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Building a JSON webservice in R

R is a programming language for mathematics and statistics. There are several R libraries available to support web development, including rjson and RJSONIO (note case – R library names are case sensitive). RJSONIO is based on rjson, but with modifications to improve performance working with large JSON payloads.

The example below returns the data required to render a scatter chart with a best fit line like this:

Chart in R-Studio

This requires that you’ve already set up rApache. To install RJSONIO, check http://cran.r-project.org/src/contrib/ to find the latest version, and use that filename in the following. It appears that CRAN removes the old versions- unfortunately they don’t have an easy way to just pull the latest.

wget http://cran.r-project.org/src/contrib/RJSONIO_1.0-1.tar.gz
R CMD INSTALL RJSONIO_1.0-1.tar.gz

The following code will pull JSON data from the URL, parse it, and return a linear model. This includes information for the graph, error bars, best fit line, axis intercepts, etc. For a charting package like ExtJS, the data may need to be re-formatted to render successfully, which fortunately R is quite good at.

setContentType("application/json")
 
library(RJSONIO)
library(utils)
 
cat(GET$data)
 
json <- fromJSON(URLdecode(GET$data))
fit <- lm(x ~ y)
 
cat(toJSON(fit))

Strictly speaking, this should be a POST, but this makes the example easier to read.

Some examples of this use the basicJSONHandler, like below. I found that this does not return numerics for JSON arrays, and opted not to use it.

h = basicJSONHandler()
x = fromJSON("[1, 2, 3]", h)

If you’ve read this far, you may enjoy my review of the R Cookbook.

This URL accepts and returns JSON results:
http://localhost:8081/R/fit.R?data={%22x%22:[1.5,2,7,8,15],%22y%22:[1.5,2,7,8,15]}

Results:

{ "assign" : [ 0,
      1
    ],
  "call" : { "" : "lm",
      "formula" : [ "~",
          "x",
          "y"
        ]
    },
  "coefficients" : { "(Intercept)" : 0.95408999999999999,
      "y" : 0.78297000000000005
    },
  "df.residual" : 3,
  "effects" : { "" : 0.23488999999999999,
      "(Intercept)" : -13.864000000000001,
      "y" : 8.5699000000000005
    },
  "fitted.values" : { "1" : 2.1284999999999998,
      "2" : 2.52,
      "3" : 6.4348999999999998,
      "4" : 7.2179000000000002,
      "5" : 12.699
    },
  "model" : { "x" : [ 1,
          3,
          6,
          9,
          12
        ],
      "y" : [ 1.5,
          2,
          7,
          8,
          15
        ]
    },
  "qr" : { "pivot" : [ 1,
          2
        ],
      "qr" : [ { "(Intercept)" : -2.2361,
            "y" : -14.981999999999999
          },
          { "(Intercept)" : 0.44721,
            "y" : 10.945
          },
          { "(Intercept)" : 0.44721,
            "y" : -0.17422000000000001
          },
          { "(Intercept)" : 0.44721,
            "y" : -0.26557999999999998
          },
          { "(Intercept)" : 0.44721,
            "y" : -0.90512999999999999
          }
        ],
      "qraux" : [ 1.4472,
          1.2826
        ],
      "rank" : 2,
      "tol" : 9.9999999999999995e-08
    },
  "rank" : 2,
  "residuals" : { "1" : -1.1285000000000001,
      "2" : 0.47997000000000001,
      "3" : -0.43489,
      "4" : 1.7821,
      "5" : -0.69865999999999995
    },
  "terms" : [ "~",
      "x",
      "y"
    ],
  "xlevels" : {  }
}

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2 replies
  1. dickoa
    dickoa says:

    Cool post, just want to add that RJSONIO is not based on rjson or the opposite.
    These two packages are independent.

    Reply
  2. Jaehyeon
    Jaehyeon says:

    This is for those who want to have a comparion of API development with R – plumber, Rserve and rApache.

    Basically concurrent requests are queued by httpuv in plumber so that it is not performant by itself. The author recommends multiple docker containers but it can be complicated as well as response-demanding.

    There are other tech eg Rserve and rApache. Rserve forks prosesses and it is possible to configure rApache to pre-fork so as to handle concurrent requests.

    See the following posts for comparison

    https://www.linkedin.com/pulse/api-development-r-part-i-jaehyeon-kim/
    https://www.linkedin.com/pulse/api-development-r-part-ii-jaehyeon-kim/

    Reply

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