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실시간 분석의 모든 것: 스트리밍 데이터 분석 및 시각화 시스템 구축 가이드
실시간 분석 솔루션을 구축하기 위한 지침서!
빠른 비즈니스 의사결정을 위해 실시간 분석에 대한 관심이 고조되고 있다. 이 책은 스트리밍 데이터의 분석에서 시각화까지 전 단계를 망라하는 가성비 높은 솔루션을 제시한다. 1부는 아파치 주키퍼, 카프카, 플룸, 스톰, 얀, 삼자, 레디스, 몽고DB, 카산드라 등으로 실시간 분석 서비스를 구성하고 데이터를 처리 및 저장하는 방법을 다룬다. 2부는 SVG와 D3.js를 활용하여 데이터를 시각화하고 모니터링하고 실시간에 맞게 최적화하는 방법을 살펴본다. 실무 관점에서 다양한 기술의 활용 및 구성 로드맵을 제시하여, 나무가 아니라 숲을 볼 수 있게 해주는 책이다.
빠른 비즈니스 의사결정을 위해 실시간 분석에 대한 관심이 고조되고 있다. 이 책은 스트리밍 데이터의 분석에서 시각화까지 전 단계를 망라하는 가성비 높은 솔루션을 제시한다. 1부는 아파치 주키퍼, 카프카, 플룸, 스톰, 얀, 삼자, 레디스, 몽고DB, 카산드라 등으로 실시간 분석 서비스를 구성하고 데이터를 처리 및 저장하는 방법을 다룬다. 2부는 SVG와 D3.js를 활용하여 데이터를 시각화하고 모니터링하고 실시간에 맞게 최적화하는 방법을 살펴본다. 실무 관점에서 다양한 기술의 활용 및 구성 로드맵을 제시하여, 나무가 아니라 숲을 볼 수 있게 해주는 책이다.
480 pages, Paperback
First published June 19, 2014
13 people are currently reading
105 people want to read
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Displaying 1 - 5 of 5 reviews
January 2, 2015
Very hard to rate.
On one hand, it may be the only book that truly touches the heart of the problems in RTA. What is more it decomposes it into "moving parts" to illustrate what the issues are really about. But on the other hand, the execution is not perfect, sometimes it's even irritating:
* author picks the particular technologies well, but he pretty much skips the overview of each of them - two / three paragraphs of intro & his jumps straight into code -> what's even more odd, this code usually makes sense, but it focuses on some particular elements of tech -> what makes it hard to crunch for people who haven't experienced this tech at all. I did (majority of them) but it was still very irritating for me. To be honest I believe that this book should be more about the concept & modeling the solutions (while analyzing the challenges), not about particular tech.
* the other big drawback affects last few chapters -> the mathematical model behind HLL, Bloom Filters, regression methods, etc. - the idea to put this knowledge in the book is absolutely awesome, the choice of topics is great as well, there are some nice examples, but the actual execution fails -> there are pretty much no graphs, images, illustrations for this part (at least in Kindle version). FAIL. It sometimes make it really hard to grasp some ideas quickly - it's very irritating.
Otherwise than that, it's a very solid book dedicated to the very interesting topic. What is more, there aren't many alternatives available -> when I've starting battling this topic about 1.5-2 yrs ago, I had to gather knowledge from multiple resources, which was very time-consuming.
On one hand, it may be the only book that truly touches the heart of the problems in RTA. What is more it decomposes it into "moving parts" to illustrate what the issues are really about. But on the other hand, the execution is not perfect, sometimes it's even irritating:
* author picks the particular technologies well, but he pretty much skips the overview of each of them - two / three paragraphs of intro & his jumps straight into code -> what's even more odd, this code usually makes sense, but it focuses on some particular elements of tech -> what makes it hard to crunch for people who haven't experienced this tech at all. I did (majority of them) but it was still very irritating for me. To be honest I believe that this book should be more about the concept & modeling the solutions (while analyzing the challenges), not about particular tech.
* the other big drawback affects last few chapters -> the mathematical model behind HLL, Bloom Filters, regression methods, etc. - the idea to put this knowledge in the book is absolutely awesome, the choice of topics is great as well, there are some nice examples, but the actual execution fails -> there are pretty much no graphs, images, illustrations for this part (at least in Kindle version). FAIL. It sometimes make it really hard to grasp some ideas quickly - it's very irritating.
Otherwise than that, it's a very solid book dedicated to the very interesting topic. What is more, there aren't many alternatives available -> when I've starting battling this topic about 1.5-2 yrs ago, I had to gather knowledge from multiple resources, which was very time-consuming.
November 13, 2016
It's mix&mash or technologies, algorithms and overview of the field.
- begins with description of the stream processing as a new approach, providing methodology and architectural backbone
- then lays down exact technologies to be used
- at the end, digs into algorithmic challenges and approaches. And even provide insights into the math behind it.
To some degree, this books gives awesome and very broad grasp of stream-processing. Most books are either technology oriented or too general or narrowed to alrorithms and data structures.
This book tries to describe the approach from different scales. Which is good.
But execution is not impressive. And you have to google a lot to get understanding what's going on.
Code samples are very cryptic and inconsistent. Math formulas deserve better formatting.
I can't say who should read this book. May be, those who are not new to the field, but still in the beginning of understanding.
- begins with description of the stream processing as a new approach, providing methodology and architectural backbone
- then lays down exact technologies to be used
- at the end, digs into algorithmic challenges and approaches. And even provide insights into the math behind it.
To some degree, this books gives awesome and very broad grasp of stream-processing. Most books are either technology oriented or too general or narrowed to alrorithms and data structures.
This book tries to describe the approach from different scales. Which is good.
But execution is not impressive. And you have to google a lot to get understanding what's going on.
Code samples are very cryptic and inconsistent. Math formulas deserve better formatting.
I can't say who should read this book. May be, those who are not new to the field, but still in the beginning of understanding.
January 3, 2015
A timely book on the different techniques that can be applied while collecting, processing, storing and modeling real-time data from sources like operational monitoring and social networks. It touches upon all the aspects in real-time data anlaytics from data collection to creating effective dashboards to real-time A/B testing using predictions based on linear/non-linear models like neural networks.
The author doesn't assume the readers to have prior knowledge on cutting edge real-time data management technologies, and that makes the book really good for beginners. A moderately experienced data engineer might find few things basic, but again, those things could be really useful for beginners.
The author doesn't assume the readers to have prior knowledge on cutting edge real-time data management technologies, and that makes the book really good for beginners. A moderately experienced data engineer might find few things basic, but again, those things could be really useful for beginners.
April 24, 2015
Good introduction into analysis of streaming data, starting with acquiring it, perform analysis & storing data. Besides overview of concrete technologies (Kafka, Flume, Spark, Samza, databases, D3.js, etc.) it also includes big part about algorithms that could be applied to streaming data, like count-min, bloom filter, etc., including implementation examples & how to apply them for your tasks.
December 2, 2015
Very basic and too vague for my taste. I guess it's ok if you need an introduction into the subject...
Displaying 1 - 5 of 5 reviews