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Previous 30 Newer Entries Showing entries 61 to 90 of 158 Next 30 Older Entries

Displaying posts with tag: big data (reset)

Two Cons against NoSQL. Part I.
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Two cons against NoSQL data stores read like this: 1. It’s very hard to move data out from one NoSQL to some other system, even other NoSQL. There is a very hard lock in when it comes to NoSQL. If you ever have to move to another database, you have basically to re-implement a lot [...]
Webinar: MongoDB and Fractal Tree Indexes
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This webinar covers the basics of B-trees and Fractal Tree Indexes, the benchmarks we’ve run so far, and the development road map going forward.

Date: November 13th
Time: 2 PM EST / 11 AM PST
REGISTER TODAY

Topics will include:

  • What is a Fractal Tree Index?
  • How to Fractal Trees compare with B-Trees
  • What can a Fractal Tree do for MongoDB performance
  • Benchmarks + Gotchas
  • What’s next

We look forward to having you join the webinar. We also hope that by sharing these results with



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On Eventual Consistency– Interview with Monty Widenius.
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“For analytical things, eventual consistency is ok (as long as you can know after you have run them if they were consistent or not). For real world involving money or resources it’s not necessarily the case.” — Michael “Monty” Widenius. In a recent interview, I asked Justin Sheehy, Chief Technology Officer at Basho Technologies, maker [...]
Presenting “MongoDB and Fractal Tree Indexes” at MongoDB Boston 2012
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I’ll be presenting “MongoDB and Fractal Tree Indexes” at MongoDB Boston 2012 on October 24th.  My presentation covers the basics of B-trees and Fractal Tree Indexes, the benchmarks we’ve run so far, and the development road map going forward.

I’ve been to this one day conference twice now and both times came away with a better understanding of MongoDB’s capabilities, use-cases, and many questions answered via their deep technical dives.  I highly recommend current MongoDB users and anyone considering a MongoDB project attend – it appears that seats are still available.

First of New NSF Big Data Grants Go to Tokutek Founders
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The core technology behind Tokutek is based on the academic research by our founders: Michael Bender, Bradley Kuszmaul and Martin Farach-Colton.  They are all still in academia, in addition to their work at Tokutek.

Back in March, the White House kicked off a new Initiative for Big Data.  Last week, the National Science Foundation announced the first interagency grants for this.  Eight awards were given, and our own Michael Bender and Martin Farach-Colton, along with Robert Johnson of Stony Brook University, received one of

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Scaling MySQL and MariaDB to TBs: Interview with Martín Farach-Colton.
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“While I believe that one size fits most, claims that RDBMS can no longer keep up with modern workloads come in from all directions. When people talk about performance of databases on large systems, the root cause of their concerns is often the performance of the underlying B-tree index”– Martín Farach-Colton. Scaling MySQL and MariaDB [...]
Log Buffer #289, A Carnival of the Vanities for DBAs
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Oracle Open World 2012, this year, was all about Cloud, 12c, Exadata, Fusion, SuperClusters, social media, content management and much more. From operating systems to databases, and from applications to interactive media, professionals all around the world presented, attended, and networked in San Francisco. MySQL’S professionals also rocked massively. SQL Server bloggers also remained actively [...]
Forbes: “Tokutek Makes Big Data Dance”
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Recently, our CEO, John Partridge had a chance to talk about novel database technologies for “Big Data” with Peter Cohan of Forbes.

According to the article, “Fractal Tree indexing is helping organizations analyze big data more efficiently due to its ability to improve database efficiency thanks to faster ‘database insertion speed, quicker input/output performance, operational agility, and data compression.’” As a start-up based on “the  first algorithm-based breakthrough in the database world in 40 years,” Toktuetek is following in the footsteps of firms such as Google and RSA, which also relied on novel algortithm advances as core to their technology.

