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Showing entries 1 to 30 of 68 Next 30 Older Entries

Displaying posts with tag: data (reset)

Showing all available MySQL data types when creating a new table with MySQL for Excel
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In this blog post we are going to talk about one of the features included since MySQL for Excel 1.3.0, a new advanced option was added to the Export Data dialog to show all available MySQL data types on its Data Type combo-box to override its default behavior that shows only the most commonly used data types.

Remember you can install the latest GA or maintenance version using the MySQL Installer or optionally you can download directly any GA or non-GA version from the MySQL Developer Zone.

Optimistic updates for Edit Data operations in MySQL for Excel
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In this blog post regarding MySQL for Excel features included since version 1.2.0, we are going to talk about a new option that is used along with Edit MySQLData operations; very useful when editing data in a multi-user environment. If you are not familiar with editing MySQL data it is very advisable that you visit our thorough blog post about that topic: How To - Guide to editing MySQL data within Excel.

Remember you can install the latest GA or maintenance version using the MySQL Installer or optionally you can download directly any GA or non-GA version from the MySQL Developer Zone.  

How To - Guide to exporting data from Excel to a new MySQL table
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There may be times when you need to create a new table in MySQL and feed it with data from another database, the Internet or from combined data sources. MS Excel is commonly used as the bridge between those data sources and a target MySQL database because of the simplicity it offers to organize the information to then just dump it into a new MySQL table. Although the last bit sounds trivial, it may actually be a cumbersome step, creating ODBC connections within Excel through Microsoft Query may not help since these are normally created to extract data from MySQL into Excel, not the opposite. What if you could do this in a few clicks from within Excel after making your data ready for export to a MySQL database?

With MySQL for Excel you can do this and this guide will teach you how easy it is.

Anonymizing Data During Replication
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If you happen to work with personal data, chances are you are subject to SOX (Sarbanes-Oxley) whether you like it or not.

One of the worst aspects of this is that if you want to be able to analyse your data and you replicate out to another host, you have to find a way of anonymizing the information. There are of course lots of ways of doing this, but if you are replicating the data, why not anonymize it during the replication?

Of the many cool features in Tungsten Replicator, one of my favorites is filtering. This allows you to process the stream of changes that are coming from the data extracted from the master and perform operations on it. We use it a lot in the replicator for ignoring tables, schemas and columns, and for ensuring that we have the correct information within the THL.

Given this, let’s use it to anonymize the data as it is being

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SQL to Hadoop and back again, Part 2: Leveraging HBase and Hive
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The second article in a series covering Big Data and SQL interaction is available now:

“Big data” is a term that has been used regularly now for almost a decade, and it — along with technologies like NoSQL — are seen as the replacements for the long-successful RDBMS solutions that use SQL. Today, DB2®, Oracle, Microsoft® SQL Server MySQL, and PostgreSQL dominate the SQL space and still make up a considerable proportion of the overall market. Here in Part 2, we will concentrate on how to use HBase and Hive for exchanging data with your SQL data stores. From the outside, the two systems seem to be largely similar, but the systems have very different goals and aims. Let\’s start by looking at how the two systems differ and how we can take advantage of that in our big data requirements.

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What’s the data on the 3Ci Data Team?
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3Ci processes over a billion transactions a month. More than 100 million unique U.S. consumers have engaged with a business through our platform. All that activity creates massive amounts of data. The Data Team at 3Ci is responsible for keeping our offerings running at optimal performance and for making sense of our data. They manage MySQL [...]   [Read more...]
Announcing the MySQL Applier for Apache Hadoop
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Enabling Real-Time MySQL to HDFS Integration

Batch processing delivered by Map/Reduce remains central to Apache Hadoop, but as the pressure to gain competitive advantage from “speed of thought” analytics grows, so Hadoop itself is undergoing significant evolution. The development of technologies allowing real time queries, such as Apache Drill, Cloudera Impala and the Stinger Initiative are emerging, supported by new generations of resource management with Apache YARN

To support this growing emphasis on real-time operations, we are releasing a new

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Data Organization in InnoDB
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Introduction

This article will explain how the data is organized in InnoDB storage engine. First we will look at the various files that are created by InnoDB, then we look at the logical data organization like tablespaces, pages, segments and extents. We will explore each of them in some detail and discuss about their relationship with each other. At the end of this article, the reader will have a high level view of the data layout within the InnoDB storage engine.

