Elasticsearch: The Definitive Guide (Early Release, Raw and by Clinton Gormley, Zachary Tong

By Clinton Gormley, Zachary Tong

(publication date: 14 Feb 2015)

Learn easy methods to use Elasticsearch, an open resource, disbursed, RESTful seek engine outfitted on most sensible of Apache Lucene. every one bankruptcy during this booklet tackles a specific side of Elasticsearch with separate sections for novices extra complicated programmers. If you’re a newbie, complicated thoughts aren't required interpreting, yet you could revisit them after you have an excellent figuring out of the basics.

This ebook explains innovations similar to complete textual content seek, close to genuine time visibility of seek info, loss of transactions, and NoSQL-style denormalization from first rules, permitting novices to glean adequate details to wake up and working with Elasticsearch.

Whether you would like full-text seek or real-time analytics of based data—or both—the Elasticsearch dispensed seek engine is a perfect strategy to placed your facts to paintings. This sensible consultant not just indicates you ways to go looking, learn, and discover information with Elasticsearch, but in addition is helping you care for the complexities of human language, geolocation, and relationships.

If you’re a newcomer to either seek and disbursed platforms, you’ll fast how you can combine Elasticsearch into your program. more matured clients will decide up plenty of complicated ideas. through the publication, you’ll stick with a problem-based method of study why, while, and the way to take advantage of Elasticsearch features.

Understand how Elasticsearch translates info on your documents
Index and question your facts to use seek ideas comparable to relevance and be aware proximity
Handle human language during the powerful use of analyzers and queries
Summarize and team facts to teach total tendencies, with aggregations and analytics
Use geo-points and geo-shapes—Elasticsearch’s techniques to geolocation
Model your info to use Elasticsearch’s horizontal scalability
Learn tips to configure and display screen your cluster in construction

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Our cluster is not only fully functional but also always available. Scale horizontally What about scaling as the demand for our application grows? If we start a third node, our cluster reorganizes itself to look like Figure 2-4. 30 | Chapter 2: Life inside a Cluster Figure 2-4. A three-node cluster — shards have been reallocated to spread the load One shard each from Node 1 and Node 2 have moved to the new Node 3 and we have two shards per node, instead of three. This means that the hardware resources (CPU, RAM, I/O) of each node are being shared between fewer shards, allowing each shard to perform better.

It is similar to GROUP BY in SQL, but much more powerful. For example, let’s find the most popular interests enjoyed by our employees: GET /megacorp/employee/_search { "aggs": { "all_interests": { "terms": { "field": "interests" } } } } Ignore the syntax for now and just look at the results: { ... "hits": { ... }, "aggregations": { "all_interests": { "buckets": [ { "key": "doc_count": }, { "key": "doc_count": }, { "key": 20 | Chapter 1: You know, for Search… "music", 2 "forestry", 1 "sports", "doc_count": 1 } ] } } } We can see that two employees are interested in music, one in forestry and one in sports.

Allow simple full text search and more complex phrase searches. • Returned highlighted search snippets from the text in the matching documents. • Enable management to build analytic dashboards over the data. Indexing employee documents The first order of business is storing employee data. This will take the form of an “em‐ ployee document”, where a single document represents a single employee. The act of storing data in Elasticsearch is called indexing, but before we can index a document we need to decide where to store it.

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