https://github.com/privefl/bigreadr

R package to read large text files based on splitting + data.table::fread
https://github.com/privefl/bigreadr

large-dataset r-package read-csv

Last synced: 20 days ago
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R package to read large text files based on splitting + data.table::fread

• Host: GitHub
• URL: https://github.com/privefl/bigreadr
• Owner: privefl
• Created: 2018-07-22T20:44:47.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2022-12-06T14:47:23.000Z (about 2 years ago)
• Last Synced: 2024-10-28T17:24:20.175Z (about 1 month ago)
• Topics: large-dataset, r-package, read-csv
• Language: R
• Homepage: https://privefl.github.io/bigreadr/
• Size: 270 KB
• Stars: 42
• Watchers: 5
• Forks: 5
• Open Issues: 1
• Metadata Files:
  • Readme: README.md

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• jimsghstars - privefl/bigreadr - R package to read large text files based on splitting + data.table::fread (R)

README

        

[![R-CMD-check](https://github.com/privefl/bigreadr/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/privefl/bigreadr/actions/workflows/R-CMD-check.yaml)

[![CRAN status](https://www.r-pkg.org/badges/version/bigreadr)](https://cran.r-project.org/package=bigreadr)

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# R package {bigreadr}

Read large text files based on splitting + `data.table::fread`

## Example

```r

# remotes::install_github("privefl/bigreadr")

library(bigreadr)

# Create a temporary file of ~141 MB (just as an example)

csv <- fwrite2(iris[rep(seq_len(nrow(iris)), 1e4), rep(1:5, 4)], tempfile())

format(file.size(csv), big.mark = ",")

## Splitting lines (1)

# Read (by parts) all data -> using `fread` would be faster

nlines(csv)  ## 1M5 lines -> split every 500,000

big_iris1 <- big_fread1(csv, every_nlines = 5e5)

# Read and subset (by parts)

big_iris1_setosa <- big_fread1(csv, every_nlines = 5e5, .transform = function(df) {

  dplyr::filter(df, Species == "setosa")

})

## Splitting columns (2)

big_iris2 <- big_fread2(csv, nb_parts = 3)

# Read and subset (by parts)

species_setosa <- (fread2(csv, select = 5)[[1]] == "setosa")

big_iris2_setosa <- big_fread2(csv, nb_parts = 3, .transform = function(df) {

  dplyr::filter(df, species_setosa)

})

## Verification

identical(big_iris1_setosa, dplyr::filter(big_iris1, Species == "setosa"))

identical(big_iris2, big_iris1)

identical(big_iris2_setosa, big_iris1_setosa)

```

## Use cases

Please send me your use cases!

- [Convert a CSV to SQLite by parts](https://privefl.github.io/bigreadr/articles/csv2sqlite.html)

- [Read a text file as a disk.frame](https://diskframe.com/articles/ingesting-data.html)

- [Read a text file as a Filebacked Big Matrix](https://privefl.github.io/bigstatsr/reference/big_read.html)

- [Read a text file as a Filebacked Data Frame](https://privefl.github.io/bigdfr/reference/FDF_read.html)

- Read multiple files at once using `bigreadr::fread2()`.