Introduction When you’re doing a search in Elasticsearch, you may have a large number of results returned from your query. It can be hard to wade through such a lengthy result set; fortunately, Elasticsearch provides the ability to limit the number of results your query returns through pagination. In this step-by-step tutorial, you’ll learn how … Continued
Introduction This step-by-step tutorial explains how you can use slop and Phrase Search in Elasticsearch. The flexibility of the slop parameter allows you to view matches that are close—not exact–to your actual Phrase Searches. The more general results may bring to attention varieties of certain products. The knowledge might help you to best streamline inventory … Continued
Introduction It’s true that you can quickly locate a specific phrase in an index in Elasticsearch. To accomplish the task, you’ll want to use Phrase Search. But if you’re just starting phrase search in Elasticsearch, you may be tempted to conduct a multiple word search with the match query. Here’s why match works for single-word … Continued
Introduction When you’re working with data in Elasticsearch, it’s important to understand your options for storing and handling string values. Elasticsearch has two core datatypes that can store string data: text and keyword. It’s easy to get these two types confused, but this tutorial will help set the story straight. In this article, we’ll look … Continued
Introduction There’s a good chance that not all of the data the typical user stores in Elasticsearch will end up being used in queries. For example, a user might be using Elasticsearch to store web session data. While it makes sense that a user would want to query on fields like the last update time … Continued
Introduction Have you ever wanted to go through an Elasticsearch index and do a “find and replace” on your data? Maybe you wanted to replace all single quotes with double quotes, or maybe you wanted to check for instances of a profanity and remove them. Fortunately, there’s an easy way to accomplish this task: using … Continued
Introduction When you’re working with data in Elasticsearch, there will likely be situations when you need to delete an index. You might have created an index just to test out some feature, but you don’t need to keep it permanently. You might have changed your overall data structure and find that you’re no longer using … Continued
Introduction If you’re familiar with Mongo or SQL databases, an index has the same function as those database technologies. Just like a database, an index holds documents. Databases use tables to differentiate between the kinds of documents while indexes characterize by document type. The latter lets you dig deep into the meaning of your data. … Continued
Introduction When importing data into Elasticsearch it will infer the types it uses based on the data that it is categorizing. It might be necessary to be explicit with details in Kibana if the working data is ambiguous or Elasticsearch is inferring the wrong type. Explicitly creating an object mapping is also good practice because … Continued
Introduction If you’re planning to harness the full power of the Elastic stack — Elasticsearch, Logstash, and Kibana — it’s important to make sure you’ve installed compatible versions of each product. Kibana, for example, should be set up to run alongside an Elasticsearch node of the same version. According to Elastic’s documentation, running different version … Continued
