This package has been rebooted as solrium - check out the tutorial at https://ropensci.org/tutorials/solrium_tutorial.html
## Installation
More stable version from CRAN
```r
install.packages("solr")
```
Development version from Github
```r
if (!require("devtools")) install.packages("devtools")
devtools::install_github("ropensci/solr")
```
Load
```r
library("solr")
```
## Usage
The `solr` package is a general purpose R interface to [Solr](http://lucene.apache.org/solr/)
This package only deals with exracting data from a Solr endpoint, not writing data (pull request or holla if you're interested in writing solr data).
### Solr info
+ [Solr home page](http://lucene.apache.org/solr/)
+ [Highlighting help](http://wiki.apache.org/solr/HighlightingParameters)
+ [Faceting help](http://wiki.apache.org/solr/SimpleFacetParameters)
+ [Installing Solr on Mac using homebrew](http://ramlev.dk/blog/2012/06/02/install-apache-solr-on-your-mac/)
+ [Install and Setup SOLR in OSX, including running Solr](http://risnandar.wordpress.com/2013/09/08/how-to-install-and-setup-apache-lucene-solr-in-osx/)
### Quick start
**Define stuff** Your base url and a key (if needed). This example should work. You do need to pass a key to the Public Library of Science search API, but it apparently doesn't need to be a real one.
```r
url <- 'http://api.plos.org/search'
key <- 'key'
```
**Search**
```r
solr_search(q='*:*', rows=2, fl='id', base=url, key=key)
```
```
#> id
#> 1 10.1371/journal.pone.0107420
#> 2 10.1371/journal.pone.0107420/title
```
**Facet**
```r
solr_facet(q='*:*', facet.field='journal', facet.query=c('cell','bird'), base=url, key=key)
```
```
#> $facet_queries
#> term value
#> 1 cell 133052
#> 2 bird 13598
#>
#> $facet_fields
#> $facet_fields$journal
#> X1 X2
#> 1 plos one 1285831
#> 2 plos genetics 50706
#> 3 plos pathogens 44134
#> 4 plos computational biology 37646
#> 5 plos neglected tropical diseases 35979
#> 6 plos biology 29392
#> 7 plos medicine 20335
#> 8 plos clinical trials 521
#> 9 plos medicin 9
#>
#>
#> $facet_dates
#> NULL
#>
#> $facet_ranges
#> NULL
```
**Highlight**
```r
solr_highlight(q='alcohol', hl.fl = 'abstract', rows=2, base = url, key=key)
```
```
#> $`10.1371/journal.pmed.0040151`
#> $`10.1371/journal.pmed.0040151`$abstract
#> [1] "Background: Alcohol consumption causes an estimated 4% of the global disease burden, prompting"
#>
#>
#> $`10.1371/journal.pone.0027752`
#> $`10.1371/journal.pone.0027752`$abstract
#> [1] "Background: The negative influences of alcohol on TB management with regard to delays in seeking"
```
**Stats**
```r
out <- solr_stats(q='ecology', stats.field=c('counter_total_all','alm_twitterCount'), stats.facet=c('journal','volume'), base=url, key=key)
```
```r
out$data
```
```
#> min max count missing sum sumOfSquares
#> counter_total_all 0 381005 32852 0 149031058 3.400519e+12
#> alm_twitterCount 0 1763 32852 0 185772 3.565201e+07
#> mean stddev
#> counter_total_all 4536.437903 9106.78332
#> alm_twitterCount 5.654816 32.45437
```
```r
out$facet
```
```
#> $counter_total_all
#> $counter_total_all$volume
#> min max count missing sum sumOfSquares mean stddev
#> 1 0 171524 2103 0 3835629 70357145667 1823.884 5490.299
#> 2 0 110768 167 0 1230491 27037286881 7368.210 10404.694
#> 3 2148 75942 72 0 772327 16099354117 10726.764 10491.301
#> 4 1054 17107 34 0 200231 1660929909 5889.147 3820.757
#> 5 1894 187549 81 0 1537428 91933035658 18980.593 28007.084
#> 6 1715 120974 482 0 5948960 169424242112 12342.241 14127.482
#> 7 1366 129059 741 0 7868119 195614871613 10618.244 12306.297
#> 8 704 366145 1010 0 9896935 353256010661 9798.946 15937.082
#> 9 103 120116 1539 0 12404305 231308647989 8059.977 9240.685
#> 10 72 253313 2948 0 18225649 347627981895 6182.378 8928.896
#> 11 51 184534 4825 0 25034662 405690249482 5188.531 7561.209
