A general purpose R interface to Elasticsearch
Also check out elasticdsl
- an R DSL for Elasticsearch - https://github.com/ropensci/elasticdsl
This client is developed following the latest stable releases, currently v6.4.0
. 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.
- Shield - This is a paid product provided by Elastic - so probably only applicable to enterprise users
- DIY security - there are a variety of techniques for securing your Elasticsearch. 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
install.packages("devtools")
devtools::install_github("ropensci/elastic")
library('elastic')
w/ Docker
Pull the official elasticsearch image
docker pull elasticsearch
Then start up a container
docker run -d -p 9200:9200 elasticsearch
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-6.4.0.tar.gz
- Extract:
tar -zxvf elasticsearch-6.4.0.tar.gz
- Move it:
sudo mv elasticsearch-6.4.0 /usr/local
- Navigate to /usr/local:
cd /usr/local
- Delete symlinked
elasticsearch
directory:rm -rf elasticsearch
- Add shortcut:
sudo ln -s elasticsearch-6.4.0 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.
connect(es_port = 9200)
#> transport: http
#> host: 127.0.0.1
#> port: 9200
#> path: NULL
#> username: NULL
#> password: <secret>
#> errors: simple
#> headers (names): NULL
For AWS hosted elasticsearch, make sure to specify es_path = "" and the correct port - transport schema pair.
connect(es_host = <aws_es_endpoint>, es_path = "", es_port = 80, es_transport_schema = "http")
# or
connect(es_host = <aws_es_endpoint>, es_path = "", es_port = 443, es_transport_schema = "https")
If you are using Elastic Cloud or an installation with authentication (X-pack), make sure to specify es_path = "", es_user = "", es_pwd = "" and the correct port - transport schema pair.
connect(es_host = <ec_endpoint>, es_path = "", es_user="test", es_pwd = "1234", es_port = 9243, es_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:
#> transport: http
#> host: 127.0.0.1
#> port: 9200
#> path: NULL
#> username: NULL
#> password: <secret>
#> errors: simple
#> headers (names): NULL
shakespeare <- system.file("examples", "shakespeare_data.json", package = "elastic")
# If you're on Elastic v6 or greater, use this one with 1 type instead of 3:
shakespeare <- system.file("examples", "shakespeare_data_.json", package = "elastic")
Then load the data into Elasticsearch:
invisible(docs_bulk(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:
plosdat <- system.file("examples", "plos_data.json", package = "elastic")
invisible(docs_bulk(plosdat))
A dataset inluded in the elastic
package is data for GBIF species occurrence records. Get the file path, then load:
gbifdat <- system.file("examples", "gbif_data.json", package = "elastic")
invisible(docs_bulk(gbifdat))
GBIF geo data with a coordinates element to allow geo_shape
queries
gbifgeo <- system.file("examples", "gbif_geo.json", package = "elastic")
invisible(docs_bulk(gbifgeo))
There are more datasets formatted for bulk loading in the ropensci/elastic_data
GitHub repository. Find it at https://github.com/ropensci/elastic_data
Search the plos
index and only return 1 result
Search(index = "plos", size = 1)$hits$hits
#> [[1]]
#> [[1]]$`_index`
#> [1] "plos"
#>
#> [[1]]$`_type`
#> [1] "article"
#>
#> [[1]]$`_id`
#> [1] "0"
#>
#> [[1]]$`_score`
#> [1] 1
#>
#> [[1]]$`_source`
#> [[1]]$`_source`$id
#> [1] "10.1371/journal.pone.0007737"
#>
#> [[1]]$`_source`$title
