https://github.com/mdsumner/RGDALDB

See https://github.com/mdsumner/RGDALSQL (this was DBI for GDAL (and sf, after many patchy attempts)
https://github.com/mdsumner/RGDALDB

Last synced: 3 months ago
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See https://github.com/mdsumner/RGDALSQL (this was DBI for GDAL (and sf, after many patchy attempts)

• Host: GitHub
• URL: https://github.com/mdsumner/RGDALDB
• Owner: mdsumner
• Archived: true
• Created: 2018-09-11T16:01:47.000Z (about 6 years ago)
• Default Branch: master
• Last Pushed: 2019-10-14T01:30:30.000Z (about 5 years ago)
• Last Synced: 2024-05-21T02:13:02.421Z (6 months ago)
• Language: R
• Homepage:
• Size: 133 KB
• Stars: 7
• Watchers: 3
• Forks: 0
• Open Issues: 1
• Metadata Files:
  • Readme: README.Rmd
  • Code of conduct: CODE_OF_CONDUCT.md

Awesome Lists containing this project

README

        
---

output: github_document

editor_options: 

  chunk_output_type: console

---

```{r setup, include = FALSE}

knitr::opts_chunk$set(

  collapse = TRUE,

  comment = "#>",

  fig.path = "man/figures/README-",

  out.width = "100%"

)

```

# RGDALDB

The goal of RGDALDB is to provide a DBI wrapper for GDAL's `ExecuteSQL` in sf. 

## What's here?

A patchy work through of *building a DBI backend* for GDAL using sf. 

The core is `sf::st_read(, query = '')` in an unsupported branch of sf, it relies on **OGRSQL**, which is not a real database engine. 

https://www.gdal.org/ogr_sql.html

But, we should be able to make it useable using the DBI abstractions and support in dbplyr. 

These official guides to doing this have been partly implemented in this package: 

https://cran.r-project.org/web/packages/DBI/vignettes/backend.html

https://cran.r-project.org/web/packages/dbplyr/vignettes/new-backend.html

There is significant overlap in the support in sf to read from PostGIS, so that needs clarifying. 

## Installation

```R

remotes::install_cran("sf")

devtools::install_github("mdsumner/RGDALDB")

```

## Example

A pretty good example, ideally no data is read until `collect()` is called.

```{r example}

library(dplyr)

library(DBI)

library(RGDALDB)

con <- DBI::dbConnect(RGDALDB::GDALDB(), dsn = system.file("shape/nc.shp", package="sf"))

#con <- DBI::dbConnect(RGDALDB::GDALDB(), dsn = system.file("gpkg/nc.gpkg", package="sf"))

(nclazy <- tbl(con, "nc"))

library(sf)

nclazy %>% 

  dplyr::filter(AREA > .1) %>% 

  dplyr::select(AREA, PERIMETER, BIR74, FIPS) %>% 

  collect() %>%  ## consider making plot and collect methods for the tbl_GDALDBConnection

  st_as_sf() %>% 

  plot()

```

Rough and ready examples

```{r rough}

library(dplyr)

library(DBI)

con <- DBI::dbConnect(RGDALDB::GDALDB(), dsn = system.file("extdata/nc.gpkg", package= "RGDALDB"))

#DBI::dbWriteTable(con, "mtcars", mtcars)

tbl(con, "nc.gpkg")

tbl(con, "nc.gpkg") %>% filter(between(AREA, 0.05, 1))

# * summarise(), mutate(), filter() etc: powered by sql_select()

# * left_join(), inner_join(): powered by sql_join()

# * semi_join(), anti_join(): powered by sql_semi_join()

# * union(), intersect(), setdiff(): powered by sql_set_op()

## NO, because we expect sf not a data frame

##  tbl(con, "nc.gpkg") %>% filter(between(AREA, 0.05, 0.1)) %>% summarize(min(AREA)) 

tbl(con, "nc.gpkg") %>% filter(between(AREA, 0.05, 0.1)) %>% mutate(AREA = AREA * 2)

## this works, no sense until we have either multiple layers or control over the row_number

tbl(con, "nc.gpkg") %>% left_join(tbl(con, "nc.gpkg"), "CRESS_ID")

## FID is not working, need to wrap for row_number

#tbl(con, "nc.gpkg") %>% select(geom, AREA)  %>% mutate(ID =row_number())

```

---

  Please note that the 'RGDALDB' project is released with a

  [Contributor Code of Conduct](CODE_OF_CONDUCT.md).

  By contributing to this project, you agree to abide by its terms.