#> 12 17 381005 6360 0 27474658 569252540142 4319.915 8417.517
#> 13 42 308057 6620 0 22228580 679102577074 3357.792 9556.281
#> 14 0 190562 5870 0 12373084 242153753584 2107.851 6067.619
#> facet_field
#> 1 11
#> 2 12
#> 3 13
#> 4 14
#> 5 1
#> 6 2
#> 7 3
#> 8 4
#> 9 5
#> 10 6
#> 11 7
#> 12 8
#> 13 9
#> 14 10
#>
#> $counter_total_all$journal
#> min max count missing sum sumOfSquares mean stddev
#> 1 704 120974 246 0 4214716 1.564771e+11 17132.992 18545.739
#> 2 1054 276407 909 0 14517422 5.853448e+11 15970.761 19730.857
#> 3 8518 13973 2 0 22491 2.678011e+08 11245.500 3857.267
#> 4 0 381005 27131 0 101671435 2.102781e+12 3747.427 7966.421
#> 5 1219 65875 609 0 4973930 7.003314e+10 8167.373 6954.883
#> 6 475 80210 779 0 6583271 9.726579e+10 8450.926 7315.077
#> 7 0 216948 1318 0 6245038 1.075082e+11 4738.269 7691.744
#> 8 0 303724 607 0 4418575 1.542870e+11 7279.366 14195.857
#> facet_field
#> 1 plos medicine
#> 2 plos biology
#> 3 plos clinical trials
#> 4 plos one
#> 5 plos pathogens
#> 6 plos genetics
#> 7 plos neglected tropical diseases
#> 8 plos computational biology
#>
#>
#> $alm_twitterCount
#> $alm_twitterCount$volume
#> min max count missing sum sumOfSquares mean stddev
#> 1 0 1763 2103 0 22076 4662064 10.4973847 45.909374
#> 2 0 1133 167 0 7738 2167192 46.3353293 104.381403
#> 3 0 360 72 0 3852 638160 53.5000000 78.010292
#> 4 0 368 34 0 3138 609804 92.2941176 98.501663
#> 5 0 42 81 0 177 5001 2.1851852 7.594589
#> 6 0 108 482 0 783 32997 1.6244813 8.121355
#> 7 0 49 741 0 714 12896 0.9635628 4.061689
#> 8 0 242 1010 0 1091 78313 1.0801980 8.743368
#> 9 0 129 1539 0 1985 96697 1.2897986 7.823506
#> 10 0 892 2948 0 4462 1290514 1.5135685 20.871417
#> 11 0 822 4825 0 19805 2066673 4.1046632 20.287017
#> 12 0 1561 6360 0 36483 6845473 5.7363208 32.304658
#> 13 0 1581 6620 0 50448 13527984 7.6205438 44.561524
#> 14 0 943 5870 0 33020 3618240 5.6252129 24.183710
#> facet_field
#> 1 11
#> 2 12
#> 3 13
#> 4 14
#> 5 1
#> 6 2
#> 7 3
#> 8 4
#> 9 5
#> 10 6
#> 11 7
#> 12 8
#> 13 9
#> 14 10
#>
#> $alm_twitterCount$journal
#> min max count missing sum sumOfSquares mean stddev
#> 1 0 784 246 0 4375 1044519 17.784553 62.81530
#> 2 0 1763 909 0 19658 7025376 21.625963 85.25844
#> 3 0 3 2 0 3 9 1.500000 2.12132
#> 4 0 1581 27131 0 135040 25380518 4.977332 30.17847
#> 5 0 133 609 0 4496 170710 7.382594 15.03930
#> 6 0 181 779 0 4835 181223 6.206675 13.94138
#> 7 0 892 1318 0 5848 1122858 4.437026 28.85976
#> 8 0 289 607 0 4643 296565 7.649094 20.75514
#> facet_field
#> 1 plos medicine
#> 2 plos biology
#> 3 plos clinical trials
#> 4 plos one
#> 5 plos pathogens
#> 6 plos genetics
#> 7 plos neglected tropical diseases
#> 8 plos computational biology
```
**More like this**
`solr_mlt` is a function to return similar documents to the one
```r
out <- solr_mlt(q='title:"ecology" AND body:"cell"', mlt.fl='title', mlt.mindf=1, mlt.mintf=1, fl='counter_total_all', rows=5, base=url, key=key)
out$docs
```
```
#> id counter_total_all
#> 1 10.1371/journal.pbio.1001805 17665
#> 2 10.1371/journal.pbio.0020440 24041
#> 3 10.1371/journal.pone.0087217 6336
#> 4 10.1371/journal.pbio.1002191 14565
#> 5 10.1371/journal.pone.0040117 4613
```
```r
out$mlt
```
```
#> $`10.1371/journal.pbio.1001805`
#> id counter_total_all
#> 1 10.1371/journal.pone.0082578 2270
#> 2 10.1371/journal.pone.0098876 2603
#> 3 10.1371/journal.pone.0102159 1244
#> 4 10.1371/journal.pcbi.1003408 7336
#> 5 10.1371/journal.pone.0076063 2971
#>
#> $`10.1371/journal.pbio.0020440`
#> id counter_total_all
#> 1 10.1371/journal.pone.0035964 5920
#> 2 10.1371/journal.pone.0102679 3340
#> 3 10.1371/journal.pone.0003259 2882
#> 4 10.1371/journal.pone.0101568 2823
#> 5 10.1371/journal.pntd.0003377 3507
#>
#> $`10.1371/journal.pone.0087217`
#> id counter_total_all
#> 1 10.1371/journal.pone.0131665 522
#> 2 10.1371/journal.pcbi.0020092 20087
