R interface to InfluxDB
# influxdbr is available on CRAN:
install.packages("influxdbr")# Install the development version from GitHub:
if (!require(devtools)) {
install.packages('devtools')
}
devtools::install_github("dleutnant/influxdbr@dev", quiet = TRUE)# load libs
library(xts)## Loading required package: zoo
##
## Attaching package: 'zoo'
## The following objects are masked from 'package:base':
##
## as.Date, as.Date.numericlibrary(influxdbr)# attach data "sample_matrix"
data("sample_matrix")
# create xts object
xts_data <- xts::as.xts(x = sample_matrix)
# assign some attributes
xts::xtsAttributes(xts_data) <- list(info = "SampleDataMatrix",
UnitTesting = TRUE,
n = 180)
str(xts_data)## An 'xts' object on 2007-01-02/2007-06-30 containing:
## Data: num [1:180, 1:4] 50 50.2 50.4 50.4 50.2 ...
## - attr(*, "dimnames")=List of 2
## ..$ : NULL
## ..$ : chr [1:4] "Open" "High" "Low" "Close"
## Indexed by objects of class: [POSIXct,POSIXt] TZ:
## xts Attributes:
## List of 3
## $ info : chr "SampleDataMatrix"
## $ UnitTesting: logi TRUE
## $ n : num 180# create connection object
# (here: based on a config file with (s. package documentation))
con <- influxdbr::influx_connection(group = "admin")## Success: (204) No Content# create new database
influxdbr::create_database(con = con, db = "mydb")
# list all databases
influxdbr::show_databases(con = con)## # A tibble: 11 x 1
## name
## <chr>
## 1 _internal
## 2 stbmod
## 3 wasig
## 4 wasig-fr
## 5 wasig-h
## 6 tmp2
## 7 tmp3
## 8 tmp
## 9 test
## 10 new_db
## 11 mydb# write example xts-object to database
# attributes of the xts object are interpreted as InfluxDB tags (keys and values)
# colnames of the xts object are interpreted as InfluxDB fields (keys and values)
influxdbr::influx_write(con = con,
db = "mydb",
xts = xts_data,
measurement = "sampledata")# check if measurement was succefully written
influxdbr::show_measurements(con = con, db = "mydb")## # A tibble: 1 x 1
## name
## <chr>
## 1 sampledata# return tibble
# fetch time series data by using the helper function `influx_select`
result <- influx_select(con = con,
db = "mydb",
field_keys = "Open, High",
measurement = "sampledata",
group_by = "*",
limit = 10,
order_desc = TRUE,
return_xts = FALSE)
result## [[1]]
## # A tibble: 10 x 9
## statement_id series_names series_partial UnitTesting info
## <int> <chr> <lgl> <chr> <chr>
## 1 0 sampledata FALSE TRUE SampleDataMatrix
## 2 0 sampledata FALSE TRUE SampleDataMatrix
## 3 0 sampledata FALSE TRUE SampleDataMatrix
## 4 0 sampledata FALSE TRUE SampleDataMatrix
## 5 0 sampledata FALSE TRUE SampleDataMatrix
## 6 0 sampledata FALSE TRUE SampleDataMatrix
## 7 0 sampledata FALSE TRUE SampleDataMatrix
## 8 0 sampledata FALSE TRUE SampleDataMatrix
## 9 0 sampledata FALSE TRUE SampleDataMatrix
## 10 0 sampledata FALSE TRUE SampleDataMatrix
## # ... with 4 more variables: n <chr>, time <dttm>, Open <dbl>, High <dbl># return xts object
# fetch time series data by using the helper function `influx_select`
result <- influx_select(con = con,
db = "mydb",
field_keys = "Open, High",
measurement = "sampledata",
group_by = "*",
limit = 10,
order_desc = TRUE,
return_xts = TRUE)
# InfluxDB tags are now xts attributes.
# Because xts objects are basically matrices (which can store one data type only),
# a single xts object is created for each InfluxDB field.
# This ensures a correct representation of the field values data type (instead of getting all into a "character" matrix).
str(result)## List of 1
## $ :List of 2
## ..$ sampledata:An 'xts' object on 2007-06-20 22:00:00/2007-06-29 22:00:00 containing:
## Data: num [1:10, 1] 47.7 47.6 47.2 47.2 47.2 ...
## - attr(*, "dimnames")=List of 2
## ..$ : NULL
## ..$ : chr "Open"
## Indexed by objects of class: [POSIXct,POSIXt] TZ: GMT
## xts Attributes:
## List of 6
## .. ..$ statement_id : int 0
## .. ..$ series_names : chr "sampledata"
## .. ..$ series_partial: logi FALSE
## .. ..$ UnitTesting : chr "TRUE"
## .. ..$ info : chr "SampleDataMatrix"
## .. ..$ n : chr "180"
## ..$ sampledata:An 'xts' object on 2007-06-20 22:00:00/2007-06-29 22:00:00 containing:
## Data: num [1:10, 1] 47.7 47.6 47.2 47.3 47.4 ...
## - attr(*, "dimnames")=List of 2
## ..$ : NULL
## ..$ : chr "High"
## Indexed by objects of class: [POSIXct,POSIXt] TZ: GMT
## xts Attributes:
## List of 6
## .. ..$ statement_id : int 0
## .. ..$ series_names : chr "sampledata"
## .. ..$ series_partial: logi FALSE
## .. ..$ UnitTesting : chr "TRUE"
## .. ..$ info : chr "SampleDataMatrix"
## .. ..$ n : chr "180"# In case the InfluxDB response is expected to be a single series only,
# we can flatten the list ('simplifyList = TRUE') to directly get to the data.
# This enhances a pipeable work flow.
# fetch time series data by using the helper function `influx_select`
result <- influx_select(con = con,
db = "mydb",
field_keys = "Open",
measurement = "sampledata",
group_by = "*",
limit = 10,
order_desc = TRUE,
return_xts = TRUE,
simplifyList = TRUE)
str(result)## An 'xts' object on 2007-06-20 22:00:00/2007-06-29 22:00:00 containing:
## Data: num [1:10, 1] 47.7 47.6 47.2 47.2 47.2 ...
## - attr(*, "dimnames")=List of 2
## ..$ : NULL
## ..$ : chr "Open"
## Indexed by objects of class: [POSIXct,POSIXt] TZ: GMT
## xts Attributes:
## List of 6
## $ statement_id : int 0
## $ series_names : chr "sampledata"
## $ series_partial: logi FALSE
## $ UnitTesting : chr "TRUE"
## $ info : chr "SampleDataMatrix"
## $ n : chr "180"