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Showing entries 1 to 8

Displaying posts with tag: Stéphane Combaudon (reset)

Many-table joins in MySQL 5.6
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I recently worked on an uncommon slow query: less than 100 rows were read and returned, the whole dataset was fitting in memory but the query took several seconds to run. Long story short: the query was a join involving 21 tables, running on MySQL 5.1. But by default MySQL 5.1 is not good at handling joins with such a large number of tables. The good news is that MySQL 5.6 brings welcome improvements.

Isolating the problem

As always with a slow query, finding the execution plan with EXPLAIN is the 1st step to understand where time is spent. Here the plan was very good with almost all joins using the primary key or a unique key, but perhaps the most interesting part was that EXPLAIN was very slow as well. This indicates that the optimizer takes a lot of time finding the optimal execution plan. To double check, we can run SHOW

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10 MySQL settings to tune after installation
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When we are hired for a MySQL performance audit, we are expected to review the MySQL configuration and to suggest improvements. Many people are surprised because in most cases, we only suggest to change a few settings even though hundreds of options are available. The goal of this post is to give you a list of some of the most critical settings.

We already made such suggestions in the past here on this blog a few years ago, but things have changed a lot in the MySQL world since then!

Before we start…

Even experienced people can make mistakes that can cause a lot of trouble. So before blindly applying the recommendations of this post, please keep in mind the following items:

  • Change one setting at a
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innodb_stats_on_metadata and slow queries on INFORMATION_SCHEMA
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INFORMATION_SCHEMA is usually the place to go when you want to get facts about a system (how many tables do we have? what are the 10 largest tables? What is data size and index size for table t?, etc). However it is also quite common that such queries are very slow and create lots of I/O load. Here is a tip to avoid theses hassles: set innodb_stats_on_metadata to OFF.

This is a topic we already talked about, but given the number of systems suffering from INFORMATION_SCHEMA slowness, I think it is good to bring innodb_stats_on_metadata back on the table.

The problem

Let’s look at a system I’ve seen recently: MySQL 5.5, working set fitting

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Handling long-running queries in MySQL with Percona XtraBackup
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I recently had a case where replication lag on a slave was caused by a backup script. First reaction was to incriminate the additional pressure on the disks, but it turned out to be more subtle: Percona XtraBackup was not able to execute FLUSH TABLES WITH READ LOCK due to a long-running query, and the server ended up being read-only. Let’s see how we can deal with that kind of situation.

In short

Starting with Percona XtraBackup 2.1.4, you can:

  • Configure a timeout after which the backup will be aborted (and the global lock released) with the lock-wait-threshold, lock-wait-query-type and lock-wait-timeout options
  • Or automatically kill all queries that prevent the lock to be granted with the kill-long-queries-timeout and
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Schema Design in MongoDB vs Schema Design in MySQL
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For people used to relational databases, using NoSQL solutions such as MongoDB brings interesting challenges. One of them is schema design: while in the relational world, normalization is a good way to start, how should we design our collections when creating a new MongoDB application?

Let’s see with a simple example how we would create a data structure for MySQL (or any relational database) and for MongoDB. We will assume in this post that we want to store people information (their name) and the details from their passport (country and validity date).

Relational Design

In the relational world, the basic idea is to try to stick to the 3rd normal form and create two tables (I’ll omit indexes and foreign keys for clarity – MongoDB supports indexes but not foreign keys):

mysql> select * from people;
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Percona Toolkit for MySQL Webinar Followup Questions
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I didn’t have time to answer all of the questions during Wednesday’s MySQL webinar, “5 Percona Toolkit Tools That Could Save Your Day,” but as promised, here are all of the questions and my answers. (A recording is available here.)

Q: One of the links to download the Percona Toolkit for MySQL (percona.com/get/percona-toolkit.tgz) doesn’t work!

A: You’re

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5 Percona Toolkit Tools for MySQL That Could Save Your Day: April 3 Webinar
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On April 3 at 10 a.m. PST, I’ll be giving a webinar titled “5 Percona Toolkit Tools for MySQL That Could Save Your Day.” In this presentation you’ll learn how to perform typical but challenging MySQL database administration tasks.

My focus will be on the following tools:

  • pt-query-digest, to select the queries you should try to improve to get optimal response times
  • pt-archiver, to efficiently purge purge data from huge
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Practical MySQL Indexing guidelines by Stéphane Combaudon
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Stéphane Combaudon of Dailymotion.

Index: separate data structure to speed up SELECTs. Think of index in a book. In MySQL, key=index. Consider that indexes are trees.

InnoDB’s clustered index – data is stored with the Primary Key (PK) so PK lookups are fast. Secondary keys hold the PK values. Designing InnoDB PK’s with care is critical for performance.

An index can filter and/or sort values. An index can contain all the fields needed for the query you don’t need to go to the table (a covering index).

MySQL only uses 1 index per table per query (not 100% true – OR clauses), so think of a composite index when you can. Can’t index TEXT fields (use a prefix). Same for BLOBs and long VARCHARs.

Indexes: speed up queries, increases the size of your dataset, slows down writes. How

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Showing entries 1 to 8

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