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Previous 30 Newer Entries Showing entries 61 to 90 of 742 Next 30 Older Entries

Displaying posts with tag: performance (reset)

OurSQL Episode 167: Data, Data Everywhere
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This week we discuss test data sets. Ear Candy is errata from Episode 165 on Galera Cluster, and At the Movies is "Runaway Complexity in Big Data"

Test Data Sets
Episode 81, where we talked about different benchmark tools
Sysbench - general version
Percona's sysbench tests

Factors: # tables, concurrency, data set size

Episode 143, where we did an ear candy featuring Morgan Tocker's article on estimating MySQL's working set with INFORMATION_SCHEMA

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MySQL 5.7.3: Deep dive into 1mil QPS with InnoDB Memcached
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As you probably already know, in MySQL 5.7.3 release, InnoDB Memcached reached a record of over 1 million QPS on read only workload. The overview of the benchmark and testing results can be seen in an earlier blog by Dimitri. In this blog, I will spend sometime on the detail changes we have made to achieve this record number.

First thanks to Facebook’s Yoshinori with his bug#70172 that brought our attention to this single commit read only load test. We have been focussing on operation with large batch size. This bug prompted us to do a series of optimization on single commit read only queries and these optimizations eliminated almost all major bottlenecks from the

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OurSQL Episode 166: Top Hat Options
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This week we discuss fine-tuning Galera Cluster. In this week's ear candy we talk about recent changes to mysqldump and locking; At the Movies presents "Using Amazon Web Services for MySQL at Scale".

Events
DB Hangops - every other Wednesay at noon Pacific time
FOSDEM 2014 - Sat February 1 - Sun February 2 in Brussels, Belgium.
Upcoming MySQL events (http://www.mysql.com/news-and-events/events/)

Training
SkySQL Trainings

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Improving connect/disconnect performance
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In some application scenarios (e.g. PHP applications) client connections have very short durations, maybe only executing a single query. This means that the time spent processing connects and disconnects can have a large impact on the overall performance.

In MySQL 5.6 we started working on optimizing the code handling connects and disconnects. And this work has accelerated in MySQL 5.7. In this blog post I will first show the results we have achieved and then describe what we have done to get them.

The results

The graph below shows a comparison of the most recent 5.5 and 5.6 releases as well as the 5.7.2 and 5.7.3 milestones. We measured the number of queries per second (QPS) where each client executes a single query (point select) before disconnecting. For each server

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OurSQL Episode 165: Top Hat Cluster
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This week we talk about how to install and set up Galera Cluster. Ear Candy talks about the new MySQL repos from Oracle and what to know about using them; At the Movies is Michael Stonebreaker talking about how to process today's big data transactional processing needs.

Galera Cluster
Codership documentation of Galera Cluster
Installing Percona XtraDB Cluster on Ubuntu documentation
MariaDB's Galera Cluster documentation

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MySQL/MariaDB single-threaded performance regressions, and a lesson in thread synchronisation primit
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I took a quick look at MariaDB 10.0 single-treaded performance (simple read-only sysbench). One thing immediately leaps to the eye, and I thought it worthy of mention. It contains an important lesson about the use of synchronisation primitives and in particular "atomic operations" in MariaDB (and MySQL).

I am using the Linux perf tool on this sysbench command:

  sysbench --num-threads=1 --test=oltp --oltp-test-mode=simple --oltp-read-only --oltp-skip-trx
Look at the top offender in the output from perf report:
  1,54%  mysqld  mysqld               [.] set_thread_state_v1
The only thing this does is set a string for SHOW PROCESSLIST (and the like) about what the thread is doing. And we are spending a whopping 1.5% of the total time doing this.

And why? That becomes clear when looking

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MySQL 5.7 : Over 1M QPS with InnoDB Memcached Plugin
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Or I could place in the title – “Yes, we done it!”

After reaching 500K QPS in Read-Only on SQL queries, it was natural to expect a much higher performance level from InnoDB Memcached Plugin which is by-passing all SQL related layers.. However the story is not simple, and yet far from finished

While for today we have already our first “preview” results showing that we’re able to reach over 1,000,000 Query/sec level with the latest MySQL 5.7 code:

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Optimizing MySQL Database Operations for Better Performance
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If you are responsible for a MySQL Database, you make choices based on your priorities; cost, security and performance.