#> 3 10.1371/journal.pone.0133941 595
#> 4 10.1371/journal.pone.0123774 1095
#> 5 10.1371/journal.pone.0140306 370
#>
#> $`10.1371/journal.pbio.1002191`
#> id counter_total_all
#> 1 10.1371/journal.pbio.1002232 2148
#> 2 10.1371/journal.pone.0131700 1121
#> 3 10.1371/journal.pone.0070448 1669
#> 4 10.1371/journal.pone.0044766 2349
#> 5 10.1371/journal.pone.0062824 2732
#>
#> $`10.1371/journal.pone.0040117`
#> id counter_total_all
#> 1 10.1371/journal.pone.0069352 2940
#> 2 10.1371/journal.pone.0148280 710
#> 3 10.1371/journal.pone.0014065 5915
#> 4 10.1371/journal.pone.0035502 4139
#> 5 10.1371/journal.pone.0078369 3548
```
**Parsing**
`solr_parse` is a general purpose parser function with extension methods `solr_parse.sr_search`, `solr_parse.sr_facet`, and `solr_parse.sr_high`, for parsing `solr_search`, `solr_facet`, and `solr_highlight` function output, respectively. `solr_parse` is used internally within those three functions (`solr_search`, `solr_facet`, `solr_highlight`) to do parsing. You can optionally get back raw `json` or `xml` from `solr_search`, `solr_facet`, and `solr_highlight` setting parameter `raw=TRUE`, and then parsing after the fact with `solr_parse`. All you need to know is `solr_parse` can parse
For example:
```r
(out <- solr_highlight(q='alcohol', hl.fl = 'abstract', rows=2, base = url, key=key, raw=TRUE))
```
```
#> [1] "{\"response\":{\"numFound\":21115,\"start\":0,\"docs\":[{},{}]},\"highlighting\":{\"10.1371/journal.pmed.0040151\":{\"abstract\":[\"Background: Alcohol consumption causes an estimated 4% of the global disease burden, prompting\"]},\"10.1371/journal.pone.0027752\":{\"abstract\":[\"Background: The negative influences of alcohol on TB management with regard to delays in seeking\"]}}}\n"
#> attr(,"class")
#> [1] "sr_high"
#> attr(,"wt")
#> [1] "json"
```
Then parse
```r
solr_parse(out, 'df')
```
```
#> names
#> 1 10.1371/journal.pmed.0040151
#> 2 10.1371/journal.pone.0027752
#> abstract
#> 1 Background: Alcohol consumption causes an estimated 4% of the global disease burden, prompting
#> 2 Background: The negative influences of alcohol on TB management with regard to delays in seeking
```
**Using specific data sources**
*USGS BISON service*
The occurrences service
```r
url <- "http://bisonapi.usgs.ornl.gov/solr/occurrences/select"
solr_search(q='*:*', fl=c('decimalLatitude','decimalLongitude','scientificName'), base=url)
```
```
#> decimalLongitude decimalLatitude scientificName
#> 1 -98.2376 29.5502 Nyctanassa violacea
#> 2 -98.2376 29.5502 Myiarchus cinerascens
#> 3 -98.2376 29.5502 Melanerpes aurifrons
#> 4 -98.2376 29.5502 Melanerpes aurifrons
#> 5 -98.2376 29.5502 Mimus polyglottos
#> 6 -98.2376 29.5502 Molothrus ater
#> 7 -98.2376 29.5502 Mimus polyglottos
#> 8 -98.2376 29.5502 Oreothlypis celata
#> 9 -98.2376 29.5502 Megaceryle alcyon
#> 10 -98.2376 29.5502 Molothrus ater
```
The species names service
```r
url <- "http://bisonapi.usgs.ornl.gov/solr/scientificName/select"
out <- solr_search(q='*:*', base=url, raw=TRUE)
solr_parse(out, "list")$response$docs[1:3]
```
```
#> [[1]]
#> [[1]]$scientificName
#> [1] "Catocala editha"
#>
#> [[1]]$`_version_`
#> [1] 1.518645e+18
#>
#>
#> [[2]]
#> [[2]]$scientificName
#> [1] "Dictyopteris polypodioides"
#>
#> [[2]]$`_version_`
#> [1] 1.518645e+18
#>
#>
#> [[3]]
#> [[3]]$scientificName
#> [1] "Lonicera iberica"
#>
#> [[3]]$`_version_`
#> [1] 1.518645e+18
```
Sweet! Love me some `solr`
## Citing
To cite `solr` in publications use:
> Scott Chamberlain (2016). solr: General purpose R interface to Solr. R package version 0.1.6. http://CRAN.R-project.org/package=solr
## License and bugs
* License: [MIT](http://opensource.org/licenses/MIT)
* Report bugs at [our Github repo for solr](https://github.com/solr/rgauges/issues?state=open)
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