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Tutorial: Improving Performance with Data Placement in Search Engine Shards

One of the most common ways to improve the performance of software systems is to parallelize the work that needs to be performed. Search engines are no exception: as the data stored in search indices increases, data inside them gets split into multiple shards. These shards are searched in parallel and results are retrieved from them, then merged/sorted before the final search result is produced. 

Download our technical tutorial to learn about a data placement technique which results in substantial improvements in query performance. The discussions focus on Elasticsearch and Solr as the main search engines where the technique can be applied. 

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