According to kdnuggets the Big Data related skills led the list of top paying technical skills (six-figure salaries) in 2013.
The study focus on technology professionals in the U.S. who enjoyed raises over the last year(2013).
Average U.S. tech salaries increased nearly three percent to $87,811 in 2013, up from $85,619 the previous year.Technology professionals understand they can easily find ways to grow their career in 2014, with two-thirds of respondents (65%) confident in finding a new, better position. That overwhelming confidence matched with declining salary satisfaction (54%, down from 57%) will keep tech-powered companies on edge about their retention strategies.
Companies are willing to pay hefty amounts to professionals with Big Data skills.
According to a report released on Jan 29, 2014 an average salary for a professional having knowledge and experience in programming language R was $115,531 in year 2013.
Other Big Data oriented skills such as NoSQL, MapReduce, Cassandra, Pig, Hadoop, MongoDB are among top 10 paying skills.
Dex is a MongoDB performance tuning tool that compares queries to the available indexes in the queried collection(s) and generates index suggestions based on simple heuristics. Currently you must provide a connection URI for your database.
Dex uses the URI you provide as a helpful way to determine when an index is recommended. Dex does not take existing indexes into account when actually constructing its ideal recommendation.
Currently, Dex only recommends complete indexes, not partial indexes. Dex ignores partial indexes that may be used by the query in favor of a better index, if one is not found. Dex recommends partially-ordered indexes according to a rule of thumb:
Your index field order should first answer:
Equivalent value checks
Range value checks ($in, $nin, $lt/gt, $lte/gte, etc.)
Note that your data cardinality may warrant a different order than the suggested indexes.
Choosing a shard key can be difficult, and the factors involved largely depend on your use case.
In fact, there is no such thing as a perfect shard key; there are design tradeoffs inherent in every decision. This presentation goes through those tradeoffs, as well as the different types of shard keys available in MongoDB, such as hashed and compound shard keys
The Mongo-Hadoop Adapter 1.1 have been released, it makes easy to use Mongo databases, or mongoDB backup files in .bson format, as the input source or output destination for Hadoop Map/Reduce jobs. By inspecting the data and computing input splits, Hadoop can process the data in parallel so that very large datasets can be processed quickly.
The Mongo-Hadoop adapter also includes support for Pig and Hive, which allow very sophisticated MapReduce workflows to be executed just by writing very simple scripts.
Pig is a high-level scripting language for data analysis and building map/reduce workflows
Hive is a SQL-like language for ad-hoc queries and analysis of data sets on Hadoop-compatible file systems.
Hadoop streaming is also supported, so map/reduce functions can be written in any language besides Java. Right now the Mongo-Hadoop adapter supports streaming in Ruby, Node.js and Python.
How it Works
How the Hadoop Adapter works
The adapter examines the MongoDB Collection and calculates a set of splits from the data
Each of the splits gets assigned to a node in Hadoop cluster
In parallel, Hadoop nodes pull data for their splits from MongoDB (or BSON) and process them locally
Hadoop merges results and streams output back to MongoDB or BSON
Perhaps you’ve heard about the next generation of databases roughly classified as NoSQL databases? These databases are generally much better than RDBMS at scaling, performance, and ease-of-development (e.g. in NoSQL the object-relational impedance mismatch usually disappears). Unfortunately, many talks on NoSQL are very academic and general. Not this one. This session will introduce the ideas around the so-called NoSQL movement, and we’ll learn how to leverage MongoDB (a popular open source NoSQL db) to build .NET applications using LINQ as the data access language. We’ll build out a .NET application using LINQ and MongoDB in a series of interactive demos using Visual Studio 2012 and C#.