Skip to contents

Use the bulk API to update documents


  index = NULL,
  type = NULL,
  chunk_size = 1000,
  doc_ids = NULL,
  raw = FALSE,
  quiet = FALSE,
  query = list(),
  digits = NA,
  sf = NULL,



an Elasticsearch connection object, see connect()


A list, data.frame, or character path to a file. required.


(character) The index name to use. Required for data.frame input, but optional for file inputs.


(character) The type. default: NULL. Note that type is deprecated in Elasticsearch v7 and greater, and removed in Elasticsearch v8


(integer) Size of each chunk. If your data.frame is smaller thank chunk_size, this parameter is essentially ignored. We write in chunks because at some point, depending on size of each document, and Elasticsearch setup, writing a very large number of documents in one go becomes slow, so chunking can help. This parameter is ignored if you pass a file name. Default: 1000


An optional vector (character or numeric/integer) of document ids to use. This vector has to equal the size of the documents you are passing in, and will error if not. If you pass a factor we convert to character. Default: not passed


(logical) Get raw JSON back or not. If TRUE you get JSON; if FALSE you get a list. Default: FALSE


(logical) Suppress progress bar. Default: FALSE


(list) a named list of query parameters. optional. options include: pipeline, refresh, routing, _source, _source_excludes, _source_includes, timeout, wait_for_active_shards. See the docs bulk ES page for details


digits used by the parameter of the same name by jsonlite::toJSON() to convert data to JSON before being submitted to your ES instance. default: NA


used by jsonlite::toJSON() to convert sf objects. Set to "features" for conversion to GeoJSON. default: "dataframe"


Pass on curl options to crul::HttpClient


  • doc_as_upsert - is set to TRUE for all records

For doing updates with a file already prepared for the bulk API, see docs_bulk()

Only data.frame's are supported for now.

See also


if (FALSE) { # \dontrun{
x <- connect()
if (index_exists(x, "foobar")) index_delete(x, "foobar")

df <- data.frame(name = letters[1:3], size = 1:3, id = 100:102)
invisible(docs_bulk(x, df, 'foobar', es_ids = FALSE))

# add new rows in existing fields
(df2 <- data.frame(size = c(45, 56), id = 100:101))
(df2 <- data.frame(size = c(45, 56)))
df2$`_id` <- 100:101
Search(x, "foobar", asdf = TRUE)$hits$hits
invisible(docs_bulk_update(x, df2, index = 'foobar'))
Search(x, "foobar", asdf = TRUE)$hits$hits

# add new fields (and new rows by extension)
(df3 <- data.frame(color = c("blue", "red", "green"), id = 100:102))
Search(x, "foobar", asdf = TRUE)$hits$hits
invisible(docs_bulk_update(x, df3, index = 'foobar'))
Sys.sleep(2) # wait for a few sec to make sure you see changes reflected
Search(x, "foobar", asdf = TRUE)$hits$hits
} # }