Qbox to join forces with Instaclustr. Read about it on our blog post here.

If you’ve spent time trying to ramp up on Elasticsearch and configure a local cluster, you may be wondering if there’s a better way. Perhaps you’re in need of solid advice, and maybe you’d like to find an easier path. In this article, we summarize a number of best practices in managing an ES cluster. Also, we provide many links to specific information that you can find in our extensive blog and knowledge base.

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Qbox users will often need to import an existing dataset from a primary data source or an external Elasticsearch cluster.

As you might expect, the indexing activity is much more intensive during an initial import of such data. This initial indexing places a significant load on the system. In this short article we show you how to change a couple of settings that will greatly improve the efficiency of your bulk data loads into Elasticsearch clusters.

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Although Elasticsearch offers an efficient scoring algorithm, it may often be inadequate in e-commerce contexts. Most users tend to care only about the topmost number of results. which means that it’s very important to have a flexible scoring mechanism. If you can present the topmost results according to user preference, then your conversion rate is likely to increase significantly.

In this article, we’ll look at the default scoring configuration in Elasticsearch, and we’ll also walk through several customizations to the scoring. This knowledge can help you achieve a user-customizable list of results.

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