Tips, Expertise, Articles and Advice from the Pro's for Your Website or Blog to Succeed
People like to complain about MongoDB. For instance, maybe they feel that it ruined their social network, or any number of other less recent complaints. The debate gets so heated, though, that sometimes valid criticisms - and nothing is above criticism - are dismissed as bandwagon hatred. It's a problem that Slava Kim seems very aware of in this recent blog post on some of the syntactic weirdnesses of MongoDB. It's not bashing, Kim stresses. For developers to effectively use any technology, they need to understand the "sharp edges."
Kim goes into detail for each warning, covering five general areas:
This third post in this series of blogs about MaxScale is finally getting where you want to go: Install and configure MaxScale. The first blog in this series was an overview of what MaxScale is and the second about how to set up a Cluster of MariaDB servers, using MariaDB Replication, for MaxScale to access. But now it's time to introduce MaxScale.
If you skipped the second post as you already know how to set up MariaDB with Replication and all that, be remineded that I will use the same Linux server setup as outlined there even for the MaxScale server and for a client to do some testing, and I recommend you stick with that for now (for MariaDB itself you can use any relevant setup you want, MaxSCale doesn't really care, but MaxScale is pretty new and has still not been tested on that many platforms, so try to stick to the CentOS 6.5 setup I propose.
for people in hurry, here is the code and some steps to run few demo samples .
disclaimer: i am still learning play 2.0, please point to me if something is incorrect.
[Editor's note: Be sure to check out part 1, part 2 and part 3 first.]
This is the fifth of a series of blogs introducing Apache HBase. In the fourth part, we saw the basics of using the Java API to interact with HBase to create tables, retrieve data by row key, and do table scans. This part will discuss how to design schemas in HBase.
I have talked about human filters and my plan for digital curation. These items are the fruits of those ideas, the items I deemed worthy from my Google Reader feeds. These items are a combination of tech business news, development news and programming tools and techniques.
I hope you enjoy today’s items, and please participate in the discussions on those sites.
A few months ago, we wrote a blog post on finding and terminating long-running operations in MongoDB. To help make it even easier for MongoLab users* to quickly identify the cause behind database unresponsiveness, we’ve integrated the currentOp() and killOp() methods into our management portal.
* currentOp and killOp functionality is not available on our free Sandbox databases because they run on multi-tenanted mongod processes.
In my last post, I described a new feature in TokuMX 1.5—partitioned collections—that’s aimed at making it easier and faster to work with time series data. Feedback from that post made me realize that some users may not immediately understand the differences between partitioning a collection and sharding a collection. In this post, I hope to clear that up.
On the surface, partitioning a collection and sharding a collection seem similar. Both actions take a collection and break it into smaller pieces for some performance benefit. Also, the terms are sometimes used interchangeably when discussing other technologies. But for TokuMX, the two features are very different in purpose and implementation. In describing each feature’s purpose and implementation, I hope to clarify the differences between the two features.
