Is it possible to boost 'newest' items using elasticsearch? (FOQElasticaBundle)

Whew, after much experimentation and hours of trawling the Interweb I finally managed to get the desired behavior! (Full credit goes to Clinton Gormley.)

Mapping configuration:

mappings:    title: { boost: 8 }    summary: { boost: 5 }    text: { boost: 3 }    author:    publishedAt: { type: date }

Here is the code using the PHP client, Elastica, to dynamically build the query to boost using the original mapping AND the published date:

$query = new \Elastica_Query_Bool();$query->addMust(new \Elastica_Query_QueryString($queryString));$ranges = array();for ($i = 1; $i <= 5; $i++) {    $date = new \DateTime("-$i month");    $currentRange = new \Elastica_Query_Range();    $currentRange->addField('publishedAt', array(        'boost' => (6 - $i),        'gte' => $date->getTimestamp()    ));    $ranges[] = $currentRange->toArray();}$query->addShould($ranges);/** @var $pagerfanta Pagerfanta */$pagerfanta = $this->getFinder()->findPaginated($query);

And for those of you more interested in the raw elasticsearch query (only with 3 date ranges for brevity)...

curl -XPOST 'http://localhost:9200/website/story/_search?pretty=true' -d '{  "query" : {    "bool" : {      "must" : {        query_string: {          query: "<search term(s)>"        }      },      "should" : [        {          "range" : {            "publishedAt" : {              "boost" : 5,              "gte" : "<1 month ago>"            }          }        },        {          "range" : {            "publishedAt" : {              "boost" : 4,              "gte" : "<2 months ago>"            }          }        },        {          "range" : {            "publishedAt" : {              "boost" : 3,              "gte" : "<3 months ago>"            }          }        }      ]    }  }}'

You can use a decay scoring function, to decrease the scoring versus time :

{ "query": { "function_score": {    "functions": [     {      "linear": {        "pubdate": {          "origin": 1398673886,          "scale": "1h",          "offset": 0,          "decay": 0.1        }      }    }    ]   }  } }

A full elasticsearch 5 example based on function_score. See this blogpost and function_score docs for more info.

Allows for boosting more recent entries based on multiple date ranges, with varying strengths, on a gaussian curve without "hard cutoffs".

{    "query": {        "function_score": {            "score_mode": "sum", // All functions outputs get summed            "boost_mode": "multiply", // The documents relevance is multiplied with the sum            "functions": [                {                    // The relevancy of old posts is multiplied by at least one.                    // Remove if you want to exclude old posts                    "weight": 1                },                {                    // Published this month get a big boost                    "weight": 5,                    "gauss": {                        "date": { // <- Change to your date field name                            "origin": "2017-04-07", // Change to current date                            "scale": "31d",                            "decay": 0.5                        }                    }                },                {                    // Published this year get a boost                    "weight": 2,                    "gauss": {                        "date": { // <- Change to your date field name                            "origin": "2017-04-07", // Change to current date                            "scale": "356d",                            "decay": 0.5                        }                    }                }            ],            "query": {                // The rest of your search here, change to something relevant                "match": { "title": "< your search string >" }            }        }    }}