Tag: Analysis

Static charts vs. interactive charts

MySQL

I’m having my usual fun with charts. Working on mycheckpoint, I’ve generated monitoring charts using the Google Chars API. But I’ve also had chance to experiment and deploy interactive charts, JavaScript based. In particular, I used and tweaked dygraphs.

I’d like to note some differences in using charts of both kinds. And I think it makes a very big difference.

Static charts

I’ll call any image-based chart by “static chart”. It’s just a static image. Example of such charts are those generated by Google Image Charts (they now also have new, interactive charts), or RRDtool. Show below is an example of a static chart; in this example, generated by Google: Continue reading » “Static charts vs. interactive charts”

Performance analysis with mycheckpoint

MySQL

mycheckpoint (see announcement) allows for both graph presentation and quick SQL access to monitored & analyzed data. I’d like to show the power of combining them both.

InnoDB performance

Taking a look at one of the most important InnoDB metrics: the read hit ratio (we could get the same graph by looking at the HTML report):

SELECT innodb_read_hit_percent FROM sv_report_chart_sample \G
*************************** 1. row ***************************
innodb_read_hit_percent: http://chart.apis.google.com/chart?cht=lc&chs=400x200&chts=303030,12&chtt=Nov+10,+11:40++-++Nov+11,+08:55+(0+days,+21+hours)&chdl=innodb_read_hit_percent&chdlp=b&chco=ff8c00&chd=s:400664366P6674y7176677677u467773y64ux166666764366646y616666666666644444434444s6u4S331444404433341334433646777666666074736777r1777767764776666F667777617777777777777777yaRi776776mlf667676xgx776766rou67767777u37797777x76676776u6A737464y67467761777666643u66446&chxt=x,y&chxr=1,99.60,100.00&chxl=0:||Nov+10,+15:55|Nov+10,+20:10|Nov+11,+00:25|Nov+11,+04:40|&chxs=0,505050,10

We see that read hit is usually high, but occasionally drops low, down to 99.7, or even 99.6. But it seems like most of the time we are above 99.95% read hit ratio. It’s hard to tell about 99.98%.

Can we know for sure?

We can stress our eyes, yet be certain of little. It’s best if we just query for the metrics! mycheckpoint provides with all data, accessible by simple SQL queries: Continue reading » “Performance analysis with mycheckpoint”

Replication analysis with mycheckpoint

MySQL

I would like to show how mycehckpoint (see announcement) can be put to use for analyzing various replication metrics.

Lagging slaves

A slave has been monitored. Monitoring started at a time when it was way behind master (about two days lag), but it has since caught up. This can be easily verified by the following chart:

The above chart can be obtained by viewing the HTML report:

SELECT html FROM sv_report_html

Or by directly issuing the query:

mysql> SELECT seconds_behind_master FROM sv_report_chart_hour\G
*************************** 1. row ***************************
seconds_behind_master: http://chart.apis.google.com/chart?cht=lc&chs=400x200&chts=303030,12&chtt=Nov+5,+10:00++-++Nov+10,+08:00+(4+days,+22+hours)&chdl=seconds_behind_master&chdlp=b&chco=ff8c00&chd=s:976431zzzywutrpnliiifdbZYXVTRRRPNLJHEBAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA&chxt=x,y&chxr=1,0,169811&chxl=0:||Nov+6,+09:00|Nov+7,+09:00|Nov+8,+08:00|Nov+9,+08:00|&chxs=0,505050,10

This is all nice. But I’m also interested in the rate at which slave lag decreased. Many ignore this important metric: just how fast does your slave replicate?

Continue reading » “Replication analysis with mycheckpoint”

Announcing mycheckpoint: lightweight, SQL oriented monitoring for MySQL

MySQL

I’m proud to announce mycheckpoint, a monitoring utility for MySQL, with strong emphasis on user accessibility to monitored data.

mycheckpoint is a different kind of monitoring tool. It leaves the power in the user’s hand. It’s power is not with script-based calculations of recorded data. It’s with the creation of a view hierarchy, which allows the user to access computed metrics directly.

mycheckpoint is needed first, to deploy a monitoring schema. It may be needed next, so as to INSERT recorded data (GLOBAL STATUS, GLOBAL VARIABLES, MASTER STATUS, SLAVE STATUS) — but this is just a simple INSERT; anyone can do that, even another monitoring tool.

It is then that you do not need it anymore: everything is laid at your fingertips. Consider:

SELECT innodb_read_hit_percent, DML FROM sv_report_chart_hour;

mycheckpoint provides the views which take raw data (just innodb_buffer_pool_read_requests, com_select, innodb_buffer_pool_size, table_open_cache, seconds_behind_master etc.) and generate Google Charts URLs, HTML reports, human readable reports, or otherwise easily accessible data.

Continue reading » “Announcing mycheckpoint: lightweight, SQL oriented monitoring for MySQL”

How NOT to test that mysqld is alive

MySQL

I had a call from a new customer last week. They had issues with their MySQL server. Apparently, it was repeatingly crashing, every few hours. To have their production system kept alive, they used a script to periodically see if MySQL was still alive, and if not – start it.

I was first thinking in directions of old installations; wrong memory allocations (too little memory for large content; to large memory allocation for weak machine). When I reached the customer’s premises, I quickly reviewed general settings, while explaining some basic configuration guidelines. There were peculiarities (e.g. query_cache_limit being larger than query_cache_size), but nothing to obviously suggest a reason for crash.

I then observed the error log. Took some time to find it, since the log_error parameter appeared twice in the my.cnf file; first one appearing at the very beginning, the second (overwriting the first) was far into the file.

Sure enough, there were a lot of startup messages. And… shutdown messages. In fact, the log looked something like: Continue reading » “How NOT to test that mysqld is alive”

Useful database analysis queries with INFORMATION_SCHEMA

MySQL

A set of useful queries on INFORMATION_SCHEMA follows. These queries can be used when approaching a new database, to learn about some of its properties, or they can be regularly used on an existing schema, so as to verify its integrity.

I will present queries for: