Elasticsearch for Hadoop
Shukla, Vishal
Vendu par Biblios, Frankfurt am main, HESSE, Allemagne
Vendeur AbeBooks depuis 10 septembre 2024
Neuf(s) - Couverture souple
Etat : Neuf
Quantité disponible : 4 disponible(s)
Ajouter au panierVendu par Biblios, Frankfurt am main, HESSE, Allemagne
Vendeur AbeBooks depuis 10 septembre 2024
Etat : Neuf
Quantité disponible : 4 disponible(s)
Ajouter au panierPRINT ON DEMAND pp. 222.
N° de réf. du vendeur 18374807996
Integrate Elasticsearch into Hadoop to effectively visualize and analyze your data
This book is targeted at Java developers with basic knowledge on Hadoop. No prior Elasticsearch experience is expected.
The Hadoop ecosystem is a de-facto standard for processing terra-bytes and peta-bytes of data. Lucene-enabled Elasticsearch is becoming an industry standard for its full-text search and aggregation capabilities. Elasticsearch-Hadoop serves as a perfect tool to bridge the worlds of Elasticsearch and Hadoop ecosystem to get best out of both the worlds. Powered with Kibana, this stack makes it a cakewalk to get surprising insights out of your massive amount of Hadoop ecosystem in a flash.
In this book, you'll learn to use Elasticsearch, Kibana and Elasticsearch-Hadoop effectively to analyze and understand your HDFS and streaming data.
You begin with an in-depth understanding of the Hadoop, Elasticsearch, Marvel, and Kibana setup. Right after this, you will learn to successfully import Hadoop data into Elasticsearch by writing MapReduce job in a real-world example. This is then followed by a comprehensive look at Elasticsearch essentials, such as full-text search analysis, queries, filters and aggregations; after which you gain an understanding of creating various visualizations and interactive dashboard using Kibana. Classifying your real-world streaming data and identifying trends in it using Storm and Elasticsearch are some of the other topics that we'll cover. You will also gain an insight about key concepts of Elasticsearch and Elasticsearch-hadoop in distributed mode, advanced configurations along with some common configuration presets you may need for your production deployments. You will have “Go production checklist” and high-level view for cluster administration for post-production. Towards the end, you will learn to integrate Elasticsearch with other Hadoop eco-system tools, such as Pig, Hive and Spark.
A concise yet comprehensive approach has been adopted with real-time examples to help you grasp the concepts easily.
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