Where I’m reviewing support for encryption in the context of IaaS|PaaS|SaaS cloud service offerings as well as concerning Hadoop. While the motivation for encryption might differ, the primary question is if systems support this (transparently) or if developers are forced to code this in the application logic. Continue reading
In situations where Hadoop is used in a shared setup we witness two competing forces: the user expects performance vs. the view of the cluster owner who aims to optimise throughput and maximise utilisation. In the post, Michael elaborates a bit on challenges and solutions on this topic. Continue reading
You might have already heard that MapR, the leading provider of enterprise-grade Hadoop and friends, is launching its European operations. Guess what? I’m joining MapR Europe as of January 2013 in the role of Chief Data Engineer EMEA and will support our technical and sales teams throughout Europe. Pretty exciting times ahead! As an aside: … Continue reading
Today’s question is: where are we regarding MapReduce/Hadoop in the cloud? That is, what are the offerings of Hadoop-as-a-Service or other hosted MapReduce implementations, currently? A year ago, InfoQ ran a story Hadoop-as-a-Service from Amazon, Cloudera, Microsoft and IBM which will serve us as a baseline here. This article contains the following statement: According to … Continue reading
Last week was Halloween and of course we went trick-or-treating with our three kids which resulted in piles of sweets in the living room. Powered by the sugar, the kids would stay up late to count their harvest and while I was observing them at it, I was wondering if it possible to explain the … Continue reading
As nicely pointed out by Ilya Katsov: Denormalization can be defined as the copying of the same data into multiple documents or tables in order to simplify/optimize query processing or to fit the user’s data into a particular data model. So, I was wondering, why is – in Ilya’s write-up – denormalization not considered to be … Continue reading
The value of large-scale datasets – stemming from IoT sensors, end-user and business transactions, social networks, search engine logs, etc. – apparently lies in the patterns buried deep inside them. Being able to identify these patterns, analyzing them is vital. Be it for detecting fraud, determining a new customer segment or predicting a trend. As … Continue reading
Imagine you search for a camera, say a Canon EOS 60D, and in addition to the usual search results you’re as well offered a choice of actions you can perform on it, for example share the result with a friend, write a review for the item or, why not directly buy it? Sounds far fetched? … Continue reading
Two widely used data formats on the Web are CSV and JSON. In order to enable fine-grained access in an hypermedia-oriented fashion I’ve started to work on Tride, a mapping language that takes one or more CSV files as inputs and produces a set of (connected) JSON documents. In the 2 min demo video I … Continue reading
On the one hand you have structured data sources such as relational DB, NoSQL datastores or OODBs and the like that allow you to query and manipulate data in a structured way. This typically involves schemata (either upfront with RDB or sort of dynamically with NoSQL that defines the data layout and the types of … Continue reading
