Full Metal Hadoop as a Service with Altiscale

Full Metal Hadoop as a Service with Altiscale
Hadoop, known to be powerful and challenging to manage, is increasingly becoming available as-a-Service in numerous varieties. Initially do-it-yourself distributions like Cloudera, MapR, and Hortonworks made up a great part of the market. In recent years, following the success of Amazon Web Services ElasticMapReduce (EMR), Hadoop/data services like Qubole are becoming popular. Last year, quietly, another entrant in the field ... read more →

Lambda Architecture: Achieving Velocity and Volume with Big Data 4

Lambda Architecture: Achieving Velocity and Volume with Big Data
Big data architecture paradigms are commonly separated into two (supposedly) diametrical models, the more traditional batch and the (near) real-time processing. The most popular technologies representing the two are Hadoop with MapReduce and Storm. However, a hybrid solution, the Lambda Architecture, challenges the idea that these approaches have to exclude each other. The Lambda Architecture combines ... read more →

GraphChi: How a Mac Mini outperformed a 1,636 node Hadoop cluster

GraphChi: How a Mac Mini outperformed a 1,636 node Hadoop cluster
Last year GraphChi, a spin-off of GraphLab, a distributed graph-based high performance computation framework, did something remarkable. GraphChi outperformed a 1,636 node Hadoop cluster processing a Twitter graph (dataset from 2010) with 1.5 billion edges – using a single Mac Mini. The task was triangle counting and the Hadoop cluster required over 7 hours while ... read more →

ORC: An Intelligent Big Data file format for Hadoop and Hive 11

ORC: An Intelligent Big Data file format for Hadoop and Hive
RCFile (Record Columnar File), the previous Hadoop Big Data storage format on Hive, is being challenged by the smart ORC (Optimized Row Columnar) format. My first post on the topic, Getting Started with Big Data with Text and Apache Hive, presented a common scenario to illustrate why Hive file formats are significant to its performance and ... read more →

Faster Big Data on Hadoop with Hive and RCFile 5

Faster Big Data on Hadoop with Hive and RCFile
SQL on Hadoop with Hive makes Big Data accessible. Yet performance can lack. RCFile (Record Columnar File) are great optimisation for Big Data with Hive. The previous two posts in this four parts series explained the reasons why to use text on the periphery of an ETL process and optimisations for text. The inside of a Hive ... read more →

Getting Started with Big Data with Text and Apache Hive 3

Getting Started with Big Data with Text and Apache Hive
Big Data more often than expected is stored and exchanged as text. Apache Hadoop’s Hive SQL interface helps to reduce costs and to get results fast. Often, things have to get done fast rather than perfectly. However, with big data even a small decision like a file format could have a great impact. What are ... read more →

32x Faster Hadoop and MapReduce With Indexing 8

32x Faster Hadoop and MapReduce With Indexing
Hadoop and map reduce’s simplicity, and especially lack of indices, significantly limits its performance. I described how map reduce 2.0 and alternatives bypassing map reduce will change Hadoop’s application and speed it up in the next year or two. Another approach is the introduction of indices to data stored on Hadoop Distributed File System (HDFS). At its inception, ... read more →

Online Education Revolution

Online Education Revolution
For hundreds of years, brick-and-mortar universities were at the unchallenged pinnacle of education. In the last decades, remote and online education appeared with Massive Open Online Course (MOOC) being the latest incarnation. At first it was little more than traditional education channelled through alternative media, with limited success and appeal. This is changing fast and ... read more →

Hadoop 2.0: Beyond MapReduce with YARN, Drill, Tez

Hadoop 2.0: Beyond MapReduce with YARN, Drill, Tez
Hadoop 1.0 is increasingly challenged as slow and limited in its application, now that the hype is dying down. Marketing departments, riding the Big Data wave, wildly exaggerated Hadoop’s ability. Hadoop 2.0, surprisingly, is about to prove them somewhat right with two major developments. read more →

4 Free DIY Twitter Visualisations: The Shahbag Protest

4 Free DIY Twitter Visualisations: The Shahbag Protest
Earlier this year a mass movement occurred in Bangladesh, which received little global news coverage. It was an immensely important event to Bangladeshi’s at home and abroad. This prompted me to try and illustrate the event with Twitter data myself, merely utilizing some free web services and a few hours time. Amazingly the results are ... read more →