Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Mapping in ElasticSearch, what, how and why? #63

Open
heron2014 opened this issue Apr 10, 2016 · 2 comments
Open

Mapping in ElasticSearch, what, how and why? #63

heron2014 opened this issue Apr 10, 2016 · 2 comments
Assignees

Comments

@heron2014
Copy link
Member

What is mapping? Why is it important? How to do it?

According to this tutorial here, is good to define mappings when you define your index, instead of default mapping by ES.

@heron2014 heron2014 self-assigned this Apr 10, 2016
@heron2014
Copy link
Member Author

What
Mapping in ES is a format data related to each field. Official docs

When we index a document with ElasticSearch it (simplified) does two things: it stores the original data untouched for later retrieval in the form of _source and it indexes each JSON property into one or more fields in a Lucene index. During the indexing it processes each field according to how the field is mapped. If it isn't mapped default mappings depending on the fields type (string, number etc) is used.

Why

For example imaging we have 2 documents in our DB.

curl -XPUT "http://localhost:9200/movies/movie/4" -d'
{
    "title": "Apocalypse Now",
    "director": "Francis Ford Coppola",
    "year": 1979,
    "genres": ["Drama", "War"]
}'
curl -XPUT "http://localhost:9200/movies/movie/1" -d'
{
    "title": "The Godfather",
    "director": "Francis Ford Coppola",
    "year": 1972,
    "genres": ["Crime", "Drama"]
}'

We process a query search to find all movies who's director is Francis Coppola.

curl -XPOST "http://localhost:9200/_search" -d'
{
    "query": {
        "constant_score": {
            "filter": {
                "term": { "director": "Francis Ford Coppola" }
            }
        }
    }
}'

and we get 0 results. Why???

As we haven't supplied any mappings for our index ElasticSearch uses the default mappings for strings for the director field. This means that in the index the director fields value isn't "Francis Ford Coppola". Instead it's something more like ["francis", "ford", "coppola"].

We can verify that by modifying our filter to instead match "francis" (or "ford" or "coppola"):

curl -XPOST "http://localhost:9200/_search" -d'
{
    "query": {
        "constant_score": {
            "filter": {
                "term": { "director": "francis" }
            }
        }
    }
}'

We got response with : 2 documents.
So, what to do if we want to filter by the exact name of the director? We modify how it's mapped.

How
There are a number of ways to add mappings to ElasticSearch, through a configuration file, as part of a HTTP request that creates and index and by calling the _mapping endpoint.

First approach to this problem:
Using the_mapping endpoint we could in theory fix the above issue by adding a mapping for the "director" field instructing ElasticSearch not to analyze (tokenize etc.) the field at all when indexing it, like this:

curl -XPUT "http://localhost:9200/movies/movie/_mapping" -d'
{
   "movie": {
      "properties": {
         "director": {
            "type": "string",
            "index": "not_analyzed"
        }
      }
   }
}'

There are however a couple of issues if we do this. First of all, it won't work as there already is a mapping for the field:

error-mappng

In many cases it's not possible to modify existing mappings. Often the easiest work around for that is to create a new index with the desired mappings and re-index all of the data into the new index.

The second problem with adding the above mapping is that, even if we could add it, we would have limited our ability to search in the director field. That is, while a search for the exact value in the field would match we wouldn't be able to search for single words in the field.

Luckily, there's a simple solution to our problem. We add a mapping that upgrades the field to a multi field. What that means is that we'll map the field multiple times for indexing. Given that one of the ways we map it match the existing mapping both by name and settings that will work fine and we won't have to create a new index.

Here's a request that does that:

mapping-solution

So, what did we just do? We told ElasticSearch that whenever it sees a property named "director" in a movie document that is about to be indexed in the movies index it should index it multiple times. Once into a field with the same name (director) and once into a field named "director.original" and the latter field should not be analyzed, maintaining the original value allowing is to filter by the exact director name.

With our new shiny mapping in place we can re-index one or both of the movies directed by Francis Ford Coppola (copy from the list of initial indexing requests above) and try the search request that filtered by author again. Only, this time we don't filter on the "director" field (which is indexed the same way as before) but instead on the "director.original" field:

curl -XPOST "http://localhost:9200/_search" -d'
{
    "query": {
        "constant_score": {
            "filter": {
                "term": { "director.original": "Francis Ford Coppola" }
            }
        }
    }
}'

We got response: 2 documents found.

@heron2014
Copy link
Member Author

Dynamic mappings - here

Nested mapping and filter - here

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Projects
None yet
Development

No branches or pull requests

1 participant