'InfluxDB' 2.x Client.
influxdb-client-r
This repository contains R package for InfluxDB 2.0 client.
Features
The InfluxDB 2.0 client supports:
- Querying data
- Writing data
- Getting status
Documentation
This section contains links to the client library documentation.
Installing
The package requires R >= 3.4.
Installing dependencies
install.packages(c("httr", "bit64", "nanotime", "plyr"))
Installing influxdbclient
package
The package is published on CRAN and can be installed with
install.packages("influxdbclient")
The latest development version can be installed with
# install.packages("remotes")
remotes::install_github("influxdata/influxdb-client-r")
Usage
Client instantiation
library(influxdbclient)
client <- InfluxDBClient$new(url = "http://localhost:8086",
token = "my-token",
org = "my-org")
Parameters
Parameter | Description | Type | Default |
---|---|---|---|
url | InfluxDB instance URL | character | none |
token | authentication token | character | none |
org | organization name | character | none |
Hint: to avoid SSL certificate validation errors when accessing InfluxDB instance over https such as SSL certificate problem: unable to get local issuer certificate
, you can try to disable the validation using the following call before using any InfluxDBClient
method. Warning: it will disable peer certificate validation for the current R session.
library(httr)
httr::set_config(config(ssl_verifypeer = FALSE))
Querying data
Use query
method.
client <- InfluxDBClient$new(url = "http://localhost:8086",
token = "my-token",
org = "my-org")
data <- client$query('from(bucket: "my-bucket") |> range(start: -1h) |> drop(columns: ["_start", "_stop"])')
data
Flux query can yield multiple results in one response, where each result may contain multiple tables.
Return value is therefore a named list, where each element is a list of data frames that represent a result. Data frame represents Flux table. You can list the results using names
method.
Quite often, though, there is just a single result and therefore the query
by default flattens the return value to simple unnamed list of data frames. This behaviour controlled by flatSingleResult
parameter. With flatSingleResult = FALSE
, you can check that the return value contains one element with name "_result"
(default result name when there is no explicit yield
in the query) and use the name to retrieve it, like
> names(data)
[1] "_result"
> data[["_result"]]
[[1]]
time name region sensor_id altitude grounded temperature
1 2021-06-09T09:52:41+00:00 airSensors south TLM0101 549 FALSE 71.7844100
2 2021-06-09T09:52:51+00:00 airSensors south TLM0101 547 FALSE 71.7684399
3 2021-06-09T09:53:01+00:00 airSensors south TLM0101 563 TRUE 71.7819928
4 2021-06-09T09:53:11+00:00 airSensors south TLM0101 560 TRUE 71.7487767
5 2021-06-09T09:53:21+00:00 airSensors south TLM0101 544 FALSE 71.7335579
Parameters
Parameter | Description | Type | Default |
---|---|---|---|
text | Flux query | character | none |
POSIXctCol | Flux time to POSIXct column mapping | named list | c("_time"="time") |
flatSingleResult | Whether to return simple list when response contains only one result | logical | TRUE |
Incoming type mapping
Flux type | R type |
---|---|
string | character |
int | integer64 |
float | numeric |
bool | logical |
time | nanotime |
Using retrieved data as time series
Flux timestamps are parsed into nanotime
(integer64
underneath) type, because R datetime types do not support nanosecond precision. nanotime
is not a time-based object appropriate for creating a time series, though. By default, query
coerces the _time
column to time
column of POSIXct
type (see POSIXctCol
parameter), with possible loss precision (which is unimportant in the context of R time series).
Select data of interest from the result like
# from the first data frame, pick subset containing `time` and `_value` columns only
df1 <- data[[1]][c("time", "_value")]
Then, a time series object can be created from the data frame, eg. using tsbox
package:
ts1 <- ts_ts(ts_df(df1))
A data frame, or a time series object created from it, can be used for decomposition, anomaly detection etc, like
df1$`_value` %>% ts(freq=168) %>% stl(s.window=13) %>% autoplot()
or
ts1 %>% ts(freq=168) %>% stl(s.window=13) %>% autoplot()
Querying metadata
For queries returning records without time info (listing buckets, tag values etc.), set POSIXctCol
to NULL
.
buckets <- client$query('buckets()', POSIXctCol = NULL)
Writing data
Use write
method.
client <- InfluxDBClient$new(url = "http://localhost:8086",
token = "my-token",
org = "my-org")
data <- ...
response <- client$write(data, bucket = "my-bucket", precision = "us",
measurementCol = "name",
tagCols = c("region", "sensor_id"),
fieldCols = c("altitude", "temperature"),
timeCol = "time")
The example is valid for data.frame
data
like the following:
> print(data)
time name region sensor_id altitude grounded temperature
1 2021-06-09T09:52:41+00:00 airSensors south TLM0101 549 FALSE 71.7844100
2 2021-06-09T09:52:51+00:00 airSensors south TLM0101 547 FALSE 71.7684399
3 2021-06-09T09:53:01+00:00 airSensors south TLM0101 563 TRUE 71.7819928
4 2021-06-09T09:53:11+00:00 airSensors south TLM0101 560 TRUE 71.7487767
5 2021-06-09T09:53:21+00:00 airSensors south TLM0101 544 FALSE 71.7335579
> str(data)
'data.frame': 5 obs. of 7 variables:
$ time :integer64 1623232361000000000 1623232371000000000 1623232381000000000 1623232391000000000 1623232401000000000
$ name : chr "airSensors" "airSensors" "airSensors" "airSensors" ...
