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AWS_ROLE_ARN
. This caused
confusing when connecting through web identity (#177)dbplyr::in_catalog
when working with
dplyr::tbl
(#178)INFO: (Data scanned: -43839744 Bytes)
clear_s3_resource
parameter to
RAthena_options
to prevent AWS Athena output AWS S3
resource being cleared up by dbClearResult
(#168). Thanks
to @juhoautio for
the request.boto3.session.Session
class and client
method
(#169)endpoint_override
parameter allow default
endpoints for each service to be overridden accordingly (#169). Thanks
to @aoyh for the request
and checking the package in development.test_data
to use
size
parameter explicitly.RAthena_options
to change 1 parameter at a time
without affecting other pre-configured settingsretry_quiet
parameter in RAthena_options
function.dbplyr
2.0.0 backend API.dplyr
to benefit from AWS Athena unload
methods (noctua #
174).dbGetQuery
, dbExecute
,
dbSendQuery
, dbSendStatement
work on older
versions of R
(noctua #
170). Thanks to @tyner for identifying issue.AWS Athena UNLOAD
(noctua: #
160). This is to take advantage of read/write speed
parquet
has to offer.import awswrangler as wr
import getpass
= getpass.getpass()
bucket = f"s3://{bucket}/data/"
path
if "awswrangler_test" not in wr.catalog.databases().values:
"awswrangler_test")
wr.catalog.create_database(
= ["id", "dt", "element", "value", "m_flag", "q_flag", "s_flag", "obs_time"]
cols
= wr.s3.read_csv(
df ="s3://noaa-ghcn-pds/csv/189",
path=cols,
names=["dt", "obs_time"]) # Read 10 files from the 1890 decade (~1GB)
parse_dates
wr.s3.to_parquet(=df,
df=path,
path=True,
dataset="overwrite",
mode="awswrangler_test",
database="noaa"
table;
)
="awswrangler_test", table="noaa") wr.catalog.table(database
library(DBI)
<- dbConnect(RAthena::athena())
con
# Query ran using CSV output
system.time({
= dbGetQuery(con, "SELECT * FROM awswrangler_test.noaa")
df
})# Info: (Data scanned: 80.88 MB)
# user system elapsed
# 57.004 8.430 160.567
::RAthena_options(cache_size = 1)
RAthena
# Query ran using UNLOAD Parquet output
system.time({
= dbGetQuery(con, "SELECT * FROM awswrangler_test.noaa", unload = T)
df
})
# Info: (Data scanned: 80.88 MB)
# user system elapsed
# 21.622 2.350 39.232
# Query ran using cache
system.time({
= dbGetQuery(con, "SELECT * FROM awswrangler_test.noaa", unload = T)
df
})# Info: (Data scanned: 80.88 MB)
# user system elapsed
# 13.738 1.886 11.029
sql_translate_env
correctly translates R functions
quantile
and median
to AWS Athena
equivalents (noctua #
153). Thanks to @ellmanj for spotting issue.AWS Athena
timestamp with time zone
data type.list
when converting data to
AWS Athena
SQL
format.library(data.table)
library(DBI)
= 5
x
= data.table(
dt var1 = sample(LETTERS, size = x, T),
var2 = rep(list(list("var3"= 1:3, "var4" = list("var5"= letters[1:5]))), x)
)
<- dbConnect(RAthena::athena())
con
#> Version: 2.2.0
sqlData(con, dt)
# Registered S3 method overwritten by 'jsonify':
# method from
# print.json jsonlite
# Info: Special characters "\t" has been converted to " " to help with Athena reading file format tsv
# var1 var2
# 1: 1 {"var3":[1,2,3],"var4":{"var5":["a","b","c","d","e"]}}
# 2: 2 {"var3":[1,2,3],"var4":{"var5":["a","b","c","d","e"]}}
# 3: 3 {"var3":[1,2,3],"var4":{"var5":["a","b","c","d","e"]}}
# 4: 4 {"var3":[1,2,3],"var4":{"var5":["a","b","c","d","e"]}}
# 5: 5 {"var3":[1,2,3],"var4":{"var5":["a","b","c","d","e"]}}
#> Version: 2.1.0
sqlData(con, dt)
# Info: Special characters "\t" has been converted to " " to help with Athena reading file format tsv
# var1 var2
# 1: 1 1:3|list(var5 = c("a", "b", "c", "d", "e"))
# 2: 2 1:3|list(var5 = c("a", "b", "c", "d", "e"))
# 3: 3 1:3|list(var5 = c("a", "b", "c", "d", "e"))
# 4: 4 1:3|list(var5 = c("a", "b", "c", "d", "e"))
# 5: 5 1:3|list(var5 = c("a", "b", "c", "d", "e"))
v-2.2.0 now converts lists into json lines format so that AWS Athena
can parse with sql
array
/mapping
/json
functions.