To read the full article, and

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Tips for Leveraging Oracle OpenWorld 2012 From Pythian Marketing
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With Oracle OpenWorld just around the corner & MySQL Connect already underway I can’t believe yet another year has passed.  This is my third OOW and I must have a following as folks are already reaching out to me on twitter @pythiansimmons (log buffer lady seems to be a handle I can’t seem to shake). [...]
Announcing TokuDB v6.5: Optimized for Flash
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We are excited to announce TokuDB® v6.5, the latest version of Tokutek’s flagship storage engine for MySQL and MariaDB.

This version offers optimization for Flash as well as more hot schema change operations for improved agility.

We’ll be posting more details about the new features and performance, so here’s an overview of what’s in store.

Flash TokuDB v6.5 continues the great Toku-tradition of fast insertions. On flash drives, we show an order-of-magnitude (9x) faster insertion rate than InnoDB. TokuDB’s standard compression works just as well on flash and helps you get the most out of your  [Read more...]
Data Fabrics and Other Tales: Percona Live and MySQL Connect
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The fall conference season is starting.  I will be doing a number of talks including a keynote on "future proofing" MySQL through the use of data fabrics.  Data fabrics allow you to build durable, long-lasting systems that take advantage of MySQL's strengths today but also evolve to solve future problems using fast-changing cloud and big data technologies.  The talk brings together ideas that Ed Archibald (our CTO) and I have been working on for over two decades.  I'm looking forward to rolling them out to a larger crowd.

Here are the talks in calendar order.  The first two are at MySQL Connect 2012 in San Francisco on September 30th:



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Pythian at OOW12
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Every time I have had the pleasure of attending Oracle Open World, I have discovered a plethora of technical heavy-weights from all over the world in attendance. I enjoy meeting and shmoozing with these people almost as much as absorbing the technical content of the show itself. Many of my Pythian colleagues are presenting at [...]
Oracle High Availability and More with Continuent Tungsten
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Oracle is the most powerful database system in the world. However, Oracle's expensive and complex replication makes it difficult to build highly available applications or move data in real-time to data warehouses and popular databases like MySQL. In this video (recording of our 9/13/12 webinar) you will learn how Continuent Tungsten solves problems with Oracle replication at a fraction of the
XLDB Tutorial on Data Structures and Algorithms
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Next week Michael and I (Bradley) will be travelling to Silicon Valley to present a tutorial on Data Structures and Algorithms for Big Databases at the 6th XLDB Conference.

The tutorial, which is 4 hours on Monday afternoon, aims to cover the following topics (but it’s looking like we’ll have to drop several items for lack of time.)

This tutorial will explore data structures and algorithms for big databases. The topics include:

  • Data structures including B-trees, Log Structured Merge Trees, and Streaming B-trees.
  • Approximate Query Membership data structures including Bloom filters and cascade filters.
  • Algorithms for join including hash joins and
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Facebook makes big data look... big!
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Oh I love these things: http://techcrunch.com/2012/08/22/how-big-is-facebooks-data-2-5-billion-pieces-of-content-and-500-terabytes-ingested-every-day/

Every day there are 2.5B content items shares, and 2.7B "Like"s. I care less about GiGo content itself, but metadata, connections, relations are kept transactionally in a relational database. The above 2 use-cases generate 5.2B transactions on the database, and since there are only 86400 seconds a day, we get over 60000 write transactions per second on the database, from these 2 use-cases alone, not to mention all other use-cases, such as new profiles, emails, queries...

And what's the



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Scale Up, Partitioning, Scale Out
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On the 8/16 I conducted a webinar titled: "Scale Up vs. Scale Out" (http://www.slideshare.net/ScaleBase/scalebase-webinar-816-scaleup-vs-scaleout):


ScaleBase Webinar 8.16: ScaleUp vs. ScaleOut from ScaleBase
The webinar was successful, we had many attendees and great participation in questions and answers throughout the session and in the end. Only after the webinar it only occurred to me that one specific graphic was missing from the webinar deck. It was occurred to me after answering



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Y Gatorz are Considering Moving Back to a Gator Farm Instead of MapReducing the World
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NSFW (audio) “…pipe your data to /dev/null – it will be very fast.” “Does /dev/null support sharding?” NSFW (audio) “…the only thing constructive we could have used their source files for was as random keys for SSL certs.” NSFW (audio) “PHP reeks … Continue reading →
FROSCON and VLDB
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Next week I (Bradley) will be traveling to FROSCON near Bonn, Germany, and then on to VLDB in Istanbul.

