GitHub - alexander-marquardt/es_local_indexer: ES Local Indexer - Desktop search powered by Elasticsearch

My professional work spans semiconductor architecture, distributed search systems, and large-scale data platforms. This page provides supporting material for that work, including selected publications, patents, open-source projects, and formal education. External Profiles LinkedIn Profile Github Profile Recognition Author of three papers that were selected to be amongst the 25 most significant FPGA papers of the past 20 years at the 20th anniversary of the International Symposium on Field-Programmable Gate Arrays in 2012. Scientific Publications The publications listed below have been cited over 3,600 times. These publications reflect my early work in FPGA architecture, placement, and routing algorithms.

Learn how to use boolean queries, boosts, and search templates to mix and match different query types. With these simple concepts, you can tune Elasticsearch's search relevance for any use case you ca...

Introduction Elasticsearch provides search functionality for some of the most important websites in the world including Wikimedia (i.e. Wikipedia), eBay, Yelp, Tinder, and many others. Elasticsearch is super scalable, which means that just as easily as it can be scaled it up for use in huge complex systems, it can also be scaled down for use in smaller projects. ES Local Indexer is a small desktop search application that runs on top of a local Elasticsearch installation. It indexes HTML documents into Elasticsearch and provides an intuitive browser-based interface for searching through the ingested documents. The ES Local Indexer project consists of two main components: