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Showing entries 1 to 15

Displaying posts with tag: Fractal Tree™ indexes (reset)

OLTP and OLAP – Have Your Cake and Eat it Too!
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Looks like we’ll be having some more fun at the Percona Live MySQL Conference! In addition to our booth and my colleague Tim’s talk, my lightning talk was accepted. The title is “OLTP and OLAP – Have Your Cake and Eat it Too!” The lightning talks, given in a TBD order, will start Wednesday evening (April 11th) at around 6:30 pm.

Below is the abstract I submitted.

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Fractal Tree Indexes and Mead – MySQL Meetup
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Thanks again to Sheeri Cabral  for having me at the Boston MySQL Meetup on Monday for the talk on “Fractal Tree® Indexes – Theoretical Overview and Customer Use Cases.” The crowd was very interactive, and I appreciated that over 50 people signed up for the event and left some very positive comments and reviews.

In addition, the conversation spilled over late into the night as we made our way over to nearby Mead


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FictionPress Selects TokuDB for Consistent Performance and Fast Disaster Recovery
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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

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Write Optimization: Myths, Comparison, Clarifications, Part 2
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In my last post, we talked about the read/write tradeoff of indexing data structures, and some ways that people augment B-trees in order to get better write performance. We also talked about the significant drawbacks of each method, and I promised to show some more fundamental approaches.

We had two “workload-based” techniques: inserting in sequential order, and using fewer indexes, and two “data structure-based” techniques: a write buffer, and OLAP. Remember, the most common thing people do when faced with an insertion bottleneck is to use fewer indexes, and this kills query performance. So keep in mind that all our work on write-optimization is really work for read-optimization, in that write-optimized

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Are You Forcing MySQL to Do Twice as Many JOINs as Necessary?
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Baron Schwartz This guest post is from our friends at Percona. They’re hosting Percona Live London from October 24-25, 2011. Percona Live is a two day summit with 100% technical sessions led by some of the most established speakers in the MySQL field.

In the London area and interested in attending? We are giving away two free passes in the next few days. Watch our @tokutek twitter feed for a chance to win.

Did you know that the following query actually performs a JOIN? You can’t see it, but it’s there:

SELECT the_day, COUNT(*), SUM(clicks),

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Write Optimization: Myths, Comparison, Clarifications
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Some indexing structures are write optimized in that they are better than B-trees at ingesting data. Other indexing structures are read optimized in that they are better than B-trees at query time. Even within B-trees, there is a tradeoff between write performance and read performance. For example, non-clustering B-trees (such as MyISAM) are typically faster at indexing than clustering B-trees (such as InnoDB), but are then slower at queries.

This post is the first of two about how to understand write optimization, what it means for overall performance, and what the difference is between different write-optimized indexing schemes. We’ll be talking about how to deal with workloads that don’t fit in memory—in particular, if we had our data in B-trees, only the internal nodes (perhaps not even all of them) would fit

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Online Advertiser Intent Media Selects TokuDB over InnoDB and NoSQL for Big Data Ad-Hoc Analysis
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Intent Media

Issue addressed: Ad hoc analytics on clickstream data arriving too fast for InnoDB or NoSQL to handle.

TokuDB powers an online advertising application

The Company: Headquartered in New York, Intent Media is a fast-growing online advertising startup. The company helps some of the largest online retailers monetize their traffic more efficiently at scale by showing highly relevant and targeted advertising to the 97+% of e-commerce visitors who do not transact.

The Challenge: The Intent Media platform processes hundreds of

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Ask What Your Database Can Do for Your Country
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How many in your household again?

One of President John Kennedy’s most memorable phrases is “ask not what your country can do for you –  ask what can you do for your country”.  I got to thinking about this over lunch with a fellow colleague in the big data space. After comparing named customers for a while, we realized we had forgotten one of the biggest “big data” customers whom we both have in common – the government.

Whether you believe in small or big government, one thing is

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It Actually is Easy Being Green
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(Fractal) Tree Frog

Fractal Tree™ indexes are green. They have the potential to be greener still. Here’s why:

Remarkably, data centers consume 1-3 percent of all the US electricity. A majority of this power is used to drive servers and storage systems. Significant energy savings remain on the table.

