VIRTUAL IP

Configuration for LB server:
============================

Configure packet forwarding on LB server

vi /etc/sysctl.conf

net.ipv4.ip_forward = 1       …

I was configuring MySQL Cluster where the application servers use a properties file to connect to the MySQL Data/Storage node (I configured both Data and Storage nodes on same physical server).
I want the application to use a single IP address, to access the DB servers in cluster. Since if any of the nodes fail, the application servers should still be able to query the databases.
Hence I thought of using LVS so that multiple application servers can access the DB servers through VIP. To achieve the same I have configured LVS, thought of sharing the same.

RHEL Linux LVS setup:
=====================

Pre-Requisites:
===============

REDHAT Linux Cluster Packages
VIRTUAL IP

Configuration for LB server:
============================

Configure packet forwarding on LB server

vi /etc/sysctl.conf

net.ipv4.ip_forward = 1       …

Mikeal Rogers wrote a blog post on MongoDB performance and durability. In one of the sections, he writes about the request/response model, and makes the following statement:

MongoDB, by default, doesn’t actually have a response for writes.

In response, one of 10gen employees (the company behind MongoDB) made the following comment on Hacker News:

We did this to make MongoDB look good in stupid benchmarks.

The benchmark in question shows a single graph, which demonstrates that MongoDB is 27 times faster than CouchDB on inserting one million rows. At the first glance, the benchmark immediately looks silly if you’ve ever done serious benchmarking before. CouchDB people are smart, inserting …

Some of you may have noticed that blob streaming has been merged into the main Drizzle tree recently. There are a few hooks inside the Drizzle kernel that PBMS uses, and everything else is just in the plug in.

For those not familiar with PBMS it does two things: provide a place (not in the table) for BLOBs to be stored (locally on disk or even out to S3) and provide a HTTP interface to get and store BLOBs.

This means you can do really neat things such as have your BLOBs replicated, consistent and all those nice databasey things as well as easily access them in a scalable way (everybody knows how to cache HTTP).

This is a great addition to the AlsoSQL arsenal of Drizzle. I’m looking forward to it advancing and being adopted (now much easier that it’s in the main repository)

• …

Connector/J provides a useful load-balancing implementation for Cluster or multi-master deployments.  As of Connector/J 5.1.12, this same implementation is used under the hood for balancing load between read-only slaves with ReplicationDriver.  When trying to balance workload between multiple servers, though, the driver has to decide when it’s safe to swap servers – doing so in the middle of a transaction would not make applications very happy.  Many of the same principles which apply to autoReconnect also apply here – you don’t want to lose important state information.

As a result, Connector/J will only try to pick a new server when one of the following happen:

1. At transaction boundaries (transactions are explicitly committed or rolled back)
2. A communication …