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Data Analytics: MyISAM vs ARCHIVE vs Infobright ICE vs Infobright IEE benchmark (part2)

14 May

This is Part2 of the MySQL based engines I have been testing lately.  Part1 covered time loading data, size on disk for the tables, and system specs.  On Part1 we could see how the ARCHIVE engine and both free and commercial versions of Infobright gave significant gains in disk space.  In Load times, the commercial version of Infobright (IEE) was the fastest; while MyISAM (disabling keys), ARCHIVE, and Infobright ICE were similar.  InnoDB performed poorly importing data from CSV, taking days to import.  InnoDB works better with INSERT statements than CSV imports.  The next Figure show query performance on this test data for two different queries:

query performance for different MySQL engines


Data Analytics: MyISAM vs ARCHIVE vs Infobright ICE vs Infobright IEE benchmark

3 Apr

Next is a brief quick benchmark/comparison of different MySQL based storage engines I have been working lately for Big Data analytics.  The comparison includes: disk space used, load time, query performance, as well as some comments.  It is not intended as a formal benchmark.

During the last few days I have running out of disk space in my 2TB partition I use for my research experiments.  On that partition, I mainly have a MySQL database with partitioned tables by week and over 2 years of web log and performance data.  At first, I was comparing InnoDB vs MyISAM query performance and disk usage.  MyISAM is a quite faster than InnoDB loading data, specially when DISABLING KEYS first, but then, reenabling the keys was a problem MyISAM on large tables.  MyISAM doesn’t seem to scale well to a large number of partitions, while InnoDB does.  An advantage of MyISAM tables besides fast loading, is that the tables occupy less disk space than InnoDB:  InnoDB occupies about 40% more space than MyISAM for this type of tables, consisting of various numeric IDs and a couple of URLs.  However, had many crashes with MyISAM having to repair tables many times.   For data analysis that is annoyance but not a serious problem.  Wouldn’t use MyISAM in production/OLTP servers, maybe if back in the early 2000’s…

 Anyhow, after optimizing the configuration for both engines and having to choose between:

  • InnoDB: reliable, but large size on disk and slow to load tables.  It could take a week to load the 2 years of data.

  • MyISAM: faster to load, medium size on disk (a bit less than in CSV), but unreliable for large tables

Decided to explore other non distributed file system options like Hadoop, with easy MySQL migration and found:

  • ARCHIVE: a compressed engine for MySQL, doesn’t support keys (except for the numeric primary key).  Already familiar with it for backups and integrated into MySQL.  Supports basic partitioning.

  • InfoBright ICE: a compressed column table storage, fork from MySQL, open source with fast loading.  As cons, requires a different installation, and advanced features only in the commercial version.

  • InfoBright IEE: commercial version of the storage.  Promesses multi-core improvements for query and loading over the open-source version. Decided to give it a try for comparison.



Improve your DNS lookups with namebench

30 Jan

Ilya Ilya Grigorik’s great course on web performance made me aware of the importance of DNS server performance and how they are poorly mantained.  Domain Name System was invented in ’82, they compose one of the oldest core services of the Internet, however, they are often disregarded, as they are assumed to be fast and usually one connects to whatever is offered through DHCP.  DNS requires very little resources: uses UDP, client and server caches, and high optimized code.  DNS is also very reliable as clients have a pool of servers to connect to and requests can be forwarded between servers.  However, in general, DNS servers are poorly maintained and not optimized regularly, as they most of the time “work”.

Illya suggested trying namebench, an open-source tool to benchmark and help you choose the most appropriate DNS servers for your location.  What’s cool about the tool —besides being python based and having a multi-platform GUI– is that for it’s benchmark it can take domain names from your browser’s cache and graphical reports.

namebench DNS latency results


PHP’s XDebug tracing overhead in production

9 Aug

This is a post with some production information I had pending to write… XDebug PHP extension, is a great, open-source debugger and profiler for PHP. It is a good alternative to the commercial Zend server. XDebug besides its profiling capabilities, it adds full stack traces to PHP error messages when enabled (see config. options). These include Fatal Errors and Warnings as shown in the next picture:

XDebug PHP Fatal error trace


A tribute to Zabbix, great network+ monitoring system

7 Apr

Just a short post to recommend a great monitoring system if you haven’t heard of it yet:  Zabbix.



Zabbix has been around to the public since around 2001, and since 2004 as a stable version.  However I see very few posts about it, and it is far less popular than Nagios, even though it is more feature rich.  I have been using it since 2004, for various projects, and it is great.  It is very simple to install, it had since the beginning Windows and Unix agents so you don’t need to set up SNMP on your network, and scales very well.  I even use it to measure and keep track of  the performance of my own dev machine.

However the most important feature that I find besides monitoring servers, performance availability history, graphics and charts, is that you can extend it and import application data easily! (more…)

Yottaa, a great tool for monitoring the performance of your site

22 Nov

Recently I have found this really cool and useful website: Yottaa, besides the curious domain name is a web 2.0 style monitoring and benchmarking site. You input what pages to monitor or benchmark and it uses an automated Firefox browser to load and process the whole page, including the CSS and Javascript. Then it reports you page load time, time to interactivity, and a full YSlow report, and their custom score.


Calculating 95th, 99th, 50th (median) with a single MySQL query

16 Nov

As a first post, let’s start with a basic tip for SQL queries I use very often.  First let’s start with some basic info on percentiles:

Percentiles are one of the best indicators of how well our web site is performing, unlike averages.  Averages tend to hide information on outlier values, and while they might be showing you adequate numbers, they might be hiding how a significant portion of  users are seeing your site.

For websites, a good percentile to base measurements is the 95th percentile, while for network equipment the 99th.  This is because you might have some pages that are inherently longer to process, such an availability search for a specific product, while network equipment doesn’t have this constrain.  You should really use the number that best represents your workload, 95th seems to be set as the standard but you can also use the 85th according to the type of site you are monitoring.  The median (not average) corresponds to the 50th percentile.  (more…)