Here’s why Fractal Tree indexing enables more energy-efficient storage: Data centers typically use many small-capacity disks rather than a few large-capacity disks. Why? One reason is to harness more spindles to obtain more I/Os per second. In some high-performance applications, users go so

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Cage Match: OldSQL, NoSQL and NewSQL
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When I interviewed at Tokutek, I met a team of distinguished academics and engineers who could calmly and thoughtfully wax eloquent about the finer points of B-tree and Fractal Tree™ indexing,  drive I/Os, and database engines. Soon after, I discovered that several of my colleagues have a second passion — they practice Mixed Martial Arts (MMA). As Wikipedia explains, MMA showcases the “fighters of different disciplines, including boxing, Brazilian Jiu-Jitsu, wrestling, Muay Thai, karate and others.” I’ve since learned about many different fighting styles.

This was useful to understand when an MMA-style fight broke out in the MySQL world earlier this month between the different

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This Weekend in Japan
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We were happy to see a lot of folks from Japan on Twitter this weekend having a discussion about MySQL and Tokutek. While we always endeavor to explain ourselves as simply as possible, hearing what users and peers have to say and ask in their native language is very helpful. Here is a sampling of several of the 30+ tweets and re-tweets (translations courtesy of a colleague I know from frequent past visits to Tokyo and Yokohama):

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First, @frsyuki provided a general overview:

“TokuDB” 新種のMySQLストレージエンジン。INSERTが20〜80倍ほど速い、パーティションなしで数TBのデータを突っ込める、MVCCサポートなど。Fractal Treeというアルゴリズムを実装しているらしい。

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Dude, Where’s my Fractal Tree?
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Unless you are Ashton Kutcher (@aplusk), or one of his Hollywood buddies, you don’t need to read any further. Allow me to explain…

Over the weekend, we launched our new website. This type of announcement used to be interesting in the high-tech world. I heard Kara Swisher of the WSJ’s All things D speak at a MassTLC event in May.  She admitted back in the 1990s, when the web was just getting into high gear, that a new website from an interesting company might actually get some coverage. Not anymore.

I’ve also been told at all the SEO classes I’ve taken

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Understanding Indexing – SF MySQL Meetup
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At this week’s SF MySQL Meetup, I will give a talk: “Understanding Indexing: Three rules on making indexes around queries to provide good performance.” The meetup is 7 pm tomorrow (Wednesday, 6/22), and will be held at CBS Interactive (235 2nd St., San Francisco). Thanks to hosts Erin O’Neill and Mike Tougeron for the invitation and location.

Application performance often depends on how fast a query can respond and query performance almost always depends on good indexing. So one of the quickest and least expensive ways to increase application performance is to optimize the indexes. This talk presents three simple and effective rules on how to construct indexes around queries that result in good performance.

This is a general discussion applicable to all databases using indexes and is not

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Effective MySQL, a New York City Meetup
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Kudos to Ronald Bradford for creating a new MySQL meetup group in New York city and giving MySQL related talks. The next one is tonight, titled “MySQL Idiosyncrasies That Bite”. Information on it can be found at http://ny.effectivemysql.com/events/16884850/.

We’ll have a contingent from our New York office there this evening. We went to the last one on indexing (a favorite topic of ours) in March and it was excellent.

We look forward to seeing folks there as well as at upcoming NY events, including Percona Live (May 26th) and future Effective MySQL meetups.

Announcing TokuDB v4.1.1
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Tokutek is pleased to announce immediate availability of TokuDB for MySQL, version 4.1.1. It is ideally suited for delivering fast response times for complex / high-volume Web applications that must simultaneously store and query large volumes of rapidly arriving data:

  • Social Networking
  • Real-time clickstream analysis
  • Logfile Analysis
  • eCommerce Personalization
  • High-speed Webcrawling

TokuDB v4.1.1 replaces TokuDB v4.1.0 and is recommended for all users. (We found a bug in v4.1.0 and have withdrawn it from our website). The new version has all of v4.1.0′s new features, including support for SAVEPOINT and an even better Fast Loader. As always, this release uses our high-performance Fractal Tree™ indexing to provide a unique combination of capabilities:

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    Showing entries 1 to 15

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