The Files

MySQL will store all data within the data directory. The data directory can be specified using the command line option –data-dir or in the configuration file as datadir. Refer to the Server Command Options for complete details.

By default, when InnoDB is initialized, it creates 3

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How To: Storing and retrieving spatial data on MySQL server with Connector/Net
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Spatial data is being more used and needed at a larger number of applications. This type of data is not always easy to be managed or queried. And sometimes calculations need to be done in the application code instead of doing them at the server. Recently we added a new class to manage spatial data with Connector/Net, so our users can have the option to handle spatial data operations at their application code.
Running Out of Physical Disk Space
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Problem: You've a large table (or two) in a database on a partition that's running out of space, and you want to see if you can move that table to another drive.

Solution: Well, several actually. No silver bullet, but several options, some with conditions and some that require preparation. Let's look at some background information first.

How MySQL Stores Data 

OK, that's somewhat of an ambitious heading for an incidental paragraph or two, so to tone it back a bit, I'll summarise briefly.

  • The data directory is where MySQL stores databases, and it's set by the datadir server option. Each database is stored in a subdirectory of the data
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SELinux and MySQL
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I've previously written about AppArmor and MySQL, and how to change MySQL's default file locations on systems with AppArmor enabled. Ubuntu and SUSE ship with AppArmor enabled, but some other distributions such as Oracle Linux don't, along with related distrubutions such as Red Hat, CentOS and Fedora. Rather, these other distributions use another mandatory access control system called SELinux. 

Here's some technical detail that might come in handy later.

SELinux uses concepts such as types and domains. Types belong to resources such as files and ports; these are the "objects" in SELinux. Domains contain the "subjects" (processes) and object types that are associated with each other in some

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MySQL Web Reference Architectures - Your Guide to Innovating on the Web
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MySQL is deployed in 9 of the top 10 most trafficked sites on the web including Facebook, Twitter, eBay and YouTube, as well as in some of the fastest growing services such as Tumblr, Pinterest and box.com

Working with these companies has given MySQL developers, consultants and support engineers unique insight into how to design database-driven web architectures – whether deployed on-premise or in the cloud.

The MySQL Web Reference Architectures (http://www.mysql.com/why-mysql/white-papers/mysql-reference-architectures-for-scalable-web-infrastructure/) are a set of documented and repeatable best practices for building infrastructure that deliver the highest levels of scalability, agility and availability with the lowest levels of cost, risk and complexity. 

Four components common to most web and mobile properties are sized, with optimum

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AppArmor and MySQL
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MySQL accesses files in various places on the file system, and usually this isn't something to worry about. For example, in a standard MySQL 5.5 installation on Ubuntu, the data goes in /var/lib/mysql, and the socket is a file in /var/run/mysqld. It puts configuration files in /etc, logs and binaries in various locations, and it even needs to access some operating system files such as /etc/hosts.allow.

This is all very well until you start trying to be clever and get MySQL to access other parts of the file system. After all, you can configure the location of data, log files, socket, and so on, so why shouldn't you use those settings to optimize your system? Unfortunately, on many modern Linux distributions, it's not that always easy.

Take Ubuntu, for example. Ubuntu comes with something called AppArmor, a kernel-integrated application security system that controls how

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Upcoming MySQL Events
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Oracle's MySQL team is running/participating to a number of events during the upcoming weeks and months. Don't miss this chance to learn about the latest developments straight from the source and to get all your questions answered!

Additional events will likely be scheduled down the road and posted on our events page (http://www.mysql.com/news-and-events/events/), but you can already register for the following ones:

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MySQL and Hadoop Integration - Unlocking New Insight
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“Big Data” offers the potential for organizations to revolutionize their operations. With the volume of business data doubling every 1.2 years, analysts and business users are discovering very real benefits when integrating and analyzing data from multiple sources, enabling deeper insight into their customers, partners, and business processes.

