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The shortcomings and drawbacks of batch-oriented data processing were widely recognized by the Big Data community quite a long time ago. It became clear that real-time query processing and in-stream processing is the immediate need in many practical applications. In recent years, this idea got a lot of traction and a whole bunch of solutions like Twitter’s Storm, Yahoo’s S4, Cloudera’s Impala, Apa
Retail is one of the most important business domains for data science and data mining applications because of its prolific data and numerous optimization problems such as optimal prices, discounts, recommendations, and stock levels that can be solved using data analysis methods. The rise of omni-channel retail that integrates marketing, customer relationship management, and inventory […]
Scalability is one of the main drivers of the NoSQL movement. As such, it encompasses distributed system coordination, failover, resource management and many other capabilities. It sounds like a big umbrella, and it is. Although it can hardly be said that NoSQL movement brought fundamentally new techniques into distributed data processing, it triggered an avalanche of practical studies and real-li
Intersection of sorted lists is a cornerstone operation in many applications including search engines and databases because indexes are often implemented using different types of sorted structures. At GridDynamics, we recently worked on a custom database for realtime web analytics where fast intersection of very large lists of IDs was a must for good performance. From a functional point of view, w
Statistical analysis and mining of huge multi-terabyte data sets is a common task nowadays, especially in the areas like web analytics and Internet advertising. Analysis of such large data sets often requires powerful distributed data stores like Hadoop and heavy data processing with techniques like MapReduce. This approach often leads to heavyweight high-latency analytical processes and poor appl
Highly Scalable BlogArticles on Big Data, NoSQL, and Highly Scalable Software Engineering ACID transactions are one of the most widely used software engineering techniques, a cornerstone of the relational databases, and an integral part of the enterprise middleware where transactions are often offered as the black-box primitives. Notwithstanding all these and many other cases, the old-fashion app
NoSQL databases are often compared by various non-functional criteria, such as scalability, performance, and consistency. This aspect of NoSQL is well-studied both in practice and theory because specific non-functional properties are often the main justification for NoSQL usage and fundamental results on distributed systems like the CAP theorem apply well to NoSQL systems. At the same time, NoSQL
Highly Scalable BlogArticles on Big Data, NoSQL, and Highly Scalable Software Engineering Some time ago our team had been requested to develop several Java components for structured information retrieval. After the initial research, we concluded that standard approaches like inverted indexes are not well applicable to our problem because of specific business requirements. As a result we faced a ne
In this article I digested a number of MapReduce patterns and algorithms to give a systematic view of the different techniques that can be found on the web or scientific articles. Several practical case studies are also provided. All descriptions and code snippets use the standard Hadoop’s MapReduce model with Mappers, Reduces, Combiners, Partitioners, and sorting. This framework is depicted in th
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