During the design period of a new cluster, it is always advised to have at least 3 nodes (this is the case with PXC but it’s also the same with PRM). But why and what are the risks ? The goal of having more than 2 nodes, in fact an odd number is recommended in [...]
Eventual Consistency in MySQL
November 18, 2011 By 8 Comments
We’re told that foreign key constraints are the best way to enforce logical referential integrity (RI) in SQL, preventing rows from becoming orphaned. But then we learn that the enforcement of foreign keys incurs a significant performance overhead.1,2 MySQL allows us to set FOREIGN_KEY_CHECKS=0 to disable enforcement of RI when the overhead is too high. But [...]
Side load may massively impact your MySQL Performance
November 13, 2011 By 7 Comments
When we’re looking at benchmarks we typically run some stable workload and we run it in isolation – nothing else is happening on the system. This is not however how things happen in real world when we have significant variance in the load and many things can be happening concurrently. It is very typical to [...]
Percona Server 5.1.59-13.0
October 16, 2011 By Leave a Comment
Percona is glad to announce the release of Percona Server 5.1.59-13.0 on October 15, 2011 (Downloads are available here and from the Percona Software Repositories). Based on MySQL 5.1.59, including all the bug fixes in it, Percona Server 5.1.59-13.0 is now the current stable release in the 5.1 series. All of Percona’s software is open-source and free, all the [...]
Percona Server 5.5.16-22.0
October 16, 2011 By 2 Comments
Percona is glad to announce the release of Percona Server 5.5.16-22.0 on October 14, 2011 (Downloads are available here and from the Percona Software Repositories). Based on MySQL 5.5.16, including all the bug fixes in it, Percona Server 5.5.16-22.0 is now the current stable release in the 5.5 series. All of Percona’s software is open-source and free, all the [...]
Disaster: MySQL 5.5 Flushing
September 18, 2011 By 27 Comments
We raised topic of problems with flushing in InnoDB several times, some links: InnoDB Flushing theory and solutions MySQL 5.5.8 in search of stability This was not often recurring problem so far, however in my recent experiments, I observe it in very simple sysbench workload on hardware which can be considered as typical nowadays.
Preprocessing Data
August 8, 2011 By 3 Comments
There are many ways of improving response times for users. There are some people that spend a lot of time, energy and money on trying to have the application respond as fast as possible at the time when the users made the request. Those people may miss out on an opportunity to do some or [...]
The case for getting rid of duplicate “sets”
May 17, 2011 By 2 Comments
The most useful feature of the relational database is that it allows us to easily process data in sets, which can be much faster than processing it serially. When the relational database was first implemented, write-ahead-logging and other technologies did not exist. This made it difficult to implement the database in a way that matched [...]
Checking the subset sum set problem with set processing
May 16, 2011 By Leave a Comment
Hi, Here is an easy way to run the subset sum check from SQL, which you can then distribute with Shard-Query:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | CREATE TABLE `the list` ( `id` bigint(20) NOT NULL AUTO_INCREMENT, `val` bigint(20) NOT NULL DEFAULT '0', PRIMARY KEY (`id`), KEY `id` (`id`) ) ENGINE=MyISAM; SELECT val as `val`, COUNT(DISTINCT (id)) as `cd` FROM test.data as d WHERE val in (-2,-3,-10,15,15,16) GROUP BY val; +-----+----------+----------+ | val | cd | CNT | +-----+----------+----------+ | -10 | 1 | 1 | | -3 | 1 | 1 | | -2 | 1 | 1 | | 15 | 35417088 | 35417088 | +-----+----------+----------+ 5 rows in set (40.20 sec) |
Notice there is no 16 in the list. We did not pass the check. There are enough 15s though. The distinct value count for each item in the output set, must at least [...]
Distributed Set Processing with Shard-Query
May 14, 2011 By 27 Comments
Can Shard-Query scale to 20 nodes? Peter asked this question in comments to to my previous Shard-Query benchmark. Actually he asked if it could scale to 50, but testing 20 was all I could due to to EC2 and time limits. I think the results at 20 nodes are very useful to understand the performance: [...]