Small down side a s3 method conflict occurs when jsonify
is
called to convert lists into json lines. jsonify
was choose
in favor to jsonlite
due to the performance improvements
(noctua #
156).
dbIsValid
wrongly stated connection is valid for result
class when connection class was disconnected.sql_translate_env.paste
broke with latest version of
dbplyr
. New method is compatible with
dbplyr>=1.4.3
(noctua #
149).sql_translate_env
: add support for
stringr
/lubridate
style functions, similar to
Postgres
backend.dbConnect
add timezone
parameter so that
time zone between R
and AWS Athena
is
consistent (noctua #
149).AthenaConnection
class: ptr
and
info
slots changed from list
to
environment
with in AthenaConnect
class.
Allows class to be updated by reference. Simplifies notation when
viewing class from RStudio environment tab.AthenaResult
class: info
slot changed from
list
to environment
. Allows class to be
updated by reference.By utilising environments for AthenaConnection
and
AthenaResult
, all AthenaResult
classes created
from AthenaConnection
will point to the same
ptr
and info
environments for it’s connection.
Previously ptr
and info
would make a copy.
This means if it was modified it would not affect the child or parent
class for example:
# Old Method
library(DBI)
<- dbConnect(RAthena::athena(),
con rstudio_conn_tab = F)
<- dbExecute(con, "select 'helloworld'")
res
# modifying parent class to influence child
@info$made_up <- "helloworld"
con
# nothing happened
@connection@info$made_up
res# > NULL
# modifying child class to influence parent
@connection@info$made_up <- "oh no!"
res
# nothing happened
@info$made_up
con# > "helloworld"
# New Method
library(DBI)
<- dbConnect(RAthena::athena(),
con rstudio_conn_tab = F)
<- dbExecute(con, "select 'helloworld'")
res
# modifying parent class to influence child
@info$made_up <- "helloworld"
con
# picked up change
@connection@info$made_up
res# > "helloworld"
# modifying child class to influence parent
@connection@info$made_up <- "oh no!"
res
# picked up change
@info$made_up
con# > "oh no!"
AWS Athena
data types
[array, row, map, json, binary, ipaddress]
(noctua: #
135). Conversion types can be changed through dbConnect
and RAthena_options
.library(DBI)
library(RAthena)
# default conversion methods
<- dbConnect(RAthena::athena())
con
# change json conversion method
RAthena_options(json = "character")
:::athena_option_env$json
RAthena# [1] "character"
# change json conversion to custom method
RAthena_options(json = jsonify::from_json)
:::athena_option_env$json
RAthena# function (json, simplify = TRUE, fill_na = FALSE, buffer_size = 1024)
# {
# json_to_r(json, simplify, fill_na, buffer_size)
# }
# <bytecode: 0x7f823b9f6830>
# <environment: namespace:jsonify>
# change bigint conversion without affecting custom json conversion methods
RAthena_options(bigint = "numeric")
:::athena_option_env$json
RAthena# function (json, simplify = TRUE, fill_na = FALSE, buffer_size = 1024)
# {
# json_to_r(json, simplify, fill_na, buffer_size)
# }
# <bytecode: 0x7f823b9f6830>
# <environment: namespace:jsonify>
:::athena_option_env$bigint
RAthena# [1] "numeric"
# change binary conversion without affect, bigint or json methods
RAthena_options(binary = "character")
:::athena_option_env$json
RAthena# function (json, simplify = TRUE, fill_na = FALSE, buffer_size = 1024)
# {
# json_to_r(json, simplify, fill_na, buffer_size)
# }
# <bytecode: 0x7f823b9f6830>
# <environment: namespace:jsonify>
:::athena_option_env$bigint
RAthena# [1] "numeric"
:::athena_option_env$binary
RAthena# [1] "character"
# no conversion for json objects
<- dbConnect(RAthena::athena(), json = "character")
con2 # use custom json parser
<- dbConnect(RAthena::athena(), json = jsonify::from_json) con
rstudio_conn_tab
within dbConnect
.AWS Athena
uses float
data type for the
DDL only, RAthena
was wrongly parsing float
data type back to R. Instead AWS Athena
uses data type
real
in SQL functions like select cast
https://docs.aws.amazon.com/athena/latest/ug/data-types.html.