#> [1] "Phospholipase C-β4 Is Essential for the Progression of the Normal Sleep Sequence and Ultradian Body Temperature Rhythms in Mice"
Search the plos
index, and the article
document type, and query for antibody, limit to 1 result
Search(index = "plos", type = "article", q = "antibody", size = 1)$hits$hits
#> [[1]]
#> [[1]]$`_index`
#> [1] "plos"
#>
#> [[1]]$`_type`
#> [1] "article"
#>
#> [[1]]$`_id`
#> [1] "216"
#>
#> [[1]]$`_score`
#> [1] 4.423327
#>
#> [[1]]$`_source`
#> [[1]]$`_source`$id
#> [1] "10.1371/journal.pone.0107664"
#>
#> [[1]]$`_source`$title
#> [1] "Antibody-Validated Proteins in Inflamed Islets of Fulminant Type 1 Diabetes Profiled by Laser-Capture Microdissection Followed by Mass Spectrometry"
Get document with id=1
docs_get(index = 'plos', type = 'article', id = 4)
#> $`_index`
#> [1] "plos"
#>
#> $`_type`
#> [1] "article"
#>
#> $`_id`
#> [1] "4"
#>
#> $`_version`
#> [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(index = 'plos', type = 'article', id = 4, fields = 'id')
#> $`_index`
#> [1] "plos"
#>
#> $`_type`
#> [1] "article"
#>
#> $`_id`
#> [1] "4"
#>
#> $`_version`
#> [1] 1
#>
#> $found
#> [1] TRUE
Same index and type, different document ids
docs_mget(index = "plos", type = "article", id = 1:2)
#> $docs
#> $docs[[1]]
#> $docs[[1]]$`_index`
#> [1] "plos"
#>
#> $docs[[1]]$`_type`
#> [1] "article"
#>
#> $docs[[1]]$`_id`
#> [1] "1"
#>
#> $docs[[1]]$`_version`
#> [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] "article"
#>
#> $docs[[2]]$`_id`
#> [1] "2"
#>
#> $docs[[2]]$`_version`
#> [1] 1
#>
#> $docs[[2]]$found
#> [1] TRUE
#>
#> $docs[[2]]$`_source`
#> $docs[[2]]$`_source`$id
#> [1] "10.1371/journal.pone.0107757"
#>
#> $docs[[2]]$`_source`$title
#> [1] "Cigarette Smoke Extract Induces a Phenotypic Shift in Epithelial Cells; Involvement of HIF1α in Mesenchymal Transition"
Different indeces, types, and ids
docs_mget(index_type_id = list(c("plos", "article", 1), c("gbif", "record", 1)))$docs[[1]]
#> $`_index`
#> [1] "plos"
#>
#> $`_type`
#> [1] "article"
#>
#> $`_id`
#> [1] "1"
#>
#> $`_version`
#> [1] 1
#>
#> $found
#> [1] TRUE
#>
#> $`_source`
#> $`_source`$id
#> [1] "10.1371/journal.pone.0098602"
#>
#> $`_source`$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"
You can optionally get back raw json
from Search()
, docs_get()
, and docs_mget()
setting parameter raw=TRUE
.
For example:
(out <- docs_mget(index = "plos", type = "article", id = 1:2, raw = TRUE))
#> [1] "{\"docs\":[{\"_index\":\"plos\",\"_type\":\"article\",\"_id\":\"1\",\"_version\":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\":\"article\",\"_id\":\"2\",\"_version\":1,\"found\":true,\"_source\":{\"id\":\"10.1371/journal.pone.0107757\",\"title\":\"Cigarette Smoke Extract Induces a Phenotypic Shift in Epithelial Cells; Involvement of HIF1α in Mesenchymal Transition\"}}]}"
#> attr(,"class")
#> [1] "elastic_mget"
Then parse
jsonlite::fromJSON(out)
#> $docs
#> _index _type _id _version found _source.id
#> 1 plos article 1 1 TRUE 10.1371/journal.pone.0098602
#> 2 plos article 2 1 TRUE 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 HIF1α 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 requirePOST
requests obviously then won't work. A big one isSearch()
, but you can useSearch_uri()
to get around this, which usesGET
instead ofPOST
, but you can't pass a more complicated query via the body
- Please report any issues or bugs
- License: MIT
- Get citation information for
elastic
in R doingcitation(package = 'elastic')
- Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.