To learn more about improving performance, take the MySQL Performance Tuning course

In this 4-day instructor-led course you will learn practical, safe and highly efficient ways to optimize performance for the MySQL Server. It will help you develop the skills needed to use tools for monitoring, evaluating and tuning MySQL.

You can take this course via the following delivery methods:Training-on-Demand:

  • Take this course at your own pace, starting training within 24 hours of registration.
  • Live-Virtual Event: Follow a
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After 10 Years, MySQL Still the Right Choice for ScienceLogic's "Best Network Monitoring System on the Planet"
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ScienceLogic has a pretty fantastic network monitoring appliance.  So good in fact that InfoWorld gave it their "2013 Best Network Monitoring System on the Planet" award.  Inside their "ultraflexible, ultrascalable, carrier-grade" enterprise appliance, ScienceLogic relies on MySQL and has since their start in 2003.  Check out some of the things they've been able to do with MySQL and their reasons for continuing to use MySQL in these highlights from our new MySQL ScienceLogic case study (http://www.mysql.com/why-mysql/case-studies/mysql-best-for-sciencelogic.html).
  • Science Logic's larger customers use their appliance to monitor and manage  20,000+ devices, each of which generates a steady stream of data and

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FAQ: InnoDB extended secondary keys
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MySQL 5.6 introduced a new feature called extended secondary keys. We get a lot of questions about it and find that most of them come from a few incorrect assumption. In this post I’ll try to get rid of the confusion once and for all. Famous last words… here goes:


Q1: Do I need to do anything to enable extended secondary keys?No, nothing at all. It’s on by default and I can’t see any sensible reason why you would want to disable it. However, it is possible to disable it by tuning the optimizer_switch: SET optimizer_switch=’use_index_extensions={on|off}’.

 

Q2: Does extended secondary keys only work with InnoDB?

No, it should work with any storage engine that uses the primary key columns as reference to the row, which means most storage engines with clustered primary keys. I say
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TokuDB configuration variables of interest
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During our experiments I came upon a few TokuDB variables of interest; if you are using TokuDB you might want to look into these:

  • tokudb_analyze_time

This is a boundary on the number of seconds an ANALYZE TABLE will operate on each index on each partition on a TokuDB table.

That is, if tokudb_analyze_time = 5, and your table has 4 indexes (including PRIMARY) and 7 partitions, then the total runtime is limited to 5*4*7 = 140 seconds.

Default in 7.1.0: 5 seconds

  • tokudb_cache_size

Similar to innodb_buffer_pool_size, this variable sets the amount of memory allocated by TokuDB for caching pages. Like InnoDB the table is clustered within

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FAQ: InnoDB extended secondary keys
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MySQL 5.6 introduced a new feature called extended secondary keys. We get a lot of questions about it and find that most of them come from a few incorrect assumption. In this post I'll try to get rid of the confusion once and for all. Famous last words... here goes:

Q1: Do I need to do anything to enable extended secondary keys?

No, nothing at all. It's on by default and I can't see any sensible reason why you would want to disable it. However, it is possible to disable it by tuning the optimizer_switch: SET optimizer_switch='use_index_extensions={on|off}'.

Q2: Does extended secondary keys only work with InnoDB?

No, it should work with any storage engine that uses the primary key columns as reference to the row, which means most storage engines with clustered primary keys. I say







  [Read more...]
InnoDB scalability issues due to tables without primary keys
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Each day there is probably work done to improve performance of the InnoDB storage engine and remove bottlenecks and scalability issues. Hence there was another one I wanted to highlight: Scalability issues due to tables without primary keys. This scalability issue is caused by the usage of tables without primary keys. This issue typically shows itself as contention on the InnoDB dict_sys mutex. Now the dict_sys mutex controls access to the data dictionary. This mutex is used at various important places throughout the InnoDB code and as such any contention on the dict_sys mutex is going to have a InnoDB system-wide negative affect.

The post InnoDB scalability issues due to tables without primary keys appeared first on ovais.tariq.

InfiniDB column store moves to open source ! Congrats !
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Like TokuDB, InfiniDB is now a fully open source server product. In the past infiniDB was “almost open source”. The open source version was an old release with no access to the advance functions like MPP multi-server execution. This is no more the case. With InfiniDB 4 the open source version is the latest release [...]