$ region : chr "south" "south" "south" "south" ...
$ sensor_id : chr "TLM0101" "TLM0101" "TLM0101" "TLM0101" ...
$ altitude :integer64 549 547 563 560 544
$ grounded : logi FALSE FALSE TRUE TRUE FALSE
$ temperature: num 71.8 71.8 71.8 71.7 71.7
Parameters
Parameter | Description | Type | Default |
---|---|---|---|
x | data | data.frame (or list of) | none |
bucket | target bucket name | character | none |
batchSize | batch size | numeric | 5000 |
precision | timestamp precision | character (one of s , ms , us , ns ) | "ns" |
measurementCol | measurement column name | character | "_measurement" |
tagCols | tags column names | character | NULL |
fieldCols | fields column names | character | c("_field"="_value") |
timeCol | time column name | character | "_time" |
object | output object | character | NULL |
Supported time column value types: nanotime
, POSIXct
. To write data points without timestamp, set timeCol
to NULL
. See Timestamp precision for details.
Response is either NULL
on success, or errorr otherwise.
Note: default fieldCols
value is suitable for writing back unpivoted data retrieved from InfluxDB before. For usual tables ("pivoted" in Flux world), fieldCols
should be unnamed list, eg. c("humidity", "temperature", ...)
.
Outgoing type mapping
R type | InfluxDB type |
---|---|
character | string |
integer , integer64 | int |
numeric | float |
logical | bool |
nanotime , POSIXct | time |
Output preview
To preview how input data are serialized to InfluxDB line protocol, pass the name of object to receive the output as object
parameter value.
It changes write
to dry-run operation (nothing is sent to the database). The object will be assigned to the calling environment.
This option is intended for debugging purposes.
data <- ...
response <- client$write(data, bucket = "my-bucket", precision = "us",
measurementCol = "name",
tagCols = c("region", "sensor_id"),
fieldCols = c("altitude", "temperature"),
timeCol = "time",
object = "lp")
lp
Sample output:
> print(lp)
[[1]]
[1] "airSensors,region=south,sensor_id=TLM0101 altitude=549i,temperature=71.7844100 1623232361000000"
[2] "airSensors,region=south,sensor_id=TLM0101 altitude=547i,temperature=71.7684399 1623232371000000"
[3] "airSensors,region=south,sensor_id=TLM0101 altitude=563i,temperature=71.7819928 1623232381000000"
[4] "airSensors,region=south,sensor_id=TLM0101 altitude=560i,temperature=71.7487767 1623232391000000"
[5] "airSensors,region=south,sensor_id=TLM0101 altitude=544i,temperature=71.7335579 1623232401000000"
Write retrying
By default, client will not retry failed writes. To instantiate a client with retry support, pass an instance of RetryOptions
, eg:
client <- InfluxDBClient$new(url = "http://localhost:8086",
token = "my-token",
org = "my-org",
retryOptions = RetryOptions$new(maxAttempts = 3))
For retry strategy with default options just pass TRUE
as retryOptions
parameter value:
client <- InfluxDBClient$new(url = "http://localhost:8086",
token = "my-token",
org = "my-org",
retryOptions = TRUE)
Retryable InfluxDB write errors are 429
and 503
status codes. The retry strategy implements exponential backoff algorithm, customizable with RetryOptions
.
Getting status
Health status
Use health
method to get the health status.
client <- InfluxDBClient$new(url = "http://localhost:8086",
token = "my-token",
org = "my-org")
check <- client$health()
Response is list with health information elements (name
, status
, version
, commit
) or error.
Readiness status
Use ready
method to get the readiness status.
client <- InfluxDBClient$new(url = "http://localhost:8086",
token = "my-token",
org = "my-org")
check <- client$ready()
Response is a list with status elements (status
, started
, up
) or error.
Advanced
The client automatically follows HTTP redirects.
To use the client with proxy, use set_config
to configure the proxy:
library(httr)
httr::set_config(
use_proxy(url = "my-proxy", port = 8080, username = "user",password = "password")
)
Known Issues
Contributing
Contributions are most welcome. The fastest way to get something fixed is to open a PR.
License
The client is available as open source under the terms of the MIT License.