At FROSCON I’ll be talking about fast data structures for maintaining indexes. The talk will share some content with my upcoming MySQL Connect talk.

At VLDB, Dzejla Medjedovic will be presenting a talk on our paper on SSD-friendly Bloom-filter-like data structures. The paper is

Michael A. Bender, Martin Farach-Colton, Rob Johnson, Russell Kraner, Bradley C. Kuszmaul, Dzejla Medjedovic, Pablo Montes, Pradeep Shetty, Richard P. Spillane, and Erez Zadok.
Don’t Thrash: How to Cache Your Hash on Flash. PVLDB 5(11):1627-1637, 2012.

An earlier version of the paper appeared at


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Dagstuhl Seminar on Database Workload Management
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A few weeks ago Bradley Kuszmaul and I attended the Dagstuhl Seminar on Database Workload Management.

The Dagstuhl computer science research center is (remotely) located in the countryside in Saarland, Germany. The actual building is an 18th Century Manor House, first retooled as an old-age home, and then a computer science research center. Workshop participants typically spend the whole week talking and working together.

Dagstuhl Computer Science Center

Shivnath Babu (Duke University), Goetz Graefe (Hewlett Packard),

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A Few Thoughts on OSCon and the Open Source Community
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This past week I attended OSCon, the annual conference for open source’s true believers. And there was a religious fervor in the air, particularly from the point of view of someone more accustomed to Oracle conferences.

And if open source is the religion, proprietary closed-source companies are the devil. That having been said, I was surprised how virtually all large companies were demonized. Even long-time defenders of open source like IBM were ignored at best. That didn’t prevent them from coming though, with Microsoft and HP in particular with high-profile sponsorships and PR offensives that didn’t seem to have much influence with the crowd.

The companies generating buzz were the small companies built around development of their own open source products. There are a surprising number of them out

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Webinar: Understanding Indexing
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Three rules on making indexes around queries to provide good performance

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.


Time: 2PM EDT / 11AM PDT

This webinar is a general discussion applicable to all databases using indexes and is not specific to any particular MySQL® storage engine


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So now Hadoop's days are numbered?
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Earlier this week we all read GigaOM's article with this title:
"Why the days are numbered for Hadoop as we know it"
I know GigaOM like to provoke scandals sometimes, we all remember some other unforgettable piece, but there is something behind it...

Hadoop today (after SOA not so long ago) is one of the worst case of an abused buzzword ever known to men. It's everything, everywhere, can cure illnesses and do "big-data" at the same time! Wow! Actually Hadoop is a software framework that supports data-intensive distributed applications, derived from Google's MapReduce and Google File System (GFS) papers.

My take from the article is




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My Talks at MySQL Connect and Percona Live NYC
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Solving the Challenges of Big Databases with MySQL

When you’re using MySQL for big data (more than ten times as large as main memory), these challenges often arise: loading data fast; maintaining indexes under insertions deletions, and updates; adding and removing columns online; adding indexes online; preventing slave lag; and compressing data effectively.

This session shows why some of these challenges are difficult to solve with storage engines based on B-trees, how Fractal Tree® data structures work, and why they can help solve these problems. Tokutek sells a transaction-safe Fractal Tree storage engine for MySQL, but the presentation is primarily about the underlying technology. It includes a discussion of both the theoretical and practical aspects of Fractal Tree indexes.

I have the privilege of being able to give


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ARM based data center. Inspiring.
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In a previous post I wrote ARM based servers. Since then, and thanks to all the comments and responses I got, I looked more into this ARM thing and it's absolutely fascinating...

Look at this beauty (taken from the site of Calxeda, the manufacturer):

What is it? A chip? A server? No, it's a cluster of 4 servers...

