A general purpose R interface to Elasticsearch

• Elasticsearch home page
• API docs

This client is developed following the latest stable releases, currently v7.10.0. It is generally compatible with older versions of Elasticsearch. Unlike the Python client, we try to keep as much compatibility as possible within a single version of this client, as that's an easier setup in R world.

You're fine running ES locally on your machine, but be careful just throwing up ES on a server with a public IP address - make sure to think about security.

• Elastic has paid products - but probably only applicable to enterprise users
• DIY security - there are a variety of techniques for securing your Elasticsearch installation. A number of resources are collected in a blog post - tools include putting your ES behind something like Nginx, putting basic auth on top of it, using https, etc.

Stable version from CRAN

install.packages("elastic")

Development version from GitHub

remotes::install_github("ropensci/elastic")

library('elastic')

• Elasticsearch installation help

w/ Docker

Pull the official elasticsearch image

# elasticsearch needs to have a version tag. We're pulling 7.10.1 here
docker pull elasticsearch:7.10.1

Then start up a container

docker run -d -p 9200:9200 elasticsearch:7.10.1

Then elasticsearch should be available on port 9200, try curl localhost:9200 and you should get the familiar message indicating ES is on.

If you're using boot2docker, you'll need to use the IP address in place of localhost. Get it by doing boot2docker ip.

on OSX

• Download zip or tar file from Elasticsearch see here for download, e.g., curl -L -O https://artifacts.elastic.co/downloads/elasticsearch/elasticsearch-7.10.0-darwin-x86_64.tar.gz
• Extract: tar -zxvf elasticsearch-7.10.0-darwin-x86_64.tar.gz
• Move it: sudo mv elasticsearch-7.10.0 /usr/local
• Navigate to /usr/local: cd /usr/local
• Delete symlinked elasticsearch directory: rm -rf elasticsearch
• Add shortcut: sudo ln -s elasticsearch-7.10.0 elasticsearch (replace version with your version)

You can also install via Homebrew: brew install elasticsearch

Note: for the 1.6 and greater upgrades of Elasticsearch, they want you to have java 8 or greater. I downloaded Java 8 from here http://www.oracle.com/technetwork/java/javase/downloads/jdk8-downloads-2133151.html and it seemed to work great.

I am not totally clear on best practice here, but from what I understand, when you upgrade to a new version of Elasticsearch, place old elasticsearch/data and elasticsearch/config directories into the new installation (elasticsearch/ dir). The new elasticsearch instance with replaced data and config directories should automatically update data to the new version and start working. Maybe if you use homebrew on a Mac to upgrade it takes care of this for you - not sure.

Obviously, upgrading Elasticsearch while keeping it running is a different thing (some help here from Elastic).

• Navigate to elasticsearch: cd /usr/local/elasticsearch
• Start elasticsearch: bin/elasticsearch

I create a little bash shortcut called es that does both of the above commands in one step (cd /usr/local/elasticsearch && bin/elasticsearch).

The function connect() is used before doing anything else to set the connection details to your remote or local elasticsearch store. The details created by connect() are written to your options for the current session, and are used by elastic functions.

x <- connect(port = 9200)

If you're following along here with a local instance of Elasticsearch, you'll use x below to do more stuff.

For AWS hosted elasticsearch, make sure to specify path = "" and the correct port - transport schema pair.

connect(host = <aws_es_endpoint>, path = "", port = 80, transport_schema  = "http")
  # or
connect(host = <aws_es_endpoint>, path = "", port = 443, transport_schema  = "https")

If you are using Elastic Cloud or an installation with authentication (X-pack), make sure to specify path = "", user = "", pwd = "" and the correct port - transport schema pair.

connect(host = <ec_endpoint>, path = "", user="test", pwd = "1234", port = 9243, transport_schema  = "https")

Elasticsearch has a bulk load API to load data in fast. The format is pretty weird though. It's sort of JSON, but would pass no JSON linter. I include a few data sets in elastic so it's easy to get up and running, and so when you run examples in this package they'll actually run the same way (hopefully).

I have prepare a non-exported function useful for preparing the weird format that Elasticsearch wants for bulk data loads, that is somewhat specific to PLOS data (See below), but you could modify for your purposes. See make_bulk_plos() and make_bulk_gbif() here.

