RAthena
now supports caching. This was originally
inspired by pyathena
to reduce the cost of using
AWS Athena
. RAthena
however has a different
caching method and utilities local caching in R
environments instead of using AWS list_query_executions
.
This is down to dbClearResult
clearing
AWS S3
’s AWS Athena
output when caching is
disabled.
By caching queries the performance of repeat queries is significantly
improved. This is because the query is no longer sent to
AWS Athena
. Instead the query ID, of the repeating query,
is taken from the R environment and the result is returned from
AWS S3
.
library(DBI)
library(RAthena)
con = dbConnect(athena())
# Start caching queries
RAthena_options(cache_size = 10)
# Upload Data to AWS Athena
dbWriteTable(con, "iris", iris, partition = c("Partition" = "01"))
# initial query to AWS Athena
system.time(df1 = dbGetQuery(con, "select * from iris"))
# Info: (Data scanned: 3.63 KB)
# user system elapsed
# 0.105 0.004 3.397
# repeat query to AWS Athena
system.time(df2 = dbGetQuery(con, "select * from iris"))
# Info: (Data scanned: 3.63 KB)
# user system elapsed
# 0.072 0.000 0.348
Here we can see a performance increase of x10 with repeat query execution.
The weakness in caching occurs when the underlying data is updated. The cache will still only retrieve the previous query ID. This means that the new updated data won’t be return when the caching is enabled:
# Updating iris table
dbWriteTable(con, "iris", iris, append = T, partition = c("Partition" = "02"))
dt5 = dbGetQuery(con, "select * from iris")
# Stop using cache data
RAthena_options()
dt6 = dbGetQuery(con, "select * from iris")
nrow(dt5)
# 150
nrow(dt6)
# 300
Sadly the cached query didn’t pick up the new data from
iris
.
The caching method in RAthena
will remember previous
query ids within each R session, even if you stop and start caching in
RAthena_options
.
# Start caching
RAthena_options(cache_size = 10)
res1 = dbExecute(con, "select * from iris")
# Stop caching
RAthena_options()
res2 = dbExecute(con, "select * from iris")
# Start caching
RAthena_options(cache_size = 10)
res3 = dbExecute(con, "select * from iris")
# Compare Query ID's
res1@info$QueryExecutionId
# 9a9272f5-0632-4774-9aa9-d07f151dabc5
res2@info$QueryExecutionId
# be12fe0-3ec0-4595-b3e6-b3bf67efa266
res3@info$QueryExecutionId
# 9a9272f5-0632-4774-9aa9-d07f151dabc5
We can see that res1
and res3
utilise the
same QueryID, even tho caching was stopped and started.