https://github.com/sckott/elastic_data

Elasticsearch datasets ready for bulk loading
https://github.com/sckott/elastic_data

bulk-loading dataset elastic elasticsearch

Last synced: 18 days ago
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Elasticsearch datasets ready for bulk loading

• Host: GitHub
• URL: https://github.com/sckott/elastic_data
• Owner: sckott
• Created: 2014-11-11T02:35:28.000Z (almost 10 years ago)
• Default Branch: master
• Last Pushed: 2018-05-15T19:00:01.000Z (over 6 years ago)
• Last Synced: 2024-10-09T15:49:16.951Z (29 days ago)
• Topics: bulk-loading, dataset, elastic, elasticsearch
• Homepage:
• Size: 5.52 MB
• Stars: 43
• Watchers: 7
• Forks: 21
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
elastic datasets

================

This is a collection of smallish datasets to use for playing with Elasticsearch.

You can only fit so much data in an R package. The R client for Elasticsearch we maintain

[elastic](https://github.com/ropensci/elastic) comes with some data, but of course 

it's nice to have more, so here it is.

See also [nodbi](https://github.com/ropensci/nodbi) for working with Elasticsearch from R.

## Datasets

* `plos_everything.json`

* `plos_introductions.json`

* `plos_data.json`

* `geonames_elastic_bulk.zip` - too big for gitub, [at dropbox](https://www.dropbox.com/s/8vcrt3g2d0pfw8l/geonames_elastic_bulk.zip?dl=0)

* `gbif_data.json`

* `gbif_geo.json`

* `gbif_geopoint.json`

* `gbif_geoshape.json`

* `gbif_geosmall.json`

* `shakespeare_data.json`

* `omdb.json`

## Loading into ES

These datasets are formatted to be ready for bulk loading into Elasticsearch

via the [bulk API](http://www.elasticsearch.org/guide/en/elasticsearch/reference/current/docs-bulk.html)

### geonames

`geonames_elastic_bulk.zip` is about 70 `.json` files in Elasticsearch bulk format. It was prepared from the [Geonames](http://www.geonames.org/) database at [http://download.geonames.org/export/dump/](http://download.geonames.org/export/dump/). The original data from Geonames was licensed under a Creative Commons Attribution 3.0 License, see [http://creativecommons.org/licenses/by/3.0/](http://creativecommons.org/licenses/by/3.0/).

To load the geonames data into Elasticsearch, do as you wish, but e.g., in R you could do:

First, create the index and set the `geo_shape` mapping

```r

body <- '{

 "mappings": {

   "record": {

     "properties": {

         "location" : {"type" : "geo_shape"}

      }

   }

 }

}'

index_create(index='geonames', body=body)

```

should return

```r

#> $acknowledged

#> [1] TRUE

```

Note: the index type is `record`, and the index name is `geonames`. The index and index type were set in the json files.

Then use a for loop to load in each file. AKAIK there is a limit on the file size you can load in (let me know if there's a way to get around it), so that's why theres a bunch of json files instead of one big file.

```r

devtools::install_github("ropensci/elastic")

library("elastic")

files <- list.files("path/to/unzipped/files")

for(i in seq_along(files)){

  invisible(

    docs_bulk(

      sprintf("path/geonames%s.json", files[i])

    )

  )

}

```

The `docs_bulk()` function uses the `/_bulk` endpoint to `POST` data to an index called `geonames` in your ES server. The output of the bulk load call prints info, that's why we use `invisible()` so you don't get thousands of lines printed.

Check that it worked:

```r

Search("geonames")$hits$total

#> [1] 6646030

```

You should have ~ 6.6 million records