The `rsolr` package is an idiomatic R interface to Solr based on deferred evaluation. A Solr core is represented as a data frame or list that supports Solr-side filtering, sorting, transformation and aggregation, all through the familiar base R API. Queries are processed lazily, i.e., a query is only sent to the database when the data are required.
- Store, retrieve and compute on data with Solr, from R
- Use familiar R syntax and function names from the base R API, with some extensions
- Model data as either a
data.frameorlist, or use the low-level query API - Conveniently manipulate document collections after retrieval
- Autogenerate a Solr schema from a
data.frame - Experiment with the embedded Solr instance
- Extend to support additional/custom Solr features
This is inspired by some manipulations in the dplyr vignette.
Load the New York City 2013 flight data and upload to Solr:
library(nycflights13)
schema <- deriveSolrSchema(flights)
solr <- rsolr:::TestSolr(schema)
sr <- SolrFrame(solr$uri)
sr[] <- flights
Filtering:
subset(sr, month == 1 & day == 1)
head(sr, 10L)
Sorting:
sort(sr, by = ~ year + month + day)
Select fields:
subset(sr, select=c(year, month, day))
sr[c("year", "month", "day")]
sr[c("arr_*", "dep_*")] # Solr globs
Transform:
sr2 <- transform(sr,
gain = arr_delay - dep_delay,
speed = distance / air_time * 60)
sr2[c("gain", "speed")]
Aggregate:
unique(sr["tailnum"])
aggregate(~ tailnum, sr,
count = TRUE,
dist = mean(distance, na.rm=TRUE),
delay = mean(arr_delay, na.rm=TRUE))
Construct a SolrFrame using the URL to the existing core:
sr <- SolrFrame("http://my.host.com/solr/mycore")
Convert the SolrFrame to a data.frame, typically after some filtering or aggregation:
df <- as.data.frame(sr)