In favour of a milestone based release model

I like milestone based release models.

The advantages I find in this model are in particular beneficial for MySQL. What I find good about this model are:

  • Things are unstable for shorter periods. Even if some feature is not full stable in some milestone, the model encourages that such a feature is fixed on higher priority.
  • It is easy to create a priority ranking for new features. Moreover, priorities are expressed more by chronological time of development, less by “how many people are working on it”.
  • The model pushes towards rapid development, since you can’t release M5 before M4 is complete.

The last versions of MySQL took long time to complete. Take 5.1, for example: partitioning and event scheduling were long considered GA before row-based replication was half stable. Consider the so small but useful sub-second slow logs; the variables made dynamic in 5.1 (slow log again, for example); the new INFORMATION_SCHEMA tables.

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Useful temporal functions & queries

Here’s a complication of some common and useful time & date calculations and equations. Some, though very simple, are often misunderstood, leading to inefficient or incorrect implementations.

There are many ways to solve such problems. I’ll present my favorites.

Querying for time difference

Given two timestamps: ts1 (older) and ts2 (newer), how much time has passed between them?

One can use TIMEDIFF() & DATEDIFF(), or compare two UNIX_TIMESTAMP() values. My personal favorite is to use TIMESTAMPDIFF(). Reason being that I’m usually interested in a specific metric, like the number of hours which have passed, or the number of days, disregarding the smaller minute/second resolution. Which allows one to:

SELECT TIMESTAMPDIFF(HOUR, ts1, ts2)

Take, for example:

SELECT TIMESTAMPDIFF(MONTH, '2008-10-07 00:00:00', '2009-12-06 00:00:00')

The function correctly identifies the number of days per month, and provides with 13, being the truncated number of full months.

Doing arithmetics

One can use TIMESTAMPADD(), or DATE_SUB(), but, again, when dealing with specific resolutions, I find “+ INTERVAL” to be the most convenient:

SELECT ts1 + INTERVAL 10 HOUR

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On restoring a single table from mysqldump

Following Restore one table from an ALL database dump and Restore a Single Table From mysqldump, I would like to add my own thoughts and comments on the subject.

I also wish to note performance issues with the two suggested solutions, and offer improvements.

Problem relevance

While the problem is interesting, I just want to note that it is relevant in very specific database dimensions. Too small – and it doesn’t matter how you solve it (e.g. just open vi/emacs and copy+paste). Too big – and it would not be worthwhile to restore from mysqldump anyway. I would suggest that the problem is interesting in the whereabouts of a few dozen GB worth of data.

Problem recap

Given a dump file (generated by mysqldump), how do you restore a single table, without making any changes to other tables?

Let’s review the two referenced solutions. I’ll be using the employees db on mysql-sandbox for testing. I’ll choose a very small table to restore: departments (only a few rows in this table).

Security based solution

Chris offers to create a special purpose account, which will only have write (CREATE, INSERT, etc.) privileges on the particular table to restore. Cool hack! But, I’m afraid, not too efficient, for two reasons: Continue reading » “On restoring a single table from mysqldump”

questions or queries?

I’ve hit a recent change which took me by surprise.

I was used to checking for the ‘questions‘ global status variables to see the total amount of queries the server performs. So, for example, I could run com_select/questions to learn the SELECT ratio out of all queries.

Apparently, as of 5.0.725.0.76 & 5.1.31 this has changed. A new status variable was introduced, called ‘queries‘.

The change being? questions does not any longer indicate the number of queries the server has executed: only the number of queries requested by the client (so, calling on a stored routine only counts as 1, regardless of how many queries the routine executes). The new queries variable indicates the amount of server queries issued (see the 5.0 and 5.1 docs for details).

So, as of 5.0.72 or 5.1.31, the calculation should be com_select/com_queries (or com_select_diff/com_queries_diff) to learn the SELECT ratio of all queries. I learned this due to a bug report on mycheckpoint, which presented some 10265% SELECT ratio…

My take on this is that it could have been worked out differently: instead of changing the meaning of an existing variable, questions could have remained as it was, with the introduction of, say, client_questions, which would only indicate client number of issued queries.

I believe changing the meaning of status variables at such late versions (5.0.76 is quite late!) invites trouble: code that used to work on already then-stable versions (e.g. 5.0.51) would behave differently after upgrade. Such changes should best take place while still in BETA phase.

Performance analysis with mycheckpoint

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

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?

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Announcing mycheckpoint: lightweight, SQL oriented monitoring for 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.

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SQL multi line chart

Time for another charting SQL query. I wish to present a single-query generated multi-line/area chart. I’ll walk through some of the steps towards making this happen. By the end of this post I’ll present some real-data charts, area charts and colored charts.

+---------+-----------------------------------------------------------------------------------+
| y_scale | chart                                                                             |
+---------+-----------------------------------------------------------------------------------+
| 1       | ****---------#######----------------------------------------*******--------###### |
| 0.88    | ----***---###-------##-----------------------------------***-------***---##------ |
| 0.75    | -------**#------------##-------------------------------**-------------*##-------- |
| 0.63    | ------##-*--------------##----------------------------*--------------##**-------- |
| 0.5     | -@@@@@@@@@@@@@@@----------#-----@@@@@@@@@@@@@@@@----**---------@@@@@@@@@@@@@@@@-- |
| 0.38    | ----#-------*--------------##----------------------*---------------#-------*----- |
| 0.25    | --##---------*---------------#--------------------*--------------##---------*---- |
| 0.13    | -#------------**--------------#-----------------**--------------#------------*--- |
| 0       | @---------------*--------------##--------------*---------------#--------------**- |
| -0.12   | -----------------*---------------#------------*--------------##-----------------* |
| -0.25   | ------------------*---------------#---------**--------------#-------------------- |
| -0.37   | -------------------**--------------#-------*---------------#--------------------- |
| -0.5    | ----------------@@@@@@@@@@@@@@@@----##----*-----@@@@@@@@@@@@@@@----------------@@ |
| -0.62   | ----------------------**--------------#-**--------------#------------------------ |
| -0.75   | ------------------------**------------**#-------------##------------------------- |
| -0.87   | --------------------------**-------***---###-------###--------------------------- |
| -1      | ----------------------------*******---------#######------------------------------ |
|         | v:::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::v |
|         | 0                                                                               8 |
|         |     # sin(x)                                                                      |
|         |     * cos(x)                                                                      |
|         |     @ sign(tan(x))/2                                                              |
+---------+-----------------------------------------------------------------------------------+

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On free and open blog posts: this post is free

I’d like to criticize and stress some opinions on free and open blog posts, including such appearing on planet MySQL.

Some rants follow; skip if you’re only after technical stuff

1. On free reading

This post is completely free. You don’t need to pay or register to read it, not will you require to pass personal details to comment.

If you happen to see this post on some website, which only provides you with 1st couple of sentences, then asks you to login in order to view the complete text — you should know you need no registration to read this.

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