A summary of 5 CS papers chosen from the 55 that Adrian Coyler has reviewed for his Morning Paper blog during Q2 2016. Topics include vectors, deep learning techniques, Gorilla system.
A summary of five CS papers chosen from the 66 that Adrian Coyler has reviewed for his Morning Paper blog during the first quarter of 2016. Topics include distributed transactions, transaction recovery, and Hyperloglog.
This eMag focuses on the graph database landscape and the real world use cases of graph databases. It includes articles and interviews covering topics like data modeling in graph databases and how companies use graph databases in their application. It also includes an article on full stack web development using a graph database.
Apache Hadoop is proving useful in deriving insights out of large amounts of data, and is seeing rapid improvements. Hadoop 2 now goes beyond Map-Reduce; it is more modular, pluggable and flexible and it fits a variety of use cases better. We explore this as well as some tools that can help utilize Hadoop better.
This eMag examines topics such as how Twitter re-architected its code-base to improve stability and performance, the approaches Netflix uses to be hyper-resilient, and how Java is replacing C++ for low latency coding. We also look at some lower level tricks such as feedback controls for auto-scaling, and using memory and execution profiling to identify performance bottlenecks in Java.
The InfoQ NoSQL eMag brings together a selection of popular NoSQL articles recently published on InfoQ.com. Get a complete overview of the current NoSQL movement, learn how NoSQL relates to the CAP Theorem, and get practical guidance on setting up and using a popular NoSQL database.
With Spring Data, the ever popular Spring Framework has cultivated a new patch of ground, bringing Big Data and NOSQL technology like Neo4j to enterprise developers. This guide introduces you to Spring Data Neo4j, using the fast, powerful and scalable graph database Neo4j to enjoy the benefits of having good relationships in your data.
Java Transaction Design Strategies shows how to design an effective transaction management strategy using the transaction models provided by Java-based frameworks such as EJB and Spring. Local, programmatic, declarative, and XA models are explained; the book concludes with a set of design patterns show how to effecitvely use these models.