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10 Newer Entries Showing entries 31 to 40 of 175 10 Older Entries

Displaying posts with tag: big data (reset)

SQL to Hadoop and back again, Part 3: Direct transfer and live data exchange
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The third, and final article in my series on migrating data to and from Hadoop and SQL databases is now available:

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. In this final article of the series, we will look at more automated solutions for migrating data to and from Hadoop. In the previous …

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Log Buffer #346, A Carnival of the Vanities for DBAs
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Economist says that Physics suggest that storms will get worse as the planet warms. Typhoon Haiyan in Philippines, bush-fires in Australia, floods in China, and extreme unpredictable weather across the planet is a sober reminder. Good news is that technology and awareness is rising, and so is the data. Database technologies are playing their part to intelligently store that data and enabling the stakeholders to analyze and get meaningful results to predict and counter the extreme conditions. This Log Buffer Edition appreciates these efforts.

Big Data:

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Copying MySQL Data to Hadoop with Minimal Loss of Blood Part 2
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I have spent the better part of the last month at Big Data conferences trying to see behind the $2.5 million in marketing smoke to see what is really going to be showing up on the to-do list of DBAs. The first bit of news is that half the vendors at shows like Strata or Big Data Techon will probably be gone by this time next year. So picking a vendor right now is a little iffy. Hadoop’s ecosystem is flourishing and will surely be around for some time but the vendors are playing musical chairs.

But we are Open Source and we do not need vendors! Well, yes and no. The good folks at Cloudera and Horton Works have …

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Big Data Tools that You Need to Know About – Hadoop & NoSQL – Part 2
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In the previous article we introduced Hadoop as the most popular Big Data toolset on the market today. We had just started talking about MapReduce as the major framework that makes Hadoop distinctive. So let’s continue the discussion where we left off.

 

MapReduce is really the key to understanding Hadoop’s parallel processing …

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Big Data – What is it and Why is it Important – Part 4
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In Part 3 of this series we found out that Big Data is a huge revenue generator for business that is expected to drive $232 billion in spending through 2016. In this installment we’ll continue to explore why Big Data must become a critical part of any business strategy in the 21st century.

 

First, the Bad News

 

Okay, so we get the notion of what Big Data is and why it’s important for business. So what can be done …

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November 6 Webinar: 5 Pitfalls to Avoid with MySQL and Big Data
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You love MySQL for its ease of deployment – but are you worried about how your application will perform when it starts to scale?

SPEAKER: Gerry Narvaja, Tokutek
DATE: Wednesday, November 6th
TIME: 1pm ET
Register Now!

Join this interactive webinar with Gerry Narvaja of Tokutek as he walks through the potential pitfalls when using MySQL for Big Data applications, how you can avoid unnecessary tolls on time and resources and tips on how to get the most …




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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, …

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Data Analytics at NBCUniversal. Interview with Matthew Eric Bassett.
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“The most valuable thing I’ve learned in this role is that judicious use of a little bit of knowledge can go a long way. I’ve seen colleagues and other companies get caught up in the “Big Data” craze by spend hundreds of thousands of pounds sterling on a Hadoop cluster that sees a few megabytes [...]

Copying MySQL Data to Hadoop with Minimal Loss of Blood Part 1
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Ask ten DBAs for a definition of ‘Big Data’ and you well get more than ten replies. And the majority of those replies will lead you to Hadoop. Hadoop has been the most prominent of the big data frameworks in the open source world. Over 80% of the Hadoop instances in the world are feed their data from MySQL1. But Hadoop is made up of many parts, some confusing and many that do not play nicely with each other. It is analogous to being given a pile of automotive parts from different models and tyring to come up with a car at the end of the day. So what if you do if you are wanting to copy some of your relational data into …

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Big Data.. So what? Part 2
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Sorry for this delay in providing part 2 of this series, but stuff happened that had really high priority, and in addition I was on vacation. But now I'm back in business!

So, last time I left you with some open thought on why Big Data can be useful, but that we also need new analysis tools as well as new ways of visualizing data for this to be truly useful. As for analysis, lets have a look at text, which should be simple enough, right? And sometimes it is simple. One useful analysis tool that is often overlooked is Google. Let's give it a shot, just for fun: if I think of two fierce competitors, somehow, that we can compare, say Oracle …

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10 Newer Entries Showing entries 31 to 40 of 175 10 Older Entries

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