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You're reading from  Lucene 4 Cookbook

Product typeBook
Published inJun 2015
Reading LevelExpert
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ISBN-139781782162285
Edition1st Edition
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Authors (2):
Edwood Ng
Edwood Ng
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Edwood Ng

Edwood Ng is a technologist with over a decade of experience in building scalable solutions from proprietary implementations to client-facing web-based applications. Currently, he's the director of DevOps at Wellframe, leading infrastructure and DevOps operations. His background in search engine began at Endeca Technologies in 2004, where he was a technical consultant helping numerous clients to architect and implement faceted search solutions. After Endeca, he drew on his knowledge and began designing and building Lucene-based solutions. His first Lucene implementation that went to production was the search engine behind http://UpDown.com. From there on, he continued to create search applications using Lucene extensively to deliver robust and scalable systems for his clients. Edwood is a supporter of an open source software. He has also contributed to the plugin sfI18NGettextPluralPlugin to the Symphony project.
Read more about Edwood Ng

Vineeth Mohan
Vineeth Mohan
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Vineeth Mohan

Vineeth Mohan is an architect and developer. He currently works as the CTO at Factweavers Technologies and is also an Elasticsearch-certified trainer. He loves to spend time studying emerging technologies and applications related to data analytics, data visualizations, machine learning, natural language processing, and developments in search analytics. He began coding during his high school days, which later ignited his interest in computer science, and he pursued engineering at Model Engineering College, Cochin. He was recruited by the search giant Yahoo! during his college days. After 2 years of work at Yahoo! on various big data projects, he joined a start-up that dealt with search and analytics. Finally, he started his own big data consulting company, Factweavers. Under his leadership and technical expertise, Factweavers is one of the early adopters of Elasticsearch and has been engaged with projects related to end-to-end big data solutions and analytics for the last few years. There, he got the opportunity to learn various big-data-based technologies, such as Hadoop, and high-performance data ingress systems and storage. Later, he moved to a start-up in his hometown, where he chose Elasticsearch as the primary search and analytic engine for the project assigned to him. Later in 2014, he founded Factweavers Technologies along with Jalaluddeen; it is consultancy that aims at providing Elasticsearch-based solutions. He is also an Elasticsearch-certified corporate trainer who conducts trainings in India. Till date, he has worked on numerous projects that are mostly based on Elasticsearch and has trained numerous multinationals on Elasticsearch.
Read more about Vineeth Mohan

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Creating fields


We have learned that indexing information in Lucene requires the creation of document objects. A Lucene document contains one or more field where each one represents a single data point about the document. A field can be a title, description, article ID, and so on. In this section, we will show you the basic structure and how to create a field.

A Lucene field has three attributes:

  • Name

  • Type

  • Value

Name and value are self-explanatory. You can think of a name as a column name in a table, and value as a value in one of the records where record itself is a document. Type determines how the field is treated. You can set FieldType to control whether to store value, to index it or even tokenize text. A Lucene field can hold the following:

  • String

  • Reader or preanalyzed TokenStream

  • Binary(byte[])

  • Numeric value

How to do it...

This code snippet shows you how to create a simple TextField:

  Document doc = new Document();
  String text = "Lucene is an Information Retrieval library written in Java.";
  doc.add(new TextField("fieldname", text, Field.Store.YES));

How It Works

In this scenario, we create a document object, initialize a text, and add a field by creating a TextField object. We also configure the field to store a value so it can be retrieved during a search.

A Lucene document is a collection of field objects. A field is the name of the value pairs, which you may add to the document. A field is created by simply instantiating one of the Field classes. Field can be inserted into a document via the add method.

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Lucene 4 Cookbook
Published in: Jun 2015Publisher: ISBN-13: 9781782162285
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Authors (2)

author image
Edwood Ng

Edwood Ng is a technologist with over a decade of experience in building scalable solutions from proprietary implementations to client-facing web-based applications. Currently, he's the director of DevOps at Wellframe, leading infrastructure and DevOps operations. His background in search engine began at Endeca Technologies in 2004, where he was a technical consultant helping numerous clients to architect and implement faceted search solutions. After Endeca, he drew on his knowledge and began designing and building Lucene-based solutions. His first Lucene implementation that went to production was the search engine behind http://UpDown.com. From there on, he continued to create search applications using Lucene extensively to deliver robust and scalable systems for his clients. Edwood is a supporter of an open source software. He has also contributed to the plugin sfI18NGettextPluralPlugin to the Symphony project.
Read more about Edwood Ng

author image
Vineeth Mohan

Vineeth Mohan is an architect and developer. He currently works as the CTO at Factweavers Technologies and is also an Elasticsearch-certified trainer. He loves to spend time studying emerging technologies and applications related to data analytics, data visualizations, machine learning, natural language processing, and developments in search analytics. He began coding during his high school days, which later ignited his interest in computer science, and he pursued engineering at Model Engineering College, Cochin. He was recruited by the search giant Yahoo! during his college days. After 2 years of work at Yahoo! on various big data projects, he joined a start-up that dealt with search and analytics. Finally, he started his own big data consulting company, Factweavers. Under his leadership and technical expertise, Factweavers is one of the early adopters of Elasticsearch and has been engaged with projects related to end-to-end big data solutions and analytics for the last few years. There, he got the opportunity to learn various big-data-based technologies, such as Hadoop, and high-performance data ingress systems and storage. Later, he moved to a start-up in his hometown, where he chose Elasticsearch as the primary search and analytic engine for the project assigned to him. Later in 2014, he founded Factweavers Technologies along with Jalaluddeen; it is consultancy that aims at providing Elasticsearch-based solutions. He is also an Elasticsearch-certified corporate trainer who conducts trainings in India. Till date, he has worked on numerous projects that are mostly based on Elasticsearch and has trained numerous multinationals on Elasticsearch.
Read more about Vineeth Mohan