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Sunday, May 10, 2015

Mastering Elasticsearch - Second Edition by Rafał Kuć and Marek Rogoziński Packt Publishing Book Review

It is hard to underestimate the importance of the search nowadays. It probably even occurs without being noticed, but try to count how many times a day you tried to search for a product online, search through an online catalogue, an abbreviation or simply a weather forecast? Even a simple one page document or a webpage offers search capabilities (Ctrl-F). But have you ever wondered about how fast the search through Wiki is or how exact it is, even correcting your misspellings?

These and more elaborate searches are a product of very powerful software. Typically thanks the Lucene index, it is like standing on the shoulders of a giant, Solr and Elasticsearch are capable of scouting through a sea of documents and terms in milliseconds, boosting the most relevant results to the top helping human or robot deliver business insight, guide through darkness of overwhelming amounts of information to the decision or helping buy the correct product.

It becomes very obvious that these products encapsulate tons of advanced features and boast an array of capabilities, but sifting through the myriad of the features may at times become exhausting, and sure time consuming.

This is where the excellent technical literature as Mastering Elasticsearch 2nd Edition makes a lot of sense. Please note, this is the 2nd edition in a very short period of time (less than two years). What it means, there are two things. First, the book is very popular so the authors get a lot of support and demand for a sequel, second, the technology is evolving fast (~ 100 pages added). All these are good news and a confirmation that Elasticsearch is a mature yet promising technology that is here to stay. It will not be needless to state that this book is seen by the authors as a companion book to the Elasticsearch Server 2nd Edition that I did not read, but the authors stress out that it is a good idea to start from one.

The Mastering Elasticsearch book does feel like aiming at the search engineers, or those who already is involved in conceiving or using a product that will utilize the search capabilities of Elasticsearch. It is full of practical advice, insight and examples that are ranging from fine-tuning the searches to setting and properly configuring the cluster up. There is a chapter toward the end about how to crate plugins to any software project.

I liked the following parts in the book: boosting search scores, using Groovy as a scripting language, troubleshooting and speeding up performance.

Some knowledge of Java is assumed, but no special tooling or software is necessary to go through the book. But please be aware that you will type a lot of text, JSON specifically, so you may want an editor that has good support for JSON especially color highlighting e.g. the Eclipse JSON plugin. Groovy was used very lightly and all the examples were very eloquent.

On the missing thing part, I did not see any examples on how to execute geospatial searched event though it was mentioned that these are possible, and I was highly interested in it.

It does not reduce my score even a bit though, this is an example of a very hard work on the part of the authors and publisher, five our of five.

Monday, April 6, 2015

Getting Started with Julia by Ivo Balbaert, Packt Publishing Book Review

An awesome book on an awesome language conceived by brilliant MIT computer scientists!
The author clearly a technically savvy, mature professional who understands Julia very well.
Besides, the language itself beats everything I have ever seen to date (e.g. Python, C, and more).
It beats every language because it is simple, friendly and elegant, and it is not built to be a data manipulation language only, but a replacement to just any programming language. How you can do the 21st century programming using GPU, parallel processing, streams and more is both astonishing and easy. The language has the type system which is very flexible and the language can call other languages or its own code or libraries or be even embedded. Database connectivity is via ODBC though looks like only.
Julia is very worth starting learning.
I anticipate the release 0.4 as stated by the author in the book to be even better.
The book allows to set your development shop on any OS (even though using Linux implies) and smooth sailing through numerous topics and examples of high quality and code on the web for grabs. The book covers enough to start developing about any programs. Where you need to do some home work is probably in finding relevant to the task at hand libraries (that grow in number weekly).
5 out of 5, a winning combination of a superb language, good book, and author!

Sunday, February 22, 2015

R High Performance Programming by Aloysius Lim, William Tjhi, Packt Publishing Book Review

R High Performance Programming is probably a unique book in terms of the material covered, I just have not see yet to date a book that is dedicated to increasing the computational capacity of the R language.

And I need to state frankly, since R has left the academic circles a long time ago and now is being used more and more in applications involving the Big Data calibre of projects a developer or an R user needs to understand its limitations and perhaps even be able to shrug off some misconceptions that surface on and off about the R’s Big Data suitability.

This book will make you prepared to cope with those who encroach on R’s capability to process petabytes of data. Bedsides, since the authors have a very broad outlook on the technologies and succeeded to cover very difficult topics in simple terms this book actually is of an asset to any software developer, using any language on any platform

What do you need for this book: preferably a *NIX based 64 bit machine capable enough to run a Virtual Machine with an NVIDIA GPU. An Amazon EWS account. Eclipse R Add on (R Studio was cited as storing object state). A Windows user will be able to learn as much, but some of the libraries covered in the book (just a few) were not ported to Windows at the time of my reading.

Aloysius and William cover the code execution benchmarking techniques at the beginning very well and then make you embark on wonderful journey to exploring an array of CRAN packages, third party tools and frameworks, the book includes the use of Hadoop, PostgreSQL, MonetDB (vertical data store), Pivotal SciDB, and more so you will not be limited to a narrow subset of tools to use under your belt, it will be something like dirking from the firehose!

I read this book in one breath, it is was just that a fascinating journey. I now think I need to come back, and read several chapters of immense interest to me: code pre-compilation (just so easy to take advantage of), the FF, dplyr and BigMemory package (just take advantage of somebody giving you a hand). I will experiment with at least one database, perhaps MonetDB as being at fingertips reach.

If I had a small complaint that would be for the absence of the statistical visualizations code – I just would like to benchmark my own improvements.

All in all, it is a fantastic book, thank you Aloysius and William! A very timely release Packt!

My verdict, is it a superb reading!

Monday, February 16, 2015

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