RAthena
now correctly parses real
to R’s data
type double
(noctua: #
133)AWS
returns to get all
results from AWS Glue
catalogue (noctua: #
137)dbGetPartition
. This
simply tidies up the default AWS Athena partition format.library(DBI)
library(RAthena)
<- dbConnect(athena())
con
dbGetPartition(con, "test_df2", .format = T)
# Info: (Data scanned: 0 Bytes)
# year month day
# 1: 2020 11 17
dbGetPartition(con, "test_df2")
# Info: (Data scanned: 0 Bytes)
# partition
# 1: year=2020/month=11/day=17
bigint
, this is
to align with other DBI interfaces i.e. RPostgres
. Now
bigint
can be return in the possible formats: [“integer64”,
“integer”, “numeric”, “character”]library(DBI)
con <- dbConnect(RAthena::athena(), bigint = "numeric")
When switching between the different file parsers the
bigint
to be represented according to the file parser
i.e. data.table
: “integer64” -> vroom
:
“I”.
dbRemoveTable
: Check if key has “.” or ends with “/”
before adding “/” to the end (noctua: #
125)Error: write_parquet requires the arrow package, please install it first and try again
sql_escape_date
into
dplyr_integration.R
backend (#121). Thanks to @OssiLehtinen for
developing Athena date translation.RAthena
to append to a static AWS s3 location
using uuiduse_deprecated_int96_timestamps
set to TRUE
.
This puts POSIXct data type in to java.sql.Timestamp
compatible format, such as yyyy-MM-dd HH:mm:ss[.f...]
.
Thanks to Christian N Wolz for highlight this issue.s3_upload_location
simplified how s3 location is built.
Now s3.location parameter isn’t affected and instead only additional
components e.g. name, schema and partition.dbplyr v-2.0.0
function in_schema
now
wraps strings in quotes, this breaks
db_query_fields.AthenaConnection
. Now
db_query_fields.AthenaConnection
removes any quotation from
the string so that it can search AWS GLUE
for table
metadata. (noctua: #
117)R
has been
interrupt a new parameter has been added to dbConnect
,
keyboard_interrupt
. Example:# Stop AWS Athena when R has been interrupted:
<- dbConnect(RAthena::athena())
con
# Let AWS Athena keep running when R has been interrupted:
<- dbConnect(RAthena::athena(),
con keyboard_interrupt = F)
RAthena
would return a
data.frame
for utility SQL
queries regardless
of backend file parser. This is due to AWS Athena
outputting SQL UTILITY
queries as a text file that required
to be read in line by line. Now RAthena
will return the
correct data format based on file parser set in
RAthena_options
for example:
RAthena_options("vroom")
will return
tibbles
.dbClearResult
when user doesn’t have permission to delete
AWS S3 objects (noctua: #
96)RAthena_options
contains 2 new parameters to control
how RAthena
handles retries.dbFetch
is able to return data from AWS Athena in
chunk. This has been achieved by passing NextToken
to
AthenaResult
s4 class. This method won’t be as fast
n = -1
as each chunk will have to be process into data
frame format.library(DBI)
<- dbConnect(RAthena::athena())
con <- dbExecute(con, "select * from some_big_table limit 10000")
res dbFetch(res, 5000)
dbWriteTable
opts to use alter table
instead
of standard msck repair table
. This is to improve
performance when appending to tables with high number of existing
partitions.dbWriteTable
now allows json to be appended to json
ddls created with the Openx-JsonSerDe library.dbConvertTable
brings dplyr::compute
functionality to base package, allowing RAthena
to use the
power of AWS Athena to convert tables and queries to more efficient file
formats in AWS S3 (#37).dplyr::compute
to give same functionality of
dbConvertTable
boto3
not being detected
has been updated. This is due to several users not sure how to get
RAthena
set-up.stop("Boto3 is not detected please install boto3 using either: `pip install boto3 numpy` in terminal or `install_boto()`.",
"\nIf this doesn't work please set the python you are using with `reticulate::use_python()` or `reticulate::use_condaenv()`",
call. = FALSE)
region_name
check before making a connection to
AWS Athena (#110)dbWriteTable
would throw throttling error
