Map-Reduce — MongoDB Manual 2.6.4 Map-reduce is a data processing paradigm for condensing large volumes of data into useful aggregated results. For map-reduce operations, MongoDB provides the mapReduce database command. Consider the following map-reduce operation: In this map-reduce operation, MongoDB applies the map phase to each input document (i.e. the documents in the collection that match the query condition). MapReduce Overview MapReduce is a framework for processing parallelizable problems across huge datasets using a large number of computers (nodes), collectively referred to as a cluster (if all nodes are on the same local network and use similar hardware) or a grid (if the nodes are shared across geographically and administratively distributed systems, and use more heterogenous hardware). Processing can occur on data stored either in a filesystem (unstructured) or in a database (structured). MapReduce can take advantage of locality of data, processing it on or near the storage assets in order to reduce the distance over which it must be transmitted.
Apache Hadoop 2.5.1 - MapReduce Tutorial This section provides a reasonable amount of detail on every user-facing aspect of the MapReduce framework. This should help users implement, configure and tune their jobs in a fine-grained manner. However, please note that the javadoc for each class/interface remains the most comprehensive documentation available; this is only meant to be a tutorial. Let us first take the Mapper and Reducer interfaces. Applications typically implement them to provide the map and reduce methods.
MapReduce Tutorial This section provides a reasonable amount of detail on every user-facing aspect of the MapReduce framework. This should help users implement, configure and tune their jobs in a fine-grained manner. However, please note that the javadoc for each class/interface remains the most comprehensive documentation available; this is only meant to be a tutorial. Let us first take the Mapper and Reducer interfaces. Applications typically implement them to provide the map and reduce methods. We will then discuss other core interfaces including JobConf, JobClient, Partitioner, OutputCollector, Reporter, InputFormat, OutputFormat, OutputCommitter and others. When NoSQL Databases Are — Yes — Good For You And Your Company The proliferation of non-relational databases in the tech sector these days could lead you to think that these data management tools (also known as NoSQL databases) are eventually going to make traditional relational databases extinct. Not so. Each of these database types is best suited for very different types of workloads, and that's going to prevent either one from tromping the other into the dust. Which means that IT and other managers are going to have to figure out which approach is best suited for the task at hand. In this two-part series, I'll examine the capabilities of both NoSQL and relational databases to help you make the right decisions for your organization. "NoSQL"?
MongoDB MongoDB (from "humongous") is a cross-platform document-oriented database. Classified as a NoSQL database, MongoDB eschews the traditional table-based relational database structure in favor of JSON-like documents with dynamic schemas (MongoDB calls the format BSON), making the integration of data in certain types of applications easier and faster. Released under a combination of the GNU Affero General Public License and the Apache License, MongoDB is free and open-source software. First developed by the software company 10gen (now MongoDB Inc.) in October 2007 as a component of a planned platform as a service product, the company shifted to an open source development model in 2009, with 10gen offering commercial support and other services. Since then, MongoDB has been adopted as backend software by a number of major websites and services, including Brave Collective, Craigslist, eBay, Foursquare, SourceForge, Viacom, and the New York Times, among others.
Nonrelational Databases in a Big Data Environment Nonrelational databases do not rely on the table/key model endemic to RDBMSs (relational database management systems). In short, specialty data in the big data world requires specialty persistence and data manipulation techniques. Although these new styles of databases offer some answers to your big data challenges, they are not an express ticket to the finish line. Map Reduce - A really simple introduction « Kaushik Sathupadi Ever since google published its research paper on map reduce, you have been hearing about it. Here and there. If you have uptil now considered map-reduce a mysterious buzzword, and ignored it, Know that its not.
10 things you should know about NoSQL databases The relational database model has prevailed for decades, but a new type of database -- known as NoSQL -- is gaining attention in the enterprise. Here's an overview of its pros and cons. For a quarter of a century, the relational database (RDBMS) has been the dominant model for database management. But, today, non-relational, "cloud," or "NoSQL" databases are gaining mindshare as an alternative model for database management. In this article, we'll look at the 10 key aspects of these non-relational NoSQL databases: the top five advantages and the top five challenges.
Get Involved - MongoDB Getting involved in the MongoDB community is a great way to build relationships with other talented engineers, increase awareness for the interesting work that you are doing, sharpen your skills, or give back. Here are some of the ways that you can contribute to the MongoDB ecosystem. Discuss MongoDB through Community Forums Discuss, learn about, and get help with MongoDB through community-supported forums. We also offer office hours and paid support options.
NoSQL A relatively new concept in the world of database systems is the NoSQL DBMS. Just what is NoSQL? Well, I bet you could have guess that it doesn’t use SQL, right? Well, not exactly, at least not any more. The movement (and its name) is gaining popularity, but there isn’t exactly much rigor in terms of defining exactly what a NoSQL database system is, or what it must be able to do. At a high level, NoSQL implies non-relational, distributed, flexible, and scalable. Oracle NoSQL Database Technical Overview The Oracle NoSQL Database is a distributed key-value database. It is designed to provide highly reliable, scalable and available data storage across a configurable set of systems that function as storage nodes. Data is stored as key-value pairs, which are written to particular storage node(s), based on the hashed value of the primary key. Storage nodes are replicated to ensure high availability, rapid failover in the event of a node failure and optimal load balancing of queries. Customer applications are written using an easy-to-use Java/C API to read and write data.
Non-relational DBMSes Hierarchical DBMSes IMS - IBM’s hierarchical mainframe DBMS Model 204 - CCA’s hierarchical DBMS Database management systems have been around for a long time... a lot longer than the relational model and SQL. Of course, SQL systems (which are based on relational concepts), are the primary DBMSes implemented in large corporations today.
NoSQL "Structured storage" redirects here. For the Microsoft technology also known as structured storage, see COM Structured Storage. A NoSQL (often interpreted as Not Only SQL) database provides a mechanism for storage and retrieval of data that is modeled in means other than the tabular relations used in relational databases. Motivations for this approach include simplicity of design, horizontal scaling and finer control over availability. The data structure (e.g. key-value, graph, or document) differs from the RDBMS, and therefore some operations are faster in NoSQL and some in RDBMS. There are differences though, and the particular suitability of a given NoSQL DB depends on the problem it must solve (e.g. does the solution use graph algorithms?).