As the world’s most popular open source database, and the most deployed database in the web and cloud, MySQL is a key component of many big data platforms, with Hadoop vendors estimating 80% of deployments are integrated with MySQL.

The new Guide to MySQL and Hadoop (http://www.mysql.com/why-mysql/white-papers/mysql_wp_hadoop.php) presents the tools enabling integration between the two data platforms, supporting the data lifecycle from

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On SSDs – Lifespans, Health Measurement and RAID
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Solid State Drive (SSD) have made it big and have made their way not only in desktop computing but also in mission-critical servers. SSDs have proved to be a break-through in IO performance and leave HDD far far behind in terms of Random IO performance. Random IO is what most of the database administrators would be concerned about as that is 90% of the IO pattern visible on database servers like MySQL. I have found Intel 520-series and Intel 910-series to be quite popular and they do give very good numbers in terms of Random IOPS. However, its not just performance that you should be concerned about, failure predictions and health gauges are also very important, as loss of data is a big NO-NO. There is a great deal of misconception about the endurance level of SSD, as its mostly compared to rotating disks even when measuring endurance levels, however, there is a big difference in how both SSD and HDD work, and that has a direct impact on the endurance level of SSD.
Configuring MySQL Cluster Data Nodes
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0 0 1 692 3948 Homework 32 9 4631 14.0 Normal 0 false false false EN-US JA X-NONE

In my previous blog post, I discussed the enhanced performance and scalability delivered by extensions to the multi-threaded data

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MySQL Cluster 7.2: Over 8x Higher Performance than Cluster 7.1
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0 0 1 893 5092 Homework 42 11 5974 14.0 Normal 0 false false false EN-US JA X-NONE

Summary

The scalability enhancements delivered by extensions to multi-threaded data nodes enables MySQL Cluster 7.2 (http://mysql.com/products/cluster/) to deliver over 8x higher

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Can the People's House become a social platform for the people?
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InSourceCode developers work on "Madison" with volunteers.

There wasn't a great deal of hacking, at least in the traditional sense, at the "first congressional hackathon." Given the general shiver that the word still evokes in many a Washingtonian in 2011, that might be for the best. The attendees gathered together in the halls of the United States House of Representatives didn't create a more interactive visualization of how laws are made or a mobile health app. As open government advocate Carl Malamud observed, the "hack" felt like something even rarer in the "Age of the App for


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Visualization of the Week: A better U.S. migration map
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Jon Bruner's "American Migration" visualization, based on IRS data, demonstrates how "Americans are enormously mobile: 37.5 million people moved from one house to another last year, with 4.3 million of them moving between states." Bruner's interactive map lets you click on a specific county and see both the immigration and emigration data for that location — where folks move from and where they move to.


Screenshot from the "American Migration" visualization (click for full

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CAOS Theory Podcast 2011.11.11
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Topics for this podcast:

*Continuent extends MySQL replication to Oracle Database
*CFEngine updates server automation software
*Devops moving mainstream
*Neo Technology integrates with Spring
*451 CAOS report from Hadoop World

iTunes or direct download (26:56, 4.6MB)

Oracle's NoSQL
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Oracle's turn-about announcement of a NoSQL product wasn't really surprising. When Oracle spends time and effort putting down a technology, you can bet that its secretly impressed, and trying to re-implement it in its back room. So Oracle's paper "Debunking the NoSQL Hype" should really have been read as a backhanded product announcement. (By the way, don't click that link; the paper appears to have been taken down. Surprise.)

I have to agree with DataStax and other developers in the NoSQL movement:

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Building data startups: Fast, big, and focused
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This is a written follow-up to a talk presented at a recent Strata online event.

A new breed of startup is emerging, built to take advantage of the rising tides of data across a variety of verticals and the maturing ecosystem of tools for its large-scale analysis.

These are data startups, and they are the sumo wrestlers on the startup stage. The weight of data is a source of their competitive advantage. But like their sumo mentors, size alone is not enough. The most successful of data startups must be fast (with data), big (with analytics), and focused (with services).

