1.
R and Athena …
there is
another way!?

2.
What is AWS Athena?
Amazon Athena is an interactive query service that makes it easy
to analyse data in Amazon S3 using standard SQL
select * from iris
My S3 Bucket
R_data
iris
iris.csv
mtcars
mtcars.csv
nyc_taxi
yellow_taxi_trip
year=2019
month=01
yellow_taxi_trip.csv
month=02
yellow_taxi_trip.csv
...
...
select * from yellow_taxi_trip
select * from yellow_taxi_trip
where year = ‘2019’
select * from yellow_taxi_trip
where year = ‘2019’
and month = ‘01’

3.
How to connect to AWS Athena?
# connecting using ODBC
library(DBI)
con <- dbConnect(odbc::odbc(), ...)
# connecting using jdbc
library(DBI)
library(RJDBC)
drv <- jdbc(...)
con <- dbConnect(drv, ...)
# connecting using AWS SDK
????

4.
A new Connection Method …
# connecting using AWS SDK
library(reticulate)
boto <- import(“boto3)
athena <- boto$Session()$client(“athena”)
# query athena
res <- athena$start_query_execution(QueryString = “select * from iris”,
QueryExecutionContext =
list(‘Database’ = ‘default’),
ResultConfiguration=
list(‘OutputLocation’= ‘s3://path/to/my/bucket/’))
# check status of query
status <- athena$get_query_execution(QueryExecutionId = res$QueryExecutionId)
# if query was successful then download output to local computer
if (status$QueryExecution$Status$State == “SUCCEEDED”) {
s3 <- boto$Session()$resource(“s3”)
key <- paste0(res$QueryExecutionId, “.csv”)
s3$Bucket(‘s3://path/to/my/bucket/’)$download_file(key, ‘c://my/computer/file.csv’)
}
That is a lot of code to just query a database! Plus there is no poll function to let us
know if the query has been successful or not. Is there a better way?

5.
Introducing RAthena
library(DBI)
con <- dbConnect(RAthena::athena(),
s3_staging_dir = ‘s3://path/to/my/bucket/’)
dbGetQuery(con, “select * from iris”)

6.
What a R SDK!?
# connecting using AWS SDK
athena <- paws::athena()
# query Athena
res <- athena$start_query_execution(QueryString = “select * from iris”,
QueryExecutionContext =
list(‘Database’ = ‘default’),
ResultConfiguration=
list(‘OutputLocation’= ‘s3://path/to/my/bucket/’))
# check status of query
status <- athena$get_query_execution(QueryExecutionId = res$QueryExecutionId)
# if query was successful then download output to local computer
if (status$QueryExecution$Status$State == “SUCCEEDED”) {
s3 <-paws::s3()
key <- paste0(res$QueryExecutionId, “.csv”)
obj <- s3$(Bucket = ‘s3://path/to/my/bucket/’, Key = key)
writeBin(obj$Body, “c://my/computer/file.csv”)
}

7.
Introducing noctua
library(DBI)
con <- dbConnect(noctua::athena(),
s3_staging_dir = ‘s3://path/to/my/bucket/’)
dbGetQuery(con, “select * from iris”)

8.
RStudio integration

9.
Other features
library(DBI)
library(dplyr)
con <- dbConnect(noctua::athena(),
s3_staging_dir = ‘s3://path/to/my/bucket/’)
dbWriteTable(con, “mtcars”, mtcars)
# or dplyr method
copy_to(con, mtcars)

10.
Useful links ….
• AWS Athena: https://aws.amazon.com/athena/
• Boto3: https://boto3.amazonaws.com/v1/documentation/api/latest/index.html
• reticulate: https://rstudio.github.io/reticulate/
• paws: https://paws-r.github.io/
• RAthena: https://dyfanjones.github.io/RAthena/
• noctua: https://dyfanjones.github.io/noctua/
Stuff about Me:
• https://github.com/DyfanJones
• https://dyfanjones.me/
• https://www.linkedin.com/in/dyfan-jones-a8261799/

11.
Any
Questions?
Thanks for listening