Introduction
Elasticsearch’s Explain API is a tool that provides insights into how the scoring of matches is calculated during a search query. It is particularly useful when you want to understand why a specific document is ranked higher than another in the search results. This article will delve into the details of the Explain API, its usage, and how to interpret its results.
The Explain API
The Explain API is a built-in feature of Elasticsearch that provides detailed information about the score computation for each hit in the search results. It can be used with any search query and is invoked by adding the `explain` parameter to the search request.
Here is a basic example of a search query with the explain parameter:
json
GET /_search
{
"query" : {
"match" : { "message" : "this is a test" }
},
"explain": true
}In this example, the `explain` parameter is set to `true`, which means that Elasticsearch will include an explanation of how the score for each hit was computed in the search results.
Interpreting the results
The results returned by the Explain API can be quite complex, as they provide a detailed breakdown of the scoring process. Here is an example of what an explanation might look like:
json
"_explanation" : {
"value" : 1.0,
"description" : "weight(message:test in 0) [PerFieldSimilarity], result of:",
"details" : [
{
"value" : 1.0,
"description" : "score(doc=0,freq=1.0 = termFreq=1.0\n), product of:",
"details" : [
{
"value" : 2.2,
"description" : "idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:",
"details" : [
{
"value" : 1,
"description" : "docFreq",
"details" : []
},
{
"value" : 1,
"description" : "docCount",
"details" : []
}
]
},
{
"value" : 0.45454544,
"description" : "tfNorm, computed as (freq * (k1 + 1)) / (freq + k1 * (1 - b + b * fieldLength / avgFieldLength)) from:",
"details" : [
{
"value" : 1.0,
"description" : "termFreq=1.0",
"details" : []
},
{
"value" : 1.2,
"description" : "parameter k1",
"details" : []
},
{
"value" : 0.75,
"description" : "parameter b",
"details" : []
},
{
"value" : 1.0,
"description" : "avgFieldLength",
"details" : []
},
{
"value" : 1.0,
"description" : "fieldLength",
"details" : []
}
]
}
]
}
]
}In this example, the explanation is broken down into several parts. The `value` field represents the score for the document. The `description` field provides a brief explanation of the computation, and the `details` field provides a breakdown of the computation.
The `details` field is an array of explanations, each of which provides further details about a specific part of the computation. For example, the `idf` (inverse document frequency) explanation provides details about how the `idf` value was computed, including the `docFreq` (the number of documents containing the term) and the `docCount` (the total number of documents in the index).
