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Elasticsearch Server - Third Edition

You're reading from   Elasticsearch Server - Third Edition Leverage Elasticsearch to create a robust, fast, and flexible search solution with ease

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Product type Paperback
Published in Feb 2016
Publisher
ISBN-13 9781785888816
Length 556 pages
Edition 3rd Edition
Languages
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Authors (2):
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Rafal Kuc Rafal Kuc
Author Profile Icon Rafal Kuc
Rafal Kuc
Marek Rogozinski Marek Rogozinski
Author Profile Icon Marek Rogozinski
Marek Rogozinski
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Table of Contents (13) Chapters Close

Preface 1. Getting Started with Elasticsearch Cluster FREE CHAPTER 2. Indexing Your Data 3. Searching Your Data 4. Extending Your Querying Knowledge 5. Extending Your Index Structure 6. Make Your Search Better 7. Aggregations for Data Analysis 8. Beyond Full-text Searching 9. Elasticsearch Cluster in Detail 10. Administrating Your Cluster 11. Scaling by Example Index

Mappings configuration

If you are used to SQL databases, you may know that before you can start inserting the data in the database, you need to create a schema, which will describe what your data looks like. Although Elasticsearch is a schema-less (we rather call it data driven schema) search engine and can figure out the data structure on the fly, we think that controlling the structure and thus defining it ourselves is a better way. The field type determining mechanism is not going to guess the future. For example, if you first send an integer value, such as 60, and you send a float value such as 70.23 for the same field, an error can happen or Elasticsearch will just cut off the decimal part of the float value (which is actually what happens). This is because Elasticsearch will first set the field type to integer and will try to index the float value to the integer field which will cause cutting of the decimal point in the floating point number. In the next few pages you'll see...

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