[![Project Status: Active – The project has reached a stable, usable state and is being actively developed.](https://www.repostatus.org/badges/latest/active.svg)](https://www.repostatus.org/#active) [![Signed by](https://img.shields.io/badge/Keybase-Verified-brightgreen.svg)](https://keybase.io/hrbrmstr) ![Signed commit %](https://img.shields.io/badge/Signed_Commits-100%25-lightgrey.svg) [![Linux build Status](https://travis-ci.org/hrbrmstr/ndjson.svg?branch=master)](https://travis-ci.org/hrbrmstr/ndjson) [![Coverage Status](https://codecov.io/gh/hrbrmstr/ndjson/branch/master/graph/badge.svg)](https://codecov.io/gh/hrbrmstr/ndjson) [![cran checks](https://cranchecks.info/badges/worst/ndjson)](https://cranchecks.info/pkgs/ndjson) [![CRAN status](https://www.r-pkg.org/badges/version/ndjson)](https://www.r-pkg.org/pkg/ndjson) ![Minimal R Version](https://img.shields.io/badge/R%3E%3D-3.2.0-blue.svg) ![License](https://img.shields.io/badge/License-MIT-blue.svg) # ndjson Wicked-Fast Streaming ‘JSON’ (‘ndjson’) Reader ## Description Streaming ‘JSON’ (‘ndjson’) has one ‘JSON’ record per-line and many modern ‘ndjson’ files contain large numbers of records. These constructs may not be columnar in nature, but it is often useful to read in these files and “flatten” the structure out to enable working with the data in an R ‘data.frame’-like context. Functions are provided that make it possible to read in plain ‘ndjson’ files or compressed (‘gz’) ‘ndjson’ files and either validate the format of the records or create “flat” ‘data.table’ structures from them. Pretty much an Rcpp/C++14 wrapper for The goal is to create a completely “flat” `data.frame`-like structure from ndjson records in plain text ndjson files or gzip’d ndjson files. ### Installation guidance for Linux/BSD-ish systems CRAN has binaries for Windows and macOS. To build this on UNIX-like systems, you need at least g++4.9 or clang++. This is a forced requirement by the ndjson library. The least painful way to do this is to install gcc \>= 4.9 (and you should install `ccache` while you’re at it) and mmodfiy `~/.R/Makevars` thusly: # Use whatever version of (g++ >=4.9 or clang++) that you downloaded VER=-4.9 CC=ccache gcc$(VER) CXX=ccache g++$(VER) SHLIB_CXXLD=g++$(VER) FC=ccache gfortran F77=ccache gfortran ## Why `ndjson` + Examples An example of such files are the output from Rapid7 internet-wide scans, such as their [HTTPS study](https://opendata.rapid7.com/sonar.https/). A gzip’d extract of 100,000 of one of those scans weighs in abt about 171MB. The records sometimes contain heavily nested JSON elements depending on how comprehensive the certificate data and other fields were. A typical record will look like this: { "vhost": "teamchat.buzzpoints.com", "host": "52.87.143.83", "certsubject": { "CN": "teamchat.buzzpoints.com" }, "ip": "52.87.143.83", "data": "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", "port": "443" } A `system.time(df <- stream_in("https-extract.json.gz"))` results in: ``` user system elapsed 14.822 0.224 15.189 ``` on a 13" MacBook Pro and produces: Classes ‘data.table’ and 'data.frame': 100000 obs. of 36 variables: $ certsubject.CN : chr "*.tio.ch" "*.starwoodhotels.com" "a.ssl.fastly.net" "a.ssl.fastly.net" ... $ data : chr "SFRUUC8xLjEgNDAzIEZvcmJpZGRlbg0KU2VydmVyOiBjbG91ZGZsYXJlLW5naW54DQpEYXRlOiBNb24sIDIyIEF1ZyAyMDE2IDE3OjE2OjE2IEdNVA0KQ29udGVudC1"| __truncated__ "SFRUUC8xLjAgNDAwIEJhZCBSZXF1ZXN0DQpTZXJ2ZXI6IEFrYW1haUdIb3N0DQpNaW1lLVZlcnNpb246IDEuMA0KQ29udGVudC1UeXBlOiB0ZXh0L2h0bWwNCkNvbnR"| __truncated__ "SFRUUC8xLjEgNTAwIERvbWFpbiBOb3QgRm91bmQNClNlcnZlcjogVmFybmlzaA0KUmV0cnktQWZ0ZXI6IDANCmNvbnRlbnQtdHlwZTogdGV4dC9odG1sDQpDYWNoZS1"| __truncated__ "SFRUUC8xLjEgNTAwIERvbWFpbiBOb3QgRm91bmQNClNlcnZlcjogVmFybmlzaA0KUmV0cnktQWZ0ZXI6IDANCmNvbnRlbnQtdHlwZTogdGV4dC9odG1sDQpDYWNoZS1"| __truncated__ ... $ host : chr "104.20.28.6" "104.80.186.186" "151.101.255.54" "151.101.158.15" ... $ ip : chr "104.20.28.6" "104.80.186.186" "151.101.255.54" "151.101.158.15" ... $ port : chr "443" "443" "443" "443" ... $ vhost : chr "104.20.28.6" "104.80.186.186" "a.ssl.fastly.net" "a.ssl.fastly.net" ... $ certsubject.C : chr NA "US" "US" "US" ... $ certsubject.L : chr NA "Stamford" "San Francisco" "San Francisco" ... $ certsubject.O : chr NA "STARWOOD HOTELS AND RESORTS WORLDWIDE, INC." "Fastly, Inc." "Fastly, Inc." ... $ certsubject.OU : chr NA "IT Solutions" NA NA ... $ certsubject.ST : chr NA "Connecticut" "California" "California" ... $ certsubject.emailAddress : chr NA NA NA NA ... $ certsubject.UNDEF : chr NA NA NA NA ... $ certsubject.businessCategory : chr NA NA NA NA ... $ certsubject.postalCode : chr NA NA NA NA ... $ certsubject.serialNumber : chr NA NA NA NA ... $ certsubject.street : chr NA NA NA NA ... $ certsubject.SN : chr NA NA NA NA ... $ certsubject.unstructuredName : chr NA NA NA NA ... $ certsubject.ITU-T : chr NA NA NA NA ... $ certsubject.GN : chr NA NA NA NA ... $ certsubject.description : chr NA NA NA NA ... $ certsubject.subjectAltName : chr NA NA NA NA ... $ certsubject.name : chr NA NA NA NA ... $ certsubject.DC : chr NA NA NA NA ... $ certsubject.postOfficeBox : chr NA NA NA NA ... $ certsubject.dnQualifier : chr NA NA NA NA ... $ certsubject.generationQualifier: chr NA NA NA NA ... $ certsubject.initials : chr NA NA NA NA ... $ certsubject.pseudonym : chr NA NA NA NA ... $ certsubject.title : chr NA NA NA NA ... $ certsubject : int NA NA NA NA NA NA NA NA NA NA ... $ certsubject.unstructuredAddress: chr NA NA NA NA ... $ certsubject.UID : chr NA NA NA NA ... $ certsubject.mail : chr NA NA NA NA ... $ certsubject.Mail : chr NA NA NA NA ... - attr(*, ".internal.selfref")= All of the certificate sub-field data elements have been expanded and we have a highly performant `data.table` to work with. Just go see what you have to do in `jsonlite` to get a similar output (and how long it will take). `pryr::object_size(df)` for that shows it’s consuming `394 MB`, which means we can read in many more extracts comfortably on a reasonably configured system and most (if not all) of it on a well-configured AWS box. However, if you do end up trying to work with that scan data, it’s highly recommended that you use `jq` to filter out the fields or records you want into a more compact ndjson file. ## What’s inside the tin? The following functions are implemented: - `stream_in`: Stream in ndjson from a file (handles `.gz` files) - `validate`: Validate JSON records in an ndjson file (handles `.gz` files) - `flatten`: Flatten a character vector of individual JSON lines There are no current plans for a `stream_out()` function since `jsonlite::stream_out()` does a great job tossing `data.frame`-like structures out to an ndjson file. ## What’s Inside The Tin The following functions are implemented: - `flatten`: Flatten a character vector of individual JSON lines into a data.table - `stream_in`: Stream in & flatten an ndjson file into a data.table - `validate`: Validate ndjson file ## Installation ``` r install.packages("ndjson", repos = "https://cinc.rud.is") # or remotes::install_git("https://git.rud.is/hrbrmstr/ndjson.git") # or remotes::install_git("https://git.sr.ht/~hrbrmstr/ndjson") # or remotes::install_gitlab("hrbrmstr/ndjson") # or remotes::install_bitbucket("hrbrmstr/ndjson") # or remotes::install_github("hrbrmstr/ndjson") ``` NOTE: To use the ‘remotes’ install options you will need to have the [{remotes} package](https://github.com/r-lib/remotes) installed. ## Usage ``` r library(ndjson) # current version packageVersion("ndjson") ## [1] '0.8.0.9000' ``` ## Usage ``` r library(microbenchmark) flatten('{"top":{"next":{"final":1,"end":true},"another":"yes"},"more":"no"}') ## more top.another top.next.end top.next.final ## 1: no yes TRUE 1 f <- system.file("extdata", "test.json", package="ndjson") gzf <- system.file("extdata", "testgz.json.gz", package="ndjson") dplyr::glimpse(ndjson::stream_in(f)) ## Observations: 100 ## Variables: 8 ## $ args NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,… ## $ headers.Accept "*/*", "*/*", "*/*", "*/*", "*/*", "*/*", "*/*", "*/*", "*/*", "*/*", "*/*", "*/*",… ## $ `headers.Accept-Encoding` "identity", "identity", "identity", "identity", "identity", "identity", "identity",… ## $ headers.Host "httpbin.org", "httpbin.org", "httpbin.org", "httpbin.org", "httpbin.org", "httpbin… ## $ `headers.User-Agent` "Wget/1.18 (darwin15.5.0)", "Wget/1.18 (darwin15.5.0)", "Wget/1.18 (darwin15.5.0)",… ## $ id 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 2… ## $ origin "50.252.233.22", "50.252.233.22", "50.252.233.22", "50.252.233.22", "50.252.233.22"… ## $ url "http://httpbin.org/stream/100", "http://httpbin.org/stream/100", "http://httpbin.o… dplyr::glimpse(ndjson::stream_in(gzf)) ## Observations: 100 ## Variables: 8 ## $ args NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,… ## $ headers.Accept "*/*", "*/*", "*/*", "*/*", "*/*", "*/*", "*/*", "*/*", "*/*", "*/*", "*/*", "*/*",… ## $ `headers.Accept-Encoding` "identity", "identity", "identity", "identity", "identity", "identity", "identity",… ## $ headers.Host "httpbin.org", "httpbin.org", "httpbin.org", "httpbin.org", "httpbin.org", "httpbin… ## $ `headers.User-Agent` "Wget/1.18 (darwin15.5.0)", "Wget/1.18 (darwin15.5.0)", "Wget/1.18 (darwin15.5.0)",… ## $ id 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 2… ## $ origin "50.252.233.22", "50.252.233.22", "50.252.233.22", "50.252.233.22", "50.252.233.22"… ## $ url "http://httpbin.org/stream/100", "http://httpbin.org/stream/100", "http://httpbin.o… dplyr::glimpse(jsonlite::stream_in(file(f), flatten=TRUE, verbose=FALSE)) ## Observations: 100 ## Variables: 7 ## $ url "http://httpbin.org/stream/100", "http://httpbin.org/stream/100", "http://httpbin.o… ## $ id 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 2… ## $ origin "50.252.233.22", "50.252.233.22", "50.252.233.22", "50.252.233.22", "50.252.233.22"… ## $ headers.Host "httpbin.org", "httpbin.org", "httpbin.org", "httpbin.org", "httpbin.org", "httpbin… ## $ `headers.Accept-Encoding` "identity", "identity", "identity", "identity", "identity", "identity", "identity",… ## $ headers.Accept "*/*", "*/*", "*/*", "*/*", "*/*", "*/*", "*/*", "*/*", "*/*", "*/*", "*/*", "*/*",… ## $ `headers.User-Agent` "Wget/1.18 (darwin15.5.0)", "Wget/1.18 (darwin15.5.0)", "Wget/1.18 (darwin15.5.0)",… dplyr::glimpse(jsonlite::stream_in(gzfile(gzf), flatten=TRUE, verbose=FALSE)) ## Observations: 100 ## Variables: 7 ## $ url "http://httpbin.org/stream/100", "http://httpbin.org/stream/100", "http://httpbin.o… ## $ id 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 2… ## $ origin "50.252.233.22", "50.252.233.22", "50.252.233.22", "50.252.233.22", "50.252.233.22"… ## $ headers.Host "httpbin.org", "httpbin.org", "httpbin.org", "httpbin.org", "httpbin.org", "httpbin… ## $ `headers.Accept-Encoding` "identity", "identity", "identity", "identity", "identity", "identity", "identity",… ## $ headers.Accept "*/*", "*/*", "*/*", "*/*", "*/*", "*/*", "*/*", "*/*", "*/*", "*/*", "*/*", "*/*",… ## $ `headers.User-Agent` "Wget/1.18 (darwin15.5.0)", "Wget/1.18 (darwin15.5.0)", "Wget/1.18 (darwin15.5.0)",… microbenchmark( ndjson = { ndjson::stream_in(f) }, jsonlite = { jsonlite::stream_in(file(f), flatten=TRUE, verbose=FALSE) } ) ## Unit: milliseconds ## expr min lq mean median uq max neval cld ## ndjson 2.435400 2.508409 2.607311 2.554602 2.611543 6.070535 100 a ## jsonlite 4.177671 4.392665 4.530934 4.555521 4.656247 5.029599 100 b microbenchmark( ndjson = { ndjson::stream_in(gzf) }, jsonlite = { jsonlite::stream_in(gzfile(gzf), flatten=TRUE, verbose=FALSE) } ) ## Unit: milliseconds ## expr min lq mean median uq max neval cld ## ndjson 2.208561 2.313191 2.371382 2.370058 2.422588 2.622296 100 a ## jsonlite 3.417319 3.576970 3.685897 3.664169 3.816465 4.258603 100 b ``` ## ndjson Metrics | Lang | \# Files | (%) | LoC | (%) | Blank lines | (%) | \# Lines | (%) | | :----------- | -------: | ---: | --: | ---: | ----------: | ---: | -------: | ---: | | C++ | 3 | 0.33 | 338 | 0.74 | 105 | 0.62 | 55 | 0.21 | | C/C++ Header | 1 | 0.11 | 66 | 0.14 | 15 | 0.09 | 40 | 0.16 | | R | 4 | 0.44 | 28 | 0.06 | 6 | 0.04 | 57 | 0.22 | | Rmd | 1 | 0.11 | 24 | 0.05 | 43 | 0.25 | 104 | 0.41 | ## Code of Conduct Please note that this project is released with a Contributor Code of Conduct. 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