Recent Posts by Vineeth Mohan

Vineeth Mohan is a certified Elasticsearch trainer and author of "Elasticsearch Blueprints" book.

The suggest API is one of the important APIs in Elasticsearch. It is used extensively in search solutions to tremendously improve the user experience. Ranging from normal autocomplete to context based suggestions, this API has many interesting use cases, which we will explore. In this tutorial, we show how to implement a simple autocomplete with elasticsearch.

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Sometimes when firing a query, it gets delayed, or the response time is slow. There could be a number of reasons for the sluggishness of the query; ranging from shard issues or from computing certain elements in the query. Elasticsearch, from version 2.2, provides the Profile API for users to inspect the query execution time and other details. In this blog post, we explore how the profile API can be used to look into query timings.

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In this blog post, we explain memory related settings in detail, which can be used to give elasticsearch better performance especially at times of scaling. We also go over issues caused by poor memory settings, and the ways to overcome them.  

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Are you looking for full-text search and highlight capability on .PDF, .doc, or .epub files that you have in your system? In this tutorial, we show you how with the mapper-attachment-plugin

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So far we have seen the grouping of documents based on various aggregations like term, date histogram, and more. In this post we are going to see the limitations of the date_histogram aggregation in certain cases, and how to overcome that by employing elasticsearch scripting.

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In the previous post we saw how to set up, configure, and index network traffic data using packetbeat, logstash and elasticsearch. 

In this post we will see how to visualize the data with the help of Kibana.

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In many cases we want to use inputs from different databases which are not natively supported by Elasticsearch. In this post we show how to migrate data from a MySql database to Elasticsearch via Logstash.

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When dealing with a large number of parallel operations in elasticsearch, such as search requests or bulk indexing operations, you may encounter thread pool related errors. Here we explain thread pools and discuss a typical search request thread pool error that might be faced, as well as how to handle such issues.

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In the last article we explained how the simple moving average pipeline aggregation worked and how to analyze the trends of the stock values of a firm with it. In this post, we discuss more moving average aggregation models and their differences in detail.  We use the same data set as in the previous post.  

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We have seen numerous pipeline aggregations in previous posts. Here we discuss another pipeline aggregation called the moving average aggregation and its significance, as well as its application in real-life scenarios.

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