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Displaying posts with tag: innodb (reset)
Is 80% of RAM how you should tune your innodb_buffer_pool_size?

It seems these days if anyone knows anything about tuning InnoDB, it’s that you MUST tune your innodb_buffer_pool_size to 80% of your physical memory. This is such prolific tuning advice, it seems engrained in many a DBA’s mind.  The MySQL manual to this day refers to this rule, so who can blame the DBA?  The question is: does it makes sense?

What uses the memory on your server?

Before we question such advice, let’s consider what can take up RAM in a typical MySQL server in their broad categories.  This list isn’t necessarily complete, but I think it outlines the large areas a MySQL server could consume memory.

  • OS Usage: Kernel, running processes, filesystem cache, etc.
  • MySQL fixed usage: query cache, InnoDB …
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MySQL 5.7 key features

The other day I was discussing new features of MySQL 5.7 with a Percona Support customer. After that conversation, I thought it would be a good idea to compile list of important features of MySQL 5.7. The latest MySQL 5.7.6 release candidate (RC) is out and is packed with nice features. Here’s a list of some MySQL 5.7 key features.

Replication Enhancements:

  • One of the top features in MySQL 5.7 is multi-source replication. With multi-source replication you can point multiple master server’s to slave so limitation of slave having only one master is lift off. There is nice blog post written by my colleague on multi-source replication you will find useful.
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Creating and Restoring Database Backups With mysqldump and MySQL Enterprise Backup – Part 1 of 2

Part 1 of 2: (part two)
If you have used MySQL for a while, you have probably used mysqldump to backup your database. In part one of this blog, I am going to show you how to create a simple full and partial backup using mysqldump. In part two, I will show you how to use MySQL Enterprise Backup (which is the successor to the InnoDB Hot Backup product). MySQL …

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MySQL indexing 101: a challenging single-table query

We discussed in an earlier post how to design indexes for many types of queries using a single table. Here is a real-world example of the challenges you will face when trying to optimize queries: two similar queries, but one is performing a full table scan while the other one is using the index we specially created for these queries. Bug or expected behavior? Read on!

Our two similar queries

# Q1
mysql> explain select col1, col2 from t where ts >= '2015-04-30 00:00:00';
+----+-------------+---------------+------+---------------+------+---------+------+---------+-------------+
| id | select_type | table         | type | possible_keys | key  | key_len | ref  | rows    | Extra       |
+----+-------------+---------------+------+---------------+------+---------+------+---------+-------------+
|  1 | SIMPLE      | t …
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LinkBenchX: benchmark based on arrival request rate

An idea for a benchmark based on the “arrival request” rate that I wrote about in a post headlined “Introducing new type of benchmark” back in 2012 was implemented in Sysbench. However, Sysbench provides only a simple workload, so to be able to compare InnoDB with TokuDB, and later MongoDB with Percona TokuMX, I wanted to use more complicated scenarios. (Both TokuDB and TokuMX are part of Percona’s product line, in the case you missed Tokutek now part of the Percona family.)

Thanks to Facebook – they provide LinkBench, a benchmark that emulates the social graph …

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InnoDB locks and deadlocks with or without index for different isolation level

Recently, I was working on one of the issue related to locks and deadlocks with InnoDB tables and I found very interesting details about how InnoDB locks and deadlocks works with or without index for different Isolation levels.

Here, I would like to describe a small test case about how SELECT ..FOR UPDATE (with and without limit) behave with INSERT/UPDATE and with READ-COMMITED and REPEATABLE-READ Isolation levels. I’m creating a small table data_col with few records. Initially, this test case was written by Bill Karwin to explain details to customer, but here I have used a bit modified test case.

CREATE TABLE data_col (dataname VARCHAR(10), period INT, expires DATE, host VARCHAR(10));

INSERT INTO data_col VALUES (‘med1′, …

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JSON Labs Release: Effective Functional Indexes in InnoDB

In MySQL 5.7.6, we added a new feature called Generated Columns. In the initial work all Generated Columns were materialized, even virtual ones. This not only resulted in unnecessary disk space being used and disk I/O being done, but it also meant that any table alteration required that the full table be rebuilt. In the new MySQL 5.7.7 JSON Lab release, we have resolved all of these issues by implementing new features that not only allow users to create non-materialized virtual …

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InnoDB 全文検索 : MeCab Parser

(この記事は InnoDB Full-Text: MeCab ParserYoshiaki Yamasaki が翻訳したものです)

このブログ記事で紹介した一般的なCJK(中国語、日本語、韓国語)のサポートに加えて、私達はMeCabパーサーも追加しました。MeCabは日本語の形態素解析エンジンで、私達は今 …

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More on (transactional) MySQL metadata locks

Two years ago Ovais Tariq had explained in detail what kinds of problems existed before MySQL introduced metadata locks in 5.5.3 and how these locks help to prevent them. Still, some implications of metadata locking in MySQL remain unclear for users – DBAs and even software developers that target recent MySQL versions. I’ve decided to include a slide or two into the presentation about InnoDB locks and deadlocks I plan to make (with my colleague Nilnandan Joshi) on April 16 at Percona Live 2015.

I decided to do this as …

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Illustrating Primary Key models in InnoDB and their impact on disk usage

On a recent engagement I worked with a customer who makes extensive use of UUID() values for their Primary Key and stores it as char(36), and their row count on this example table has grown to over 1 billion rows.

The table is INSERT-only (no UPDATEs or DELETEs), and the bulk of their retrieval are PK lookups. Lookups by PK were performing acceptably, but they were concerned with the space usage by the table as we were approaching 1TB (running with innodb_file_per_table=1 and Percona Server 5.5).

This schema model presents an increasing burden for backups since they use Percona XtraBackup, and so the question was asked: does their choice of an effectively random Primary Key based on UUID() impact their on-disk storage, and to what extent? And as a neat trick I show towards the end of this post how you can calculate the …

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