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Displaying posts with tag: Performance (reset)
Impact of the number of idle connections in MySQL

Be careful with my findings, I appear to have compile in debug mode, I am redoing the benchmarks. Updated version here.

I recently had to work with many customers having large number of connections opened in MySQL and although I told them this was not optimal, I had no solid arguments to present. More than once, I heard: it is not a problem, those connections are Sleeping! In order to remedy to this situation, I decided to run a series of DBT2 benchmarks while the number of idle connections was varied from 0 to 1500. I was expecting an influence, because those idle threads are presents in internal MySQL list objects that need to be scanned and also the socket SELECT call needs to build a FD bitmap after every network activity and the size of the bitmap is proportional to the number of active …

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MariaDB optimization for string related operations

In our upcoming MariaDB 5.3 release Monty optimized the internal string append code for performance. I tested his patch with a plain MariaDB 5.2 vs. a patched MariaDB 5.2 with sql-bench, which showed an overall performance gain around 3%.

The details of the patch Monty describes like this

Patch to optimize string append:

While examining a trace output from a mysql-test-run case, I noticed a
lot of reallocation calls.  This was strange as MariaDB/MySQL was
designed to do so few malloc/realloc as possible.  The system uses was
to first calculate how big buffer you would need and then allocate a
buffer big enough for most usage. Then there was some safety calls to
extend the buffer if needed.

What had happened in the MySQL code over time was that new coders was
using a buffer that was not …

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Five reasons to upgrade to MySQL 5.5

I have been looking forward to the general availability (GA) release of MySQL 5.5 since is was publically announced in September that we would see this in 2010. While I already have a production client with 5.5.7rc, the badge of general availability is a great way to promote why environments should consider moving to using MySQL 5.5. Here is my quick short list of why I’d promote moving to MySQL 5.5.

1. Improved integration

The first significant improvement is that InnoDB is now again firmly a default included storage engine. The InnoDB plugin 1.1.x is now the builtin version of the engine, not a plugin version. Also the 1.1.x version has continued improvements over the 1.0.x version available as an included but not enabled plugin in current MySQL 5.1.x versions. Removing the complexity for end users over the choice of InnoDB and the necessary configuration changes is a great simplification. The introduction in the InnoDB plugin …

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MySQL Partitioning – can save you or kill you

I wanted for a while to write about using MySQL Partitioning for Performance Optimization and I just got a relevant customer case to illustrate it. First you need to understand how partitions work internally. Partitions are on the low level are separate table. This means when you're doing lookup by partitioned key you will look at one (or some of) partitions, however lookups by other keys will need to perform lookup in all partitions and hence can be a lot slower. The gain from updates typically comes from having smaller BTREE on the active partition(s) which allows for a lot better fit. Having potentially fewer level in BTREE is not that significant issue.

So lets see at example:

PLAIN TEXT SQL:

  1. CREATE TABLE `tbl` (
  2.   `id` bigint(20) UNSIGNED AUTO_INCREMENT NOT NULL,
  3.   `uu` varchar(255) DEFAULT NULL,
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How well does your table fits in innodb buffer pool ?

Understanding how well your tables and indexes fit to buffer pool are often very helpful to understand why some queries are IO bound and others not - it may be because the tables and indexes they are accessing are not in cache, for example being washed away by other queries. MySQL Server does not provide any information of this type, Percona Server however adds number of tables to Information Schema which makes this information possible. It is just few queries away:

PLAIN TEXT SQL:

  1. mysql> SELECT `schema` AS table_schema,innodb_sys_tables.name AS table_name,innodb_sys_indexes.name AS index_name,cnt,dirty,hashed,round(cnt*100/index_size,2) fit_pct   FROM (SELECT index_id,count(*) cnt,sum(dirty=1) dirty ,sum(hashed=1) hashed FROM innodb_buffer_pool_pages_index GROUP BY …
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MySQL At Scale – Zynga Games

Recently am part of Zynga‘s database team as I was pretty much impressed with company’s database usage. As everyone knows how popular Zynga games like Farmville, Cafe World, Mafia Wars,[...]

MySQL Query Optimization – Tip # 1 – Avoid using wildcard character at the start of a LIKE pattern.

The more I go through others SQL, there are some common mistakes that I see developers making over and over again, so I thought why not start a series of tips that can help developers optimize their queries and avoid common pitfalls. So this post is a part of that series of tips, and this is the first tip "Avoid using a wild card character at the start of a LIKE pattern".

MySQL - My new playground

Note: It was my first attempt using the MySQL UDF Api back then. The library is still maintained and got some new features. Check out the new MySQL Infusion UDF.

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Why do I recommend switching over from MyISAM to Innodb!

Although MyISAM has been the default storage engine for MySQL but its soon going to change with the release of MySQL server 5.5. Not only that, more and more people are shifting over to the Innodb storage engine and the reasons for that is the tremendous benefits, not only in terms of performance, concurrency, ACID-transactions, foreign key constraints, but also because of the way it helps out the DBA with hot-backups support, automatic crash recovery and avoiding data inconsistencies which can prove to be a pain with MyISAM. In this article I try to hammer out the reasons why you should move on to using Innodb instead of MyISAM.

random poking

These are some of my notes from some sysbench in-memory r/o testing in past day or so:

  • At ‘fetch data by primary key’ benchmark with separate read snapshots at each statement, MySQL shines until ~200 concurrent threads, then performance starts dropping slightly faster than one would want, I think mostly from table cache LOCK_open contention
  • auto-commit cost (establishing read snapshot per statement) for SELECTs is ~10% for MySQL, but for PG it can be +50% in plain SQL mode and +130% (!!!!!!!) when using prepared statements (this can be seen in a graph – obviously the global …
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