Setting the stage: The attack of the exponentials

The question of

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An iTunes model for data
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As we move toward a data economy, can we take the digital content model and apply it to data acquisition and sales? That's a suggestion that Gil Elbaz (@gilelbaz), CEO and co-founder of the data platform Factual made in passing at his recent talk at Web 2.0 Expo.

Elbaz spoke about some of the hurdles that startups face with big data — not just the question of storage, but the question of access. But as he addressed the emerging data economy, Elbaz said we will likely see novel access methods and new marketplaces for data. Startups will be able to build

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Uniform APIs for the data web
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The elmcity service connects to a half-dozen other services, including Eventful, Upcoming, EventBrite, Facebook, Delicious, and Yahoo. It's nice that each of these services provides an API that enables elmcity to read their data. It would be even nicer, though, if elmcity didn't have to query, navigate, and interpret the results of each of these APIs in different ways.

For example, the elmcity service asks the same question of Eventful, Upcoming, and EventBrite: "What are the titles, dates, times, locations, and URLs of recent events within radius R of location L?" It has to ask that question three different ways, and then interpret the answers three different ways. Can we imagine a more frictionless approach?

I can. Here's how the question might be asked in a general way using the

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What VMware's Cloud Foundry announcement is about
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I chatted today about VMware's Cloud Foundry with Roger Bodamer, the EVP of products and technology at 10Gen. 10Gen's MongoDB is one of three back-ends (along with MySQL and Redis) supported from the start by Cloud Foundry.


If I understand Cloud Foundry and VMware's declared "Open PaaS" strategy, it should fill a gap in services. Suppose you are a developer who wants to loosen the bonds between your programs and the hardware they run on, for the sake of flexibility, fast ramp-up, or cost savings. Your choices are:

An IaaS (Infrastructure as a Service) product, which hands you an emulation of


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Brian Aker explains Memcached
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Memcached is one of the technologies that holds the modern Internet together, but do you know what it actually does? Brian Aker has certainly earned the title of Memcached guru, and below he offers a peek under the hood. He'll also provide a deeper dive into Memcached in a tutorial at the upcoming 2011 MySQL Conference.

What problem is Memcached meant to solve?

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Outliers and coexistence are the new normal for big data
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Letting data speak for itself through analysis of entire data sets is eclipsing modeling from subsets. In the past, all too often what were once disregarded as "outliers" on the far edges of a data model turned out to be the telltale signs of a micro-trend that became a major event. To enable this advanced analytics and integrate in real-time with operational processes, companies and public sector organizations are evolving their enterprise architectures to incorporate new tools and approaches.

Whether you prefer "big," "very large," "extremely large," "extreme," "total," or another adjective for the "X" in the "X Data" umbrella term, what's important is accelerated growth in three dimensions: volume, complexity and speed.

Big data is not without its limitations. Many organizations need to revisit business processes, solve data silo

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Improving healthcare in Zambia with CouchDB
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A new healthcare project in Zambia is trying to integrate supervisors, clinics, and community healthcare workers (CHW) into a system that can improve patient service and provide more data about the effectiveness of care. Because of the technical challenges in an extreme rural setting, unique solutions are required. According to Cory Zue, chief technology officer of Dimagi, CouchDB went a long way toward keeping a consistent set of records under extreme circumstances. The full story will be laid out in Zue's talk at the upcoming MySQL conference, but here's a sneak peak.



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Broadband availability and speed visualized in new government map
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Today, the United States Department of Commerce's National Telecommunications and Information Administration (NTIA) unveiled a new National Broadband Map, which can be viewed at BroadbandMap.gov.

The map includes more than 25 million searchable records and it incorporates crowdsourced reporting. Built entirely upon Wordpress, the map is also one of the largest implementations of open source and open data in government to date.

Importantly, the data behind the map shows that despite an increase in broadband adoption to 68%, a digital divide persists between citizens who have full access to the rich media of the 2011 Internet and those who are limited by geography or means.

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Showing entries 1 to 30 of 68 Next 30 Older Entries

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