My colleague and teammate Ernie Souhrada will be presenting a webinar on Wednesday, August 21, 2013 at 10 a.m. PDT titled “MySQL Security: Armoring Your Dolphin.”

This is a popular topic with news breaking routinely that yet another Internet company has leaked private data of one form or another. Ernie’s webinar will be a great overview of security MySQL from top to bottom, including changes related to security in the 5.6 release.

Topics to be covered include:

• Basic …

Following our events earlier this year in Raleigh, Montevideo, Buenos Aires, Toronto and Portland, we bring Percona University to …

This is part 3 of a 3 part series covering the new InnoDB full-text search features in MySQL 5.6. To catch up on the previous parts, see part 1 or part 2

Some of you may recall a few months ago that I promised a third part in my InnoDB full-text search (FTS) series, in which I’d actually take a look at the performance of InnoDB FTS in MySQL 5.6 versus traditional MyISAM FTS. I hadn’t planned on quite such a gap between part 2 and part 3, but as they say, better late than never. Recall that we have been working with two data sets, one which I call SEO (8000-keyword-stuffed web pages) and the other which I call DIR (800K directory records), and we are comparing MyISAM FTS in …

The new Percona Server 5.6 is the most manageable, highest performance, and most scalable version of MySQL available. Percona Server 5.6 is the best open source MySQL choice for enterprise-grade applications because it combines new features with the best features of Percona Server 5.5 and MySQL 5.6 to provide unparalleled performance.

Join me tomorrow as I explain how Percona Server 5.6 takes MySQL performance to new heights. In this webinar, aptly titled “Percona Server 5.6: Enterprise Grade MySQL,” I’ll compare Percona Server 5.6 to …

If we have InnoDB pages there are two ways to learn how many records they contain:

• PAGE_N_RECS field in the page header
• Count records while walking over the list of records from infimum to supremum

In some previous revision of the recovery tool a short summary was added to a dump which is produced by the constraints_parser.

But if a page is lost and page_parser hasn’t found it, all records from this page are lost. In other words per-page recovery statistics gives us little idea about whether or not a recovered table is complete.

To cover this flaw a new tool index_check is introduced in …

In writing a recommendation for our Web development team on how to use MySQL, I came up with the following list, which I want to share: What kind of queries are bad for MySQL?

• Any query is bad. Send a query only if you must. (Hint: use caching like memcache or redis)
• Queries that examine many rows are bad. Try instead to use…
  

      SELECT col1 FROM table1 WHERE primary_key_column=SOMETHING

  
  . Or at least
  

  secondary_key_column=SOMETHING

  
  . If it is still not possible, try to make the query examine the least amount of rows possible (zero is ideal, as we come to the first case here)
• Queries with JOINS are bad. Try to denormalize the table to avoid JOINS. Example: original query
  

      SELECT t2.value FROM t2 JOIN t1 ON (t1.id=t2.tid) WHERE t1.orderdate=NOW()

  
  . This can be denormalized by copying the column orderdate from table …

MySQL 5.6 introduces a new feature – microseconds resolution in some temporal types. As of 5.6.4 TIME, TIMESTAMP and DATETIME can have a fractional part. To create a field with subseconds you can specify precision in brackets: TIME(3), DATETIME(6) etc.

Obviously, the new feature requires the format change. All three types may now have a tail with a fractional part. The tail may be one, two or three bytes long and can store up to six digits after the point.

The non-fractional part has changed too. Thus, DATETIME uses only five bytes comparing to eight in previous versions.

As of revision 79 the …

Dolphin and Elephant: an Introduction

This post is intended for MySQL DBAs or Sysadmins who need to start using Apache Hadoop and want to integrate those 2 solutions. In this post I will cover some basic information about the Hadoop, focusing on Hive as well as MySQL and Hadoop/Hive integration.

First of all, if you were dealing with MySQL or any other relational database most of your professional life (like I was), Hadoop may look different. Very different. Apparently, Hadoop is the opposite to any relational database. Unlike the database where we have a set of tables and indexes, Hadoop works with a set of text files. And… there are no indexes at all. And yes, this may be shocking, but all scans are sequential (full “table” scans in MySQL terms).

So, when does Hadoop makes sense?

First, Hadoop is great if you need to …

For the same customer I am exploring ZFS for backups, the twin server is using regular LVM and XFS. On this twin, I have setup mylvmbackup for a more conservative backup approach. I quickly found some odd behaviors, the backup was taking much longer than what I was expecting. It is not the first time I saw that, but here it was obvious. So I recorded some metrics, bi from vmstat and percent of cow space used from lvs during a backup. Cow space is the Copy On Write buffer used by LVM to record the modified pages like they were at the beginning of the snapshot. Upon reads, LVM must scan the list to verify that there’s no newer version. Here’s the other details about the backup:

• Filesystem: 2TB, xfs
• Snapsize: 60GB
• Amount to backup: ~600GB
• Backup tool: mylvmbackup
• Compressor: pbzip2

…

Among many of the improvements you can enjoy in MySQL 5.6, there is one that addresses a huge operational problem that most DBAs and System Administrators encounter in their life: schema changes.

While it is usually not a problem for small tables or those in early stages of product life cycle, schema changes become a huge pain once your tables get a significant amount of data. Planning for maintenance is becoming more and more difficult, and your worldwide users want the service to be up and running 24/7, while on the other hand, your developers desire to introduce schema changes every week.

PITA

But what is the real problem here? Let me illustrate very typical case:

Session1> ALTER TABLE revision ADD COLUMN mycol tinyint;
Query OK, 1611193 rows affected (1 min 5.74 sec)
Records: 1611193  Duplicates: 0 …