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Elasticsearch Server Second Edition by Marek Rogoziński, Rafał Kuć

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Summary

In this chapter, we learned more things about Elasticsearch data analysis capabilities. We used aggregations and faceting to bring meaning to the data we indexed. We also introduced the spellchecking and autocomplete functionalities to our application by using the Elasticsearch suggesters. We created the alerting functionality by using a percolator, and we indexed binary files by using the attachment functionality. We indexed and searched geospatial data and used the scroll API to efficiently fetch a large number of results. Finally, we used the terms lookup mechanism to speed up the querying process that fetches a list of terms.

In the next chapter, we'll focus on Elasticsearch clusters and how to handle them. We'll see what node discovery ...

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