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With Qbox, you can count on your clusters being up when you need them. You're fully backed with a SLA, a dedicated support team, and fully managed upgrades and migrations.

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Qbox is the only hosted Elasticsearch provider that allows you to choose both the location and the cloud platform of your cluster, which lowers response times significantly.

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Kibana, Logstash, and Elasticsearch. Get the ELK stack, a suite of powerful search analytics for your cluster.

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Learn more about Qbox Elasticsearch and how to get the most out of shards, aggregations, and more.

  • A Deep Dive into Significant Terms and Significant Text Bucket Aggregations in Elasticsearch

    In this article, we'll continue our overview of Elasticsearch bucket aggregations, focusing on significant terms and significant text aggregations. These aggregations are designed to search for interesting and/or unusual occurrences of terms in your datasets that can tell much about the hidden properties of your data. This functionality is especially useful for the following use cases:

    • Identifying relevant documents for the user queries containing synonyms, acronyms, etc. For example, the significant terms aggregation could suggest documents with "bird flu" when the user searches for H1N1. 
    • Identifying anomalies and interesting occurrences in your data. For example, by filtering documents based on location, we could identify the most frequent crime types in particular areas. 
    • Identifying the most significant properties of a group of subjects using the significant terms aggregation on integer fields like height, weight, income, etc. 

    It should be noted that both significant terms and significant text aggregations perform complex statistical computations on documents retrieved by the direct query (foreground set) and all other documents in your index (background set). Therefore, both aggregations are computationally intensive and should be properly configured to work fast. However, once you master them with the help of this tutorial, you'll acquire a powerful tool for building very useful features in your applications and getting useful insights from your datasets. Let's get started!

  • Comprehensive Guide to Bucket Aggregations in Elasticsearch: Part I

    Bucket aggregations in Elasticsearch create buckets or sets of documents based on certain criteria. Depending on the aggregation type, you can create filtering buckets, that is, buckets representing different value ranges and intervals for numeric values, dates, IP ranges, and more. 

    Although bucket aggregations do not calculate metrics, they can hold metrics sub-aggregations that can calculate metrics for each bucket generated by the bucket aggregation. This makes bucket aggregations very useful for the granular representation and analysis of your Elasticsearch indices. In this article, we'll focus on such bucket aggregations as histogram, range, filters, and terms. Let's get started!

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