The TSA Method
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TSA Method in class (SmartOS)

There are two basic performance analysis methodologies you can use for most performance issues. The first is the resource-oriented USE Method, which provides a checklist for identifying common bottlenecks and errors. The second is the thread-oriented TSA Method, for identifying issues causing poor thread performance. I summarized the TSA Method in my Stop The Guessing talk at Velocity conf this year, and it is also covered in the Applications chapter of my


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OurSQL Episode 158: Know Your Forks
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This week we discuss features of Percona Server 5.6 compared to MySQL 5.6. Ear Candy is about pt-upgrade, and At the Movies is a set of lightning talks.

Events
DB Hangops - every other Wednesay at noon Pacific time

Upcoming MySQL events (http://www.mysql.com/news-and-events/events/)

Percona Live London 2013 is happening Monday November 11th and Tuesday November 12th, 2013 at the Millenium Gloucester Conference Center

Training
SkySQL Trainings

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A new kid in the MySQL sharding world
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MySQL Connect 2013 has been a great edition. There was of course a lot of nice announcements of improvements in the the core MySQL server technology. One of the major announcement that received a lot of buzz was MySQL Fabric. MySQL Fabric is an infrastructure component aimed at simplifying construction of a highly available, sharded, [...]

InnoDB Temporary Tables just got faster
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It all started with a goal to make InnoDB temporary tables more effective. Temporary table semantics are blessed with some important characteristics that can help us simplify lot of operations.

  • Temporary tables are not visible across connections
  • Temporary tables lifetime is limited to connection lifetime (unless user explicitly drops it).

What does this means in to InnoDB ?

  • REDO logging can be avoided for temporary tables and related objects since temporary tables do not survive a shutdown or crash.
  • Temporary table definitions can be maintained in-memory without persisting to the disk.
  • Locking constraints can be relaxed since only one client can see these tables.
  • Change buffering can be avoided since the
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MySQL 5.7.2 : Good job Oracle! (Well, almost)
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On September 21st, during the opening keynote at MySQL Connect 2013, Tomas Ulin disclosed the release of MySQL 5.7.2. This is a milestone release that includes several new features. Unlike the Previous one, which was just a point of pride, where Oracle was stating its continuous commitment to releasing new versions of MySQL. In MySQL 5.7.2, we see several new features:

  • First and foremost, performance. The announcement slides say MySQL 5.7.2 is 95% faster than MySQL 5.6 and 172% faster than MySQL 5.5. I don’t know yet in which circumstances these numbers hold true, but I am sure someone at Percona will soon prove or disprove the claim.
  • Performance Schema tables for several aspects:
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InnoDB 5.7 performance improvements
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A quick overview of the InnoDB performance improvements for both read-only and read-write loads.
Tuning MySQL 5.6 for Great Product Performance: FAQs
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“Will you expand the next webcast to 90 minutes? This one was too interesting to last only one hour” was one of the questions we got during the “Tuning MySQL for Great Product Performance: The Fundamentals, Updated for MySQL 5.6” (http://www.mysql.com/news-and-events/web-seminars/tuning-mysql-for-great-product-performance-the-fundamentals-updated-for-mysql-5-6/) webinar on August 27th.  The engineers on Q&A got a lot of good (and more technical) questions during the webcast.  For those of you who were unable to join us live, I’ve posted the questions and answers below, and you can listen to a recording of the webinar and get a .pdf of slides at this link. (http://www.mysql.com/news-and-events/web-seminars/tuning-mysql-for-great-product-performance-the-fundamentals-updated-for-mysql-5-6/)

The webinar was created specifically for the software and

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TokuMX vs. MongoDB : In-Memory Sysbench Performance
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In talking to existing MongoDB users and TokuMX evaluators, I’ve often heard that the performance of MongoDB is very good as long as your working data set fits in RAM. The story continues that if your working data set grows to be larger than the RAM on your server, the built-in sharding capabilities of MongoDB allow you to scale horizontally.

