We’ll guide you through comprehensive recipes on what’s new in
Elasticsearch 5.x, showing you how to create complex queries and
analytics, and perform index mapping, aggregation, and scripting.
Further on, you will explore the modules of Cluster and Node monitoring
and see ways to back up and restore a snapshot of an index.
You will understand how to install Kibana to monitor a cluster and
also to extend Kibana for plugins. Finally, you will also see how you
can integrate your Java, Scala, Python, and big data applications such
as Apache Spark and Pig with ElasticSearch, and add enhanced
functionalities with custom plugins.
By the end of this book, you will have an in-depth knowledge of the
implementation of the Elasticsearch architecture and will be able to
manage data efficiently and effectively with Elasticsearch.
Alberto Paro is an engineer, project manager, and software
developer. He currently works as freelance trainer/consultant on big
data technologies and NoSQL solutions. He loves to study emerging
solutions and applications mainly related to big data processing, NoSQL,
natural language processing, and neural networks. He began programming
in BASIC on a Sinclair Spectrum when he was eight years old, and to
date, has collected a lot of experience using different operating
systems, applications, and programming languages.
In 2000, he graduated in computer science engineering from
Politecnico di Milano with a thesis on designing multiuser and
multidevice web applications. He assisted professors at the university
for about a year. He then came in contact with The Net Planet Company
and loved their innovative ideas; he started working on knowledge
management solutions and advanced data mining products. In summer 2014,
his company was acquired by a big data technologies company, where he
worked until the end of 2015 mainly using Scala and Python on
state-of-the-art big data software (Spark, Akka, Cassandra, and YARN).
In 2013, he started freelancing as a consultant for big data, machine
learning, Elasticsearch and other NoSQL products. He has created or
helped to develop big data solutions for business intelligence,
financial, and banking companies all over the world. A lot of his time
is spent teaching how to efficiently use big data solutions (mainly
Apache Spark), NoSql datastores (Elasticsearch, HBase, and Accumulo) and
related technologies (Scala, Akka, and Playframework). He is often
called to present at big data or Scala events. He is an evangelist on
Scala and Scala.js (the transcompiler from Scala to JavaScript).
In his spare time, when he is not playing with his children, he likes
to work on open source projects. When he was in high school, he started
contributing to projects related to the GNOME environment (gtkmm). One
of his preferred programming languages is Python, and he wrote one of
the first NoSQL backends on Django for MongoDB (Django-MongoDBengine).
In 2010, he began using Elasticsearch to provide search capabilities to
some Django e-commerce sites and developed PyES (a Pythonic client for
Elasticsearch), as well as the initial part of the Elasticsearch MongoDB
river. He is the author of Elasticsearch Cookbook as well as a
technical reviewer of Elasticsearch Server-Second Edition, Learning
Scala Web Development, and the video course, Building a Search Server
with Elasticsearch, all of which are published by Packt Publishing.
