This chapter is about possible reasons of "Lost connection to MySQL server" error not discussed in previous one.

Chapter 10. Lost connection to MySQL server during query

You can see error "Lost connection to MySQL server" not only because
too small connect_timeout, but because other reasons too. In this
chapter we discuss these reasons.


$php phpconf2009_4.php

string(44) "Lost connection to MySQL server during query"


Most likely error log will show what happened:

...

Rest of the chapter is here

In posts on June 30 and July 6, I explained how implementing the commands “replace into” and “insert ignore” with TokuDB’s fractal trees data structures can be two orders of magnitude faster than implementing them with B-trees. Towards the end of each post, I hinted at that there are some caveats that complicate the story a little. On July 21st I explained one caveat, secondary keys, and on August 3rd, Rich explained another caveat. In this post, I explain the other …

This chapter is about possible reasons of "Lost connection to MySQL server" error not discussed in previous one.

Chapter 10. Lost connection to MySQL server during query

You can see error "Lost connection to MySQL server" not only because
too small connect_timeout, but because other reasons too. In this
chapter we discuss these reasons.


$php phpconf2009_4.php

string(44) "Lost connection to MySQL server during query"


Most likely error log will show what happened:

...

Rest of the chapter is here

Prior posts addressed the performance benefits of a shared cache tier (ScaleDB CAS) and also the storage flexibility it enables.This post compares the ScaleDB CAS purpose-built file storage sharing system against off-the-shelf solutions like NFS and various cluster file systems (CFS).

When using a clustered database, like ScaleDB, each node has full access to all of the data in the database. This means that the file system (SAN, NAS, Cloud, etc.) must allow multiple nodes to share the data in the file system.

Options include:
1. Network File System (NFS)
2. Cluster File System (CFS)
3. Purpose-built file storage interface

Locking Granularity:
I won’t get deeply …

It has been a while since I posted on my blog - in fact, I believe this is the first time ever that more than one month passed between posts since I started blogging. There are a couple of reasons for the lag:

• 
  
• Matt Casters, Jos van Dongen and me have spent a lot of time finalizing our forthcoming book, Pentaho Kettle Solutions (Wiley, ISBN: 978-0-470-63517-9). The book is currently being produced, and should be available according to schedule in early September 2010. If you're interested, you might like to read …

If you read Percona's whitepaper on Goal-Driven Performance Optimization, you will notice that we define performance using the combination of three separate terms. You really want to read the paper, but let me summarize it here:

1. Response Time - This is the time required to complete a desired task.
2. Throughput - Throughput is measured in tasks completed per unit of time.
3. Capacity - The system's capacity is the point where load cannot be increased without degrading response time below acceptable levels.

Setting and meeting your response time goal should always be your primary focus, but the closer throughput is to capacity the worse response time can be.  It's a trade-off! …

If you’ve been looking for a simple python script to use with MySQL that you can use to expand upon for your next project, check this one out. It has error handling for the connection, error handling for the sql call, and loop iteration for the rows returned.

#!/usr/bin/python
import sys
import MySQLdb

my_host = "localhost"
my_user = "user"
my_pass = "password"
my_db = "test"

try:
    db = MySQLdb.connect(host=my_host, user=my_user, passwd=my_pass, db=my_db)
except MySQLdb.Error, e:
     print "Error %d: %s" % (e.args[0], e.args[1])
     sys.exit (1)

cursor = db.cursor()
sql = "select column1, column2 from table";
cursor.execute(sql)
results = cursor.fetchall()
for row in results:
    column1 = row[0]
    column2 = row[1]
    print "column1: %s, column2: %s"%(column1,column2)

db.close()

Compliance. Funding. Financial results. Copyright assignment. And more.

Follow 451 CAOS Links live @caostheory on Twitter and Identi.ca
“Tracking the open source news wires, so you don’t have to.”

Compliance
# The Linux Foundation launched the Open Compliance Program, including tools, training, and consulting.

Funding
# VentureBeat reported that Joyent has raised $7m in a second round of funding.

# Basho Technologies secured $2m from angel investors in a Series C preferred equity financing.

# …

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Installing A Web, Email And MySQL Database Cluster (Mirror) On Debian 5.0 With ISPConfig 3

This tutorial describes the installation of a clustered Web, Email, Database and DNS server to be used for redundancy, high availability and load balancing on Debian 5 with the ISPConfig 3 control panel. GlusterFS will be used to mirror the data between the servers and ISPConfig for mirroring the configuration files. I will use a setup of two servers here for demonstration purposes but the setup can scale to a higher number of servers with only minor modifications in the GlusterFS configuration files.

Similar to events in the US and Germany, another large Oracle User Group organization is preparing for their annual conference and would like to set up a dedicated track of sessions about MySQL – this time it's the British UKOUG  which organizes the Conference Series Technology & E-Business Suite 2010.

This annual user group event will offer a place to share knowledge and hear the latest information from key personnel about product development. This event is a technical event and not a marketing event and we'd like to encourage you to submit a MySQL-related talk!

Some more information about this conference:

• Dates: Monday 29th November – Wednesday 1st …