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POWhat is an effective way to search world-wide location names with ElasticSearch?
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copied!<p>I have location information provided by <a href="http://www.geonames.org/" rel="nofollow noreferrer">GeoNames.org</a> parsed into a relational database. Using this information, I am attempting to build an ElasticSearch index that contains populated place (city) names, administrative division (state, province, etc.) names, country names and country codes. My goal is to provide a location search that is similar to Google Maps':</p> <p><img src="https://i.stack.imgur.com/7BVxa.png" alt="Google Maps"></p> <p>I don't need the cool bold highlighting, but I do need the search to return similar results in a similar way. I've tried creating a mapping with a single location field consisting of the entire location name (e.g., "Round Rock, TX, United States") and I've also tried having five separate fields consisting of each piece of a location. I've tried keyword and prefix queries and edgengram analyzers; I have been unsuccessful in finding the correct configuration to get this working properly.</p> <p>What kinds of analyzers--both index and search--should I be looking at to accomplish my goals? This search doesn't have to be as perfected as Google's but I'd like it to be at least similar.</p> <p>I do want to support partial-name matches, which is why I've been fiddling with edgengram. For example, a search of "round r" should match Round Rock, TX, United States. Also, I would prefer that results whose populated place (city) names begin with the exact search term be ranked higher than other results. For example, a search of "round ro" should match Round Rock, TX, United States before Round, Some Province, RO (Romania). I hope I've made this clear enough.</p> <p>Here is my current index configuration (this is an anonymous type in C# that is later serialized to JSON and passed to the ElasticSearch API):</p> <pre><code>settings = new { index = new { number_of_shards = 1, number_of_replicas = 0, refresh_interval = -1, analysis = new { analyzer = new { edgengram_index_analyzer = new { type = "custom", tokenizer = "index_tokenizer", filter = new[] { "lowercase", "asciifolding" }, char_filter = new[] { "no_commas_char_filter" }, stopwords = new object[0] }, search_analyzer = new { type = "custom", tokenizer = "standard", filter = new[] { "lowercase", "asciifolding" }, char_filter = new[] { "no_commas_char_filter" }, stopwords = new object[0] } }, tokenizer = new { index_tokenizer = new { type = "edgeNGram", min_gram = 1, max_gram = 100 } }, char_filter = new { no_commas_char_filter = new { type = "mapping", mappings = new[] { ",=>" } } } } } }, mappings = new { location = new { _all = new { enabled = false }, properties = new { populatedPlace = new { index_analyzer = "edgengram_index_analyzer", type = "string" }, administrativeDivision = new { index_analyzer = "edgengram_index_analyzer", type = "string" }, administrativeDivisionAbbreviation = new { index_analyzer = "edgengram_index_analyzer", type = "string" }, country = new { index_analyzer = "edgengram_index_analyzer", type = "string" }, countryCode = new { index_analyzer = "edgengram_index_analyzer", type = "string" }, population = new { type = "long" } } } } </code></pre>

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