Welcome to the second edition of DZone's This Week in NoSQL.
New Releases This Week:
We’ve been developing an entirely new set of web tools for the last several months and we’re going to enable it by default for all users starting on Thursday, October 11th. The most obvious changes are user interface related. We set Brandon Mathis loose on our crufty HTML and he’s delivered an entirely new, responsive design with significant speed improvements and a much classier wardrobe.
This Week's Top 5 NoSQL Links:1. Algorithm of the Week: Dijkstra Shortest Path in a Graph
In this post we must answer the question: is BFS the best algorithm that finds the shortest path between any two nodes of the graph?2. Writing Geospatial Queries for MongoDB in Java
In this article, I will help you quickly write Geospatial queries described in the following presentation using Java. I assume you have MongoDB server up and running on your machine.3. MongoDB in Production [video]
Chris Harris and Alvin Richards present "MongoDB in Production." Chris Harris is European Solution Architect at 10gen and Alvin Richards is the Senior Director, Enterprise Engineering at 10gen.4. Implementing Entity Services using NoSQL – Part 1: Outline
I want to build the entity service by using as little Java code as possible but at the same time preserve the contract-first approach.5. Redis pub/sub Using Spring
Continuing to discover the powerful set of Redis features, the one worth mentioning about is out of the box support of pub/sub messaging.
New NoSQL Books This Week:
By Tom White
"Ready to unlock the power of your data? With this comprehensive guide, you’ll learn how to build and maintain reliable, scalable, distributed systems with Apache Hadoop. This book is ideal for programmers looking to analyze datasets of any size, and for administrators who want to set up and run Hadoop clusters.
You’ll find illuminating case studies that demonstrate how Hadoop is used to solve specific problems. This third edition covers recent changes to Hadoop, including material on the new MapReduce API, as well as MapReduce 2 and its more flexible execution model (YARN).
- Store large datasets with the Hadoop Distributed File System (HDFS)
- Run distributed computations with MapReduce
- Use Hadoop’s data and I/O building blocks for compression, data integrity, serialization (including Avro), and persistence
- Discover common pitfalls and advanced features for writing real-world MapReduce programs
- Design, build, and administer a dedicated Hadoop cluster—or run Hadoop in the cloud
- Load data from relational databases into HDFS, using Sqoop
- Perform large-scale data processing with the Pig query language
- Analyze datasets with Hive, Hadoop’s data warehousing system
- Take advantage of HBase for structured and semi-structured data, and ZooKeeper for building distributed systems"
Thursday October 25th - 10 PM PDT
In this webinar Gil discusses how Neo4j was implemented to power Postcards, the new interest graph enabled product from popular social publishing platform Squidoo.In this webinar, we will cover:
- Why Squidoo chose Neo4j over MySQL and Cassandra, its existing database technologies
- What the first week of development with a graph database looked like
- Simple tips to get up to speed on graph design more quickly
- How Neo4j can be used to enable the Semantic Web
- In-depth look at Squidoo's Postcards graph design
Thanks for reading! Join us next week--same NoSQL time, same NoSQL place!