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MongoDB for PHP Developers
A two-part MongoDB tutorial for PHP developers: first part covering installation and the second giving a brief intro to MongoDB PHP API for queries and indexes. While not the tutorial that will get you up and running, it’s still a good resource for beginners.
Original title and link: MongoDB for PHP Developers (NoSQL database©myNoSQL)
Short Intro to Graph Databases, Manipulating and Traversing With Gremlin
A slide deck by Pierre De Wilde with a short theoretical intro to property graphs and graph databases and an extensive set of examples of manipulating and traversing graph data with Gremlin. Good reference material.
A walk in graph databases v1.0 by Pierre De Wilde
Original title and link: Short Intro to Graph Databases, Manipulating and Traversing With Gremlin (NoSQL database©myNoSQL)
NoSQL Books: Riak Handbook and the Little Redis Book
A couple of recent books that I’ll be adding to the list of NoSQL books:
Mathias Meyer’s Riak Handbook. You can get an idea of the book by checking Consistent Hashing Explained: The What and the Why, the free sample chapter, and the table of contents.
Karl Seguin’s The Little Redis Book. Karl is at the second free NoSQL book after the The Little MongoDB Book.
Original title and link: NoSQL Books: Riak Handbook and the Little Redis Book (NoSQL database©myNoSQL)
A very practical example of how Hive and Hadoop could deliver value when applied to clickstreams, the most common data for each web property:
Hadoop, Hive, and related technologies are formidable tools for unlocking value from data. […] Retention measurements are particularly significant because they paint a detailed picture about the overall stickiness of a product across the entire userbase.
The same clickstream data can be used to calculate visitors’ conversion with the Bayesian discriminant using Hadoop.
Original title and link: Measuring User Retention With Hadoop and Hive (NoSQL database©myNoSQL)
Steve Salevan’s 7 step guide to setting up, compiling, deploying, and running a basic MapReduce job.
When Google unveiled its MapReduce algorithm to the world in an academic paper in 2004, it shook the very foundations of data analysis. By establishing a basic pattern for writing data analysis code that can run in parallel against huge datasets, speedy analysis of data at massive scale finally became a reality, turning many orthodox notions of data analysis on their head.
Google published the paper. Yahoo open sourced this. And Amazon is offering (unlimited) resources.
Update: The Hacker News thread where the main question answered is what other corporations are using MapReduce (besides the Internet companies). The answer is unfortunately extremely short: too many to be able to enumerate them all.
Original title and link: How to Run a MapReduce Job Against Common Crawl Data Using Amazon Elastic MapReduce (NoSQL database©myNoSQL)
MarkLogic Querying for SQL People
Inspired by the MongoDB MapReduce translated to SQL and Neo4j Cypher Querying for SQL People, MarkLogic’s Jason Hunter and Eric Bloch put together a page mapping SQL terms and queries to MarkLogix terms and XQuery queries respectively.
Here is how SQL statements translate to MarkLogic XQuery expressions:
Original title and link: MarkLogic Querying for SQL People (NoSQL database©myNoSQL)
NoSQL Screencast: Android Couchbase Tutorial
A 12 minutes screencast introducing the basics of Couchbase Mobile for Android applications:
Original title and link: NoSQL Screencast: Android Couchbase Tutorial (NoSQL database©myNoSQL)
[…] we’ve built up a Doctor Who data model that shows how Neo4j can be used to address several different data and domain concerns. For example, part of the dataset includes timeline data, comprising seasons, stories and episodes; elsewhere we’ve social network-like data, with characters connected to one another through being companions, allies or enemies of the Doctor. It’s a messy and densely-connected dataset – much like the data you might find in a real-world enterprise. Some of it is of high quality, some of it is lacking in detail. And for every seeming invariant in the domain, there’s an awkward exception – again, much like the real world.
Ian Robinson’s post will walk you through the details of structuring and querying the data with Neo4j. The complete source code is available on GitHub.
Original title and link: Neo4j Tutorial: The Power of the Daleks (NoSQL database©myNoSQL)
