I was recently struck by a problem which is unusual. In order to keep an eye on the database server I use nagios, cacti, merlin and some local scripts to monitor the database instance and ensure that it is working properly.  That normally works fine.  The different monitor processes do various things, one of which is to monitor the replication status of a slave, and warn me if the replication is not working or if it’s behind. This is done with the command SHOW SLAVE STATUS.

The server I was looking at runs some large local batch jobs aggregating data. Unfortunately, I was experiencing that replication was interfering with these batch jobs so decided to see if things would perform better if I stopped replication and let the batch …

A software-based distributed caching system such as memcached is an important piece of today's largest Internet sites that support millions of concurrent users and deliver user-friendly response times. The distributed nature of memcached design transforms 1000s of servers into one large caching pool with gigabytes of memory per node. This blog entry explores single-instance memcached scalability for a few usage patterns.

Table below shows out-of-the-box (no custom OS rewrites or networking tuning required) performance with 10G networking hardware and one single-socket UltraSPARC T2-based server with 8 cores and 8 threads per core (64 threads on a chip). All runs are done with a single memcached instance and 40 worker threads so that about 3 cores (24 threads) are used for the critical networking stack that is also heavily parallelized. 40+24 threads is a nice balance for this …

A software-based distributed caching system such as memcached is an important piece of today's largest Internet sites that support millions of concurrent users and deliver user-friendly response times. The distributed nature of memcached design transforms 1000s of servers into one large caching pool with gigabytes of memory per node. This blog entry explores single-instance memcached scalability for a few usage patterns.

Table below shows out-of-the-box (no custom OS rewrites or networking tuning required) performance with 10G networking hardware and one single-socket UltraSPARC T2-based server with 8 cores and 8 threads per core (64 threads on a chip). All runs are done with a single memcached instance and 40 worker threads so that about 3 cores (24 threads) are used for the critical networking stack that is also heavily parallelized. 40+24 threads is a nice balance for this …

Introduction

A question I recently saw on Stack Overflow titled Faster way to delete matching [database] rows? prompted me to organize my thoughts and observations on the subject and quickly jot them down here.

Here is the brief description of the task: say, you have 2 MySQL tables a and b. The tables contain the same type of data, for example log entries. Now you want to delete all or a subset of the entries in table a that exist in table b.

Solutions Suggested By Others

DELETE FROM a WHERE EXISTS (SELECT b.id FROM b WHERE b.id = a.id);

DELETE a FROM a INNER JOIN b on a.id=b.id;

DELETE FROM a WHERE id IN (SELECT id FROM b)

The Problem With Suggested Solutions

Solutions above are all fine if the tables are quite small and the …