Elasticsearch provides some data on Shakespeare plays. I've provided a subset of this data in this package. Get the path for the file specific to your machine:

shakespeare <- system.file("examples", "shakespeare_data.json", package = "elastic")
# If you're on Elastic v6 or greater, use this one
shakespeare <- system.file("examples", "shakespeare_data_.json", package = "elastic")
shakespeare <- type_remover(shakespeare)

Then load the data into Elasticsearch:

make sure to create your connection object with connect()

# x <- connect()  # do this now if you didn't do this above
invisible(docs_bulk(x, shakespeare))

If you need some big data to play with, the shakespeare dataset is a good one to start with. You can get the whole thing and pop it into Elasticsearch (beware, may take up to 10 minutes or so.):

curl -XGET https://download.elastic.co/demos/kibana/gettingstarted/shakespeare_6.0.json > shakespeare.json
curl -XPUT localhost:9200/_bulk --data-binary @shakespeare.json

A dataset inluded in the elastic package is metadata for PLOS scholarly articles. Get the file path, then load:

if (index_exists(x, "plos")) index_delete(x, "plos")
plosdat <- system.file("examples", "plos_data.json", package = "elastic")
plosdat <- type_remover(plosdat)
invisible(docs_bulk(x, plosdat))

A dataset inluded in the elastic package is data for GBIF species occurrence records. Get the file path, then load:

if (index_exists(x, "gbif")) index_delete(x, "gbif")
gbifdat <- system.file("examples", "gbif_data.json", package = "elastic")
gbifdat <- type_remover(gbifdat)
invisible(docs_bulk(x, gbifdat))

GBIF geo data with a coordinates element to allow geo_shape queries

if (index_exists(x, "gbifgeo")) index_delete(x, "gbifgeo")
gbifgeo <- system.file("examples", "gbif_geo.json", package = "elastic")
gbifgeo <- type_remover(gbifgeo)
invisible(docs_bulk(x, gbifgeo))

There are more datasets formatted for bulk loading in the sckott/elastic_data GitHub repository. Find it at https://github.com/sckott/elastic_data

Search the plos index and only return 1 result

Search(x, index = "plos", size = 1)$hits$hits
#> [[1]]
#> [[1]]$`_index`
#> [1] "plos"
#> 
#> [[1]]$`_type`
#> [1] "_doc"
#> 
#> [[1]]$`_id`
#> [1] "0"
#> 
#> [[1]]$`_score`
#> [1] 1
#> 
#> [[1]]$`_source`
#> [[1]]$`_source`$id
#> [1] "10.1371/journal.pone.0007737"
#> 
#> [[1]]$`_source`$title
#> [1] "Phospholipase C-\u03b24 Is Essential for the Progression of the Normal Sleep Sequence and Ultradian Body Temperature Rhythms in Mice"

Search the plos index, and query for antibody, limit to 1 result

Search(x, index = "plos", q = "antibody", size = 1)$hits$hits
#> [[1]]
#> [[1]]$`_index`
#> [1] "plos"
#> 
#> [[1]]$`_type`
#> [1] "_doc"
#> 
#> [[1]]$`_id`
#> [1] "813"
#> 
#> [[1]]$`_score`
#> [1] 5.18676
#> 
#> [[1]]$`_source`
#> [[1]]$`_source`$id
#> [1] "10.1371/journal.pone.0107638"
#> 
#> [[1]]$`_source`$title
#> [1] "Sortase A Induces Th17-Mediated and Antibody-Independent Immunity to Heterologous Serotypes of Group A Streptococci"

Get document with id=4

docs_get(x, index = 'plos', id = 4)
#> $`_index`
#> [1] "plos"
#> 
#> $`_type`
#> [1] "_doc"
#> 
#> $`_id`
#> [1] "4"
#> 
#> $`_version`
#> [1] 1
#> 
#> $`_seq_no`
#> [1] 4
#> 
#> $`_primary_term`
#> [1] 1
#> 
#> $found
#> [1] TRUE
#> 
#> $`_source`
#> $`_source`$id
#> [1] "10.1371/journal.pone.0107758"
#> 
#> $`_source`$title
#> [1] "Lactobacilli Inactivate Chlamydia trachomatis through Lactic Acid but Not H2O2"

Get certain fields

docs_get(x, index = 'plos', id = 4, fields = 'id')
#> $`_index`
#> [1] "plos"
#> 
#> $`_type`
#> [1] "_doc"
#> 
#> $`_id`
#> [1] "4"
#> 
#> $`_version`
#> [1] 1
#> 
#> $`_seq_no`
#> [1] 4
#> 
#> $`_primary_term`
#> [1] 1
#> 
#> $found
#> [1] TRUE

