Elasticsearch Essentials by Bharvi Dixit

Elasticsearch Essentials



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Elasticsearch Essentials Bharvi Dixit ebook
Publisher: Packt Publishing, Limited
Page: 165
ISBN: 9781784391010
Format: pdf


Additional functionality for forums running XenForo Enhanced Search (ElasticSearch). Backups and Security Data backups and data security are the most important aspects of any organization. Summary In this chapter, you learned how to use Python and Java clients forElasticsearch and perform CRUD operations using it. Until now we have worked with simple geo-location and rectangle searches. CRUD operations using Java In this section, we will go through the Elasticsearch Java client to perform the CRUD operations. For support files and downloads related to your book, please visit www.PacktPub. Geo-shapes are completely different from geo-points. Summary In this chapter, you learned how to create data backups of anElasticsearch cluster and restore them back into the same or another cluster. Elasticsearch mapping We have seen in the previous chapter how an index can have one or more types and each type has its own mapping. Let us know what you think about this book—what you liked or disliked. Introducing Zen-Discovery Elasticsearch is highly scalable and distributed in nature. Creating a cluster Since you have learned a major part of cluster configuration, let's begin to create a full-blown production-ready cluster. Putting Elasticsearch into Action We have covered a lot of ground onElasticsearch architecture, indexes, analyzers, and mappings. Find helpful customer reviews and review ratings for Elasticsearch Essentials at Amazon.com. Document analysis When we index documents into Elasticsearch, it goes through an analysis phase that is necessary in order to create inverted indexes. Creating a search database It's always good to have some practical examples with real data sets, and what could be better than real-time social media data? Search requests using Python All the queries that we have discussed can be performed with the Elasticsearch Python client using the search function. Working with nested objects Nested objects look similar to plain objects but they differ in mapping and the way they are stored internally in Elasticsearch. Data pagination We have seen that for any query, Elasticsearch by default returns only the top 10 documents after scoring and sorting them.





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