FictionPress

Issues addressed:

• Support complex and efficient indexes at 100+ million rows.
• Predicable and consistent performance regardless of data size growth.
• Fast recovery.

Ensuring Predictable Performance at Scale

The Company:  FictionPress operates both FictionPress.com and FanFiction.net and is home to over 6 million works of fiction, with millions of writers/readers participating from around the world in over 30 languages

The Challenge: FictionPress offers a number of interactive features to its large user base. These …

It’s almost the end of the year – that means holiday cards, shopping, cooking, parties, and the inevitable year-end top lists (including gems like this one).

In the spirit of end of year list making, we fed our 60+ blogs this year through Google Analytics to find out what our own top ten blogs were (outside of product announcements). So if you missed an episode of the View (TokuView that is) we’ve got a Tokutek Top Ten for you (spoiler alert – they are mostly technical):

10. Cage Match: OldSQL, NoSQL and NewSQL – References to mud …

Limelight Networks

Issue addressed: Managing metadata at exabyte scale

Delivering Agile Storage in the Cloud with Billions of Assets

The Company: Founded in 2001, Limelight Networks, Inc (NASDAQ: LLNW) is an Internet platform and services company that integrates the most business-critical parts of the online content value chain. Limelight’s cloud-based services enable customers to profit from the shift of content and advertising to the online world, from the explosive growth of mobile and connected devices, and from the migration of IT applications and services to the cloud. More than 1,800 customers worldwide use Limelight’s massively scalable services to better engage audiences, optimize advertising, manage and monetize …

At next month’s Boston MySQL Meetup, I will give a talk: “Fractal Tree Indexes – Theoretical Overview and Customer Use Cases.” The meetup is 7 pm Monday, January 9th, 2012, and will be held at MIT Building E51 Room 337e (corner of Ames & Amherst St, Cambridge, MA). Thanks to host Sheeri Cabral for the invitation.

Most databases employ B-trees to achieve a good tradeoff between the ability to update data quickly and to search it quickly. It turns out that B-trees are far from the optimum in this tradeoff …

As a storage engine developer, I am excited for MySQL 5.6. Looking at http://dev.mysql.com/tech-resources/articles/whats-new-in-mysql-5.6.html, there has been plenty of work done to improve the performance of reads in MySQL for all storage engines (provided they take advantage of the new APIs).

What would be great to add is API improvements to increase the performance of writes, and more specifically, updates. For many applications that perform updates, such as applications that do click counting or impression counting, there are significant opportunities for improving write performance.

Take the following example of click counting (or impression counting). You have a website and want to save the number of times links on your website have been clicked. Your table may look something like:


create table …

With the release of TokuDB v5.0 last March, we delivered a powerful and agile storage engine that broke through traditional MySQL scalability and performance barriers. As deployments of TokuDB have grown more varied, one request we have repeatedly heard from customers and prospects, especially in areas such as online advertising, social media, and clickstream analysis, is for improved performance for multi-client workloads.

Tokutek is now pleased to announce limited beta availability for TokuDB v5.2. The latest version of our flagship product offers a significant improvement over TokuDB v5.0 in multi-client scaling as well as performance gains in point queries, range queries, and trickle load speed. There are a host of other smaller changes and improvements that are detailed in our release notes (available to beta participants).

TokuDB continues to lead the field by offering:

• 20x to …

Thanks to everyone who signed up and attended the webinar I gave this week with Tim Callaghan on Scaling MySQL. For those who missed it and are interested, the video and slides are now posted here.

A brief description of the webinar is also below.

MySQL implementations are often kept relatively small, often just a few hundred GB or less. Anything beyond this quickly leads to painful operational problems such as poor insertion rates, slow queries, hours to days offline for schema changes, prolonged downtime for dump/reload, etc. The promise of scalable MySQL has remained largely unfulfilled, until TokuDB.

TokuDB v5.0 delivers

• Exceptional Agility — Hot Schema Changes allow read/write operations during index creation or …

 
This version includes support for “SELECT … FOR UPDATE” as well as displaying table “create time” and “last update time” via “SHOW TABLE STATUS”. The release also addresses a number of other bugs and fixes such as “point update” and “replace into” deadlocks. For more details, see the release notes section of the user’s guide, available here. To get the latest version of TokuDB (free for evaluation, development, testing, qualification, experimentation, and POCs ) click here. Starting with this release, we’ve also streamlined the installation process by creating a combined tarball that includes both MySQL and TokuDB.

Note that we’ll be hosting an upcoming webinar on November 15th for those who want to learn more about TokuDB in general as well as …

I’ll be talking about How Fractal Trees Work  today at MIT in the Computational Research In Boston and Beyond (CRIBB) seminar (http://www-math.mit.edu/crib/2011/nov4.html). The talk is at 12:30 in the Stata Center room 32-141.  Pizza available before.

This talk will be academically-oriented (not much marketing).  The abstract is as follows:

Most storage systems employ B-trees to achieve a good tradeoff between the ability to update data quickly and to search it quickly.  It turns out that B-trees are far from the optimimum in this tradeoff space. I’ll talk about Fractal Tree indexes, which were developed in a collaboration between MIT, Stony Brook, and Rutgers.  I’ll talk about how they work, and what their performance bounds are.  My startup, Tokutek, is commercializing fractal tree …

MySQL implementations are often kept relatively small, often just a few hundred GB or less. Anything beyond this quickly leads to painful operational problems such as poor insertion rates, slow queries, hours to days offline for schema changes, prolonged downtime for dump/reload, etc. The promise of scalable MySQL has remained largely unfulfilled, until TokuDB.

Time: 2PM EST / 11AM PST

REGISTER TODAY

TokuDB v5.0 delivers

• Exceptional Agility — Hot Schema Changes allow read/write operations during index creation or column/field addition
• Unmatched Speed — Fractal Tree indexes are optimized for index insertion performance
• Maximum Scalability — Fractal Tree index performance scales even as the primary index …