As my benchmarking presentation at Percona Live 2013 pointed out, I’m never one to accept something without at least running it once myself. I decided to run my

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MySQL Brings Huge Performance Improvements with Each Release
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The MySQL engineering team constantly works to bring you huge performance improvements with each new release of MySQL. Here are four ways to help you get the most from these improvements

Tap into Sveta Smirnova's MySQL performance expertise on October 1st 2013 at 10am Central European Time, by attending the 1-day virtual seminar, Troubleshooting MySQL Performance with Sveta Smirnova. Sveta starts with basics, working towards more advanced cases that DBAs usually need years of experience to identify or solve. Click here to learn more about this seminar and to register for the event.

The

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Converting an OLAP database to TokuDB, part 1
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This is the first in a series of posts describing my impressions of converting a large OLAP server to TokuDB. There's a lot to tell, and the experiment is not yet complete, so this is an ongoing blogging. In this post I will describe the case at hand and out initial reasons for looking at TokuDB.

Disclosure: I have no personal interests and no company interests; we did get friendly, useful and free advice from Tokutek engineers. TokuDB is open source and free to use, though commercial license is also available.

The case at hand

We have a large and fast growing DWH MySQL setup. This data warehouse is but one component in a larger data setup, which includes Hadoop, Cassandra and more. For online dashboards and most reports, MySQL is our service. We populate this warehouse mainly via Hive/Hadoop. Thus, we have an hourly load of data from Hive, as

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Indexing Talk Online
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I am doing a quick blog post to announce that I have put an indexing talk online*. Most recently, I delivered this indexing talk at Confoo and Scale 11x.

The talk is on YouTube at Are You Getting the Best Out of Your MySQL Indexes? There are also PDF slides.
From the official conference description, if you want to know more:
MySQL indexes are often used to make performance better. However, they can make performance suffer if you are not using them properly. Oracle ACE Director Sheeri Cabral explains the pitfalls to avoid with indexes and how to utilize compound indexes to maximize index availability with the least amount of write overhead.

*I know I have not



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Memory Leak (and Growth) Flame Graphs
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Memory Leak

Memory Flame Graph
   

Your application memory usage is steadily growing, and you are racing against time to fix it. This could either be memory growth due to a misconfig, or a memory leak due to a software bug. For some applications, performance can begin to degrade as garbage collection works harder, consuming CPU. If an application grows too large, performance can drop off a cliff due to paging (swapping), or the application may be killed by the system (OOM killer). You want to take a

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Tune MySQL for Top-Level Performance
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In 4 days, the MySQL Performance Tuning training teaches you practical, safe and highly efficient ways to optimize performance for the MySQL Server. It will help you:

  • Evaluate the architecture
  • Understand and use the tools.
  • Configure the database for performance.
  • Tune application and SQL code.
  • Tune the server.
  • Examine the storage engines.
  • Assess the application architecture.
  • Understand general tuning concepts.

You can take this instructor-led course as a:

  • Training-on-Demand offering: Start training within 24 hours of regsitration, taking this course at
  [Read more...]
OurSQL Episode 147: It's Web Scale
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This week we talk with Tim Callaghan of Tokutek about TokuMX, a take on MongoDB. Ear Candy is perror on Windows and At the Movies is a presentation from the SkySQL and MariaDB Solutions Day 2013 about Tokutek.

TokuMX

Replication between MySQL and MongoDB using Tungsten a couple of years ago at Open DB Camp in Sardinia (2011).

Previous interviews with Tokutek folks in:
Episode 39

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Why Unique Indexes are Bad
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Before creating a unique index in TokuMX or TokuDB, ask yourself, “does my application really depend on the database enforcing uniqueness of this key?” If the answer is ANYTHING other than yes, do not declare the index to be unique. Why? Because unique indexes may kill your write performance. In this post, I’ll explain why.

Unique indexes are a strange beast: they have no impact on standard databases that use B-Trees, such as MongoDB and MySQL, but may be horribly painful for databases that use write optimized data structures, like TokuMX’s Fractal Tree(R) indexes. How? They

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What the Mean Really Means
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When analyzing response time, or latency, you need much more information than an average provides. The average, commonly the arithmetic mean, shows the index of central tendency. But, as I found in earlier posts, the tendency is often not central, but may be skewed by outliers, or split by multiple modes. How often these factors occur was determined quantitatively, using tests and a survey of hundreds of production servers and different types of latency: over 95% had six-sigma outliers, and

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