How to read big json?

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执念已碎
执念已碎 2020-12-31 06:18

I receive json-files with data to be analyzed in R, for which I use the RJSONIO-package:

library(RJSONIO)
filename <- \"Indata.json\"
jFile <- fromJSON         


        
3条回答
  •  粉色の甜心
    2020-12-31 06:50

    Not on the memory size, but on the speed, for the quite small iris dataset (only 7088 bytes), the RJSONIO package is an order of magnitude slower than rjson. Don't use the method 'R' unless you really have to! Note the different units in the two sets of results.

    library(rjson) # library(RJSONIO)
    library(plyr)
    library(microbenchmark)
    x <- toJSON(iris)
    (op <- microbenchmark(CJ=toJSON(iris), RJ=toJSON(iris, method='R'),
      JC=fromJSON(x), JR=fromJSON(x, method='R') ) )
    
    # for rjson on this machine...
    Unit: microseconds
      expr        min          lq     median          uq        max
    1   CJ    491.470    496.5215    501.467    537.6295    561.437
    2   JC    242.079    249.8860    259.562    274.5550    325.885
    3   JR 167673.237 170963.4895 171784.270 172132.7540 190310.582
    4   RJ    912.666    925.3390    957.250   1014.2075   1153.494
    
    # for RJSONIO on the same machine...
    Unit: milliseconds
      expr      min       lq   median       uq      max
    1   CJ 7.338376 7.467097 7.563563 7.639456 8.591748
    2   JC 1.186369 1.234235 1.247235 1.265922 2.165260
    3   JR 1.196690 1.238406 1.259552 1.278455 2.325789
    4   RJ 7.353977 7.481313 7.586960 7.947347 9.364393
    

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