Same index and different document ids

docs_mget(x, index = "plos", id = 1:2)
#> $docs
#> $docs[[1]]
#> $docs[[1]]$`_index`
#> [1] "plos"
#> 
#> $docs[[1]]$`_type`
#> [1] "_doc"
#> 
#> $docs[[1]]$`_id`
#> [1] "1"
#> 
#> $docs[[1]]$`_version`
#> [1] 1
#> 
#> $docs[[1]]$`_seq_no`
#> [1] 1
#> 
#> $docs[[1]]$`_primary_term`
#> [1] 1
#> 
#> $docs[[1]]$found
#> [1] TRUE
#> 
#> $docs[[1]]$`_source`
#> $docs[[1]]$`_source`$id
#> [1] "10.1371/journal.pone.0098602"
#> 
#> $docs[[1]]$`_source`$title
#> [1] "Population Genetic Structure of a Sandstone Specialist and a Generalist Heath Species at Two Levels of Sandstone Patchiness across the Strait of Gibraltar"
#> 
#> 
#> 
#> $docs[[2]]
#> $docs[[2]]$`_index`
#> [1] "plos"
#> 
#> $docs[[2]]$`_type`
#> [1] "_doc"
#> 
#> $docs[[2]]$`_id`
#> [1] "2"
#> 
#> $docs[[2]]$`_version`
#> [1] 1
#> 
#> $docs[[2]]$`_seq_no`
#> [1] 2
#> 
#> $docs[[2]]$`_primary_term`
#> [1] 1
#> 
#> $docs[[2]]$found
#> [1] TRUE
#> 
#> $docs[[2]]$`_source`
#> $docs[[2]]$`_source`$id
#> [1] "10.1371/journal.pone.0107757"
#> 
#> $docs[[2]]$`_source`$title
#> [1] "Cigarette Smoke Extract Induces a Phenotypic Shift in Epithelial Cells; Involvement of HIF1\u03b1 in Mesenchymal Transition"

You can optionally get back raw json from Search(), docs_get(), and docs_mget() setting parameter raw=TRUE.

For example:

(out <- docs_mget(x, index = "plos", id = 1:2, raw = TRUE))
#> [1] "{\"docs\":[{\"_index\":\"plos\",\"_type\":\"_doc\",\"_id\":\"1\",\"_version\":1,\"_seq_no\":1,\"_primary_term\":1,\"found\":true,\"_source\":{\"id\":\"10.1371/journal.pone.0098602\",\"title\":\"Population Genetic Structure of a Sandstone Specialist and a Generalist Heath Species at Two Levels of Sandstone Patchiness across the Strait of Gibraltar\"}},{\"_index\":\"plos\",\"_type\":\"_doc\",\"_id\":\"2\",\"_version\":1,\"_seq_no\":2,\"_primary_term\":1,\"found\":true,\"_source\":{\"id\":\"10.1371/journal.pone.0107757\",\"title\":\"Cigarette Smoke Extract Induces a Phenotypic Shift in Epithelial Cells; Involvement of HIF1\u03b1 in Mesenchymal Transition\"}}]}"
#> attr(,"class")
#> [1] "elastic_mget"

Then parse

jsonlite::fromJSON(out)
#> $docs
#>   _index _type _id _version _seq_no _primary_term found
#> 1   plos  _doc   1        1       1             1  TRUE
#> 2   plos  _doc   2        1       2             1  TRUE
#>                     _source.id
#> 1 10.1371/journal.pone.0098602
#> 2 10.1371/journal.pone.0107757
#>                                                                                                                                                _source.title
#> 1 Population Genetic Structure of a Sandstone Specialist and a Generalist Heath Species at Two Levels of Sandstone Patchiness across the Strait of Gibraltar
#> 2                                Cigarette Smoke Extract Induces a Phenotypic Shift in Epithelial Cells; Involvement of HIF1\u03b1 in Mesenchymal Transition

• On secure Elasticsearch servers:
  • HEAD requests don't seem to work, not sure why
  • If you allow only GET requests, a number of functions that require POST requests obviously then won't work. A big one is Search(), but you can use Search_uri() to get around this, which uses GET instead of POST, but you can't pass a more complicated query via the body

A screencast introducing the package: vimeo.com/124659179

• Please report any issues or bugs
• License: MIT
• Get citation information for elastic in R doing citation(package = 'elastic')
• Please note that this package is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.