And this:







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Hot Table Optimization with MySQL
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Table optimization is a necessary evil; tables sometimes need to be optimized to reclaim space or to improve query performance.  Unfortunately, MySQL blocks writes to a table while it is being optimized.  Because optimization time is proportional to the table size, writes can be blocked for a long time.  Fractal Tree indexes support online optimization; however, the MySQL metadata lock gets in the way of writing while optimizing.  We will describe a simple patch to MySQL that enables online optimization of TokuDB tables.

Why do tables need to be optimized?  Here are some reasons.

  • Insertions with random keys can result in a tree with underutilized leaf blocks.  Many tree algorithms split nodes in half when they become full.  If these nodes are stored in fixed sized blocks, like many B-trees do, then there can be a lot of wasted space.  Table optimization of
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The catch-22 of read/write splitting
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In my previous post I covered the shard-disk paradigm's pros and cons, but the conclusion that is that it cannot really qualify as a scale-out solution, when it comes to massive OLTP, big-data, big-sessions-count and mixture of reads and writes.

Read/Write splitting is achieved when numerous replicated database servers are used for reads. This way the system can scale to cope with increase in concurrent load. This solution qualifies as a scale-out solution as it allow expansion beyond the boundaries of one DB, DB machines are shared-nothing, can be added as a slave to the replication "group" when required.



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Why shared-storage DB clusters don't scale
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Yesterday I was asked by a customer for the reason why he had failed to achieve scale with a state-of-the-art "shared-storage" cluster. "It's a scale-out to 4 servers, but with a shared disk. And I got, after tons of work and efforts, 130% throughput, not even close to the expected 400%" he said.

Well, scale-out cannot be achieved with a shared storage and the word "shared" is the key. Scale-out is done with absolutely nothing shared or a "shared-nothing" architecture. This what makes it linear and unlimited. Any shared resource, creates a tremendous burden on each and every database server in the cluster.

In a previous post, I identified database engine activities such as buffer management, locking, thread locks/semaphores,



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Basement Nodes: Turning Big Writes into Small Reads
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Executive Summary

Fast indexing requires the leaves of a Fractal Tree® Index to be big. But some queries require the leaves to be small in order to get any reasonable performance. Basements nodes are our way to achieve these conflicting goals, and here I’ll explain how.

Big Leaves

On many occasions, we at Tokutek have pointed out that TokuDB is write optimized, which means TokuDB indexes data much faster than a B-tree solution such as InnoDB. As with any write-optimized data structure, Fractal Tree indexes need to bundle up lots of small writes into a few big writes. Otherwise, there’d be no way to beat a B-tree. So the question is, how big do the writes have to be?

Consider how long it takes to write k bytes to a disk. First, there is the seek time s, which we can assume to be independent of k.

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The Sound and the NoSQL Fury
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The signal-to-noise ratio in the NoSQL world has made it hard to figure out what’s going on, or even who has something new. For all the talk of performance in the NoSQL world, much of the most exciting part of what’s new is really not about performance at all.

Take for example, MongoDB, which has a really great data model and MapReduce has a very handy scripting language. These are genuine and probably long-lasting contributions. Their innovation is all about finding a new language to use for interacting with data. They are about NoSQL.

The confusion comes, for me, when we get to the performance side of the equation. I explore this in detail in an article I did for Datanami recently – http://www.datanami.com/datanami/2012-05-22/the_sound_and_the_nosql_fury.html.

Review of the Tutorial on Algorithms for Memory Sensitive Computing at STOC
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Martin Farach-Colton and I ran a Tutorial on Algorithms for Memory Sensitive Computing on May 18th at the 44th ACM Symposium on Theory of Computing (STOC) at NYU. Here is the program for the tutorial.

Erik Demaine (MIT) spoke on the History of I/O Models. Throughout the years, a remarkable variety of computational models have been proposed to explain the effects of caching, data locality, prefetching, and single-and multi-level memory hierarchies. Erik traced the intellectual history and connections between these models. Most approaches

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