Earlier this month I blogged about our new Hadoop applier, I published the docs for that this week (http://docs.continuent.com/tungsten-replicator-3.0/deployment-hadoop.html) as part of the Tungsten Replicator 3.0 documentation (http://docs.continuent.com/tungsten-replicator-3.0/index.html). It contains some additional interesting nuggets that will appear in future blog posts.

The main part of that functionality that performs the actual applier for Hadoop is based around a JavaScript applier engine – there will eventually be docs for that as part of the Batch Applier content ( …

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 articles, we concentrated on methods that take exports or otherwise formatted and extracted data from your SQL source, load that into Hadoop in some way, then process or parse it. But if you want to analyze big data, you probably don’t want to wait while exporting the data. Here, we’re going to look at some methods and tools that enable a …

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.

SQL to Hadoop and back again, Part 2: …

I’ve got a new article, which is part of a new three-part series, on moving data between SQL and Hadoop, both the export to Hadoop and importing processed content back into an SQL store.

In this first one, we look at the basic mechanics and considerations before you start the migration of data, such as the data format, content, and export techniques.

Read: SQL to Hadoop and back again, Part 1: Basic data interchange techniques

Here at Monitis, we’re on a mission to not only build the best product but also, at the same time, make it more user-friendly. We listen to your feedback and suggestions and take various steps to improve our services, tools and features to make YOUR life easier. In any given week, you can see a new feature or update in your Monitis dashboard. Here’s some of the stuff we’ve added since our last newsletter, three months ago. Stay-up-to-date and see all that we have to offer by reading about all our changes below:

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I’ve just had a new article published with the Software Developers Journal talking about how you can write applications to take full advantage of Continuent Tungsten and Tungsten Replicator.

As a developer of an application there really isn’t a problem better than finding that you have to scale up the application and the database that supports it to handle the increased load. The main bottleneck to most expansion is the database server and in many modern environments that replication is based around MySQL. Application servers are easy to add on to the front-end of your environment.

Read: Qt5 – How to Become a Professional Developer- RELEASED | News | Magazine for software developers, programmers and designers – …

1. Apache and MySQL Logging with Syslog-ng
This article shows how to use the popular system logging tool Syslog-ng to log Apache and MySQL events. Apache does not log via syslog-ng by default so we go over two methods of easily remedying this. We also show how to use SQL queries to view syslog-ng data.

2. Using M3 to take System Monitors to the Next Level
Monitis provides built in functionality to monitor a wide variety of system statistics as well as the ability to create custom system monitors. Monitis Monitor Manager, or M3 for short, allows you to take these custom monitors …

1. Monitis–Where You Can Monitor Exchange 2010 with PowerShell
We’ve recently published a list of posts showing a variety of ways to monitor any application using the Monitis API. Microsoft Exchange is no exception. Here we go over how to use Management Shell or Management Console to speak to the Monitis API and feed data into a custom monitor. You can then generate charts and alert settings on this data.

2. Monitoring files and directories with Monitis
Things can go horribly wrong …

The MySQL database is a crucial part of a wide variety of products, particularly web applications. Naturally, it is very important to monitor the health status of MySQL.  However, there is constant disagreement on which of the many MySQL status variables provide the best overview on MySQL health status and indicate that something is not right with a server.

It certainly depends on what your application does – tuning read performance is different than optimizing write operations and everything changes when you have a cluster. The average user can use small subset of variables while advanced user want to get more detailed picture of the situation. So there cannot be one set of “magic variables” to quietly optimize every situation. However, it is possible to have a more-or-less optimal set of metrics that will allow to get a “good enough” notion about the general health status of MySQL Server.

The new white paper “ …

I hope everyone is enjoying summertime, at least in the northern hemisphere. I’m about to head out to the pool, but before I go, here is a summary of this week’s blog posts.

1. Introduction to Perl interface for Monitis API
Monitis announces a simple way to access its API through Perl, a high-level, general-purpose, interpreted, dynamic programming language. This post demonstrates some examples for using the API with Perl and describes some of the benefits of the programming language. The source can be found on our Github page.

2. 101 Tips to MySQL Tuning and Optimization …