every now and again, retry_api_call
as been built to handle
the parsing of data between R and AWS S3.dbWriteTable
did not clear down all metadata when
uploading to AWS Athena
dbWriteTable
added support ddl structures for user who
have created ddl’s outside of RAthena
RAthena
retry
functionality\dontrun
(#108)pyathena
, RAthena_options
now
has a new parameter cache_size
. This implements local
caching in R environments instead of using AWS
list_query_executions
. This is down to
dbClearResult
clearing S3’s Athena output when caching
isn’t disabledRAthena_options
now has clear_cache
parameter to clear down all cached data.dbRemoveTable
now utilise AWS Glue
to
remove tables from AWS Glue
catalogue. This has a
performance enhancement:library(DBI)
= dbConnect(RAthena::athena())
con
# upload iris dataframe for removal test
dbWriteTable(con, "iris2", iris)
# Athena method
system.time(dbRemoveTable(con, "iris2", confirm = T))
# user system elapsed
# 0.131 0.037 2.404
# upload iris dataframe for removal test
dbWriteTable(con, "iris2", iris)
# Glue method
system.time(dbRemoveTable(con, "iris2", confirm = T))
# user system elapsed
# 0.065 0.009 1.303
dbWriteTable
now supports uploading json lines
(http://jsonlines.org/) format up to AWS Athena
(#88).library(DBI)
= dbConnect(RAthena::athena())
con
dbWriteTable(con, "iris2", iris, file.type = "json")
dbGetQuery(con, "select * from iris2")
dbWriteTable
appending to existing table compress file
type was incorrectly return.install_boto
added numpy
to
RAthena
environment install as reticulate
appears to favour environments with numpy
(https://github.com/rstudio/reticulate/issues/216)Rstudio connection tab
comes into an issue when Glue
Table isn’t stored correctly (#92)AWS_REGION
into
dbConnect
fwrite
(>=1.12.4)
https://github.com/Rdatatable/data.table/blob/master/NEWS.mdsql_translate_env
(#44)# Before
::translate_sql("2019-01-01", con = con)
dbplyr# '2019-01-01'
# Now
::translate_sql("2019-01-01", con = con)
dbplyr# DATE '2019-01-01'
paste
/paste0
would use default
dplyr:sql-translate-env
(concat_ws
).
paste0
now uses Presto’s concat
function and
paste
now uses pipes to get extra flexibility for custom
separating values.# R code:
paste("hi", "bye", sep = "-")
# SQL translation:
'hi'||'-'||'bye') (
append
set to
TRUE
then existing s3.location will be utilised (#73)db_compute
returned table name, however when a user
wished to write table to another location (#74). An error would be
raised:
Error: SYNTAX_ERROR: line 2:6: Table awsdatacatalog.default.temp.iris does not exist
This has now been fixed with db_compute returning
dbplyr::in_schema
.library(DBI)
library(dplyr)
<- dbConnect(RAthena::athena())
con
tbl(con, "iris") %>%
compute(name = "temp.iris")
dbListFields
didn’t display partitioned columns. This
has now been fixed with the call to AWS Glue being altered to include
more metadata allowing for column names and partitions to be
returned.dbListFields
RAthena_options
vroom
has been restricted to >= 1.2.0
due to integer64 support and changes to vroom
apidbStatistics
is a wrapper around boto3
get_query_execution
to return statistics for
RAthena::dbSendQuery
results (#67)dbGetQuery
has new parameter statistics
to
print out dbStatistics
before returning Athena results
(#67)s3.location
now follows new syntax
s3://bucket/{schema}/{table}/{partition}/{table_file}
to
align with Pyathena
and to allow tables with same name but
in different schema to be uploaded to s3 (#73).dplyr::tbl
when calling Athena when using the ident
method (noctua # 64):library(DBI)
library(dplyr)
<- dbConnect(RAthena::athena())
con
# ident method:
<- system.time(tbl(con, "iris"))
t1
# sub query method:
<- system.time(tbl(con, sql("select * from iris")))
t2
# ident method
# user system elapsed
# 0.082 0.012 0.288
# sub query method
# user system elapsed
# 0.993 0.138 3.660
dplyr
sql_translate_env: expected results have now been
updated to take into account bug fix with date fieldsdata.table
to vroom
. From now on
it is possible to change file parser using RAthena_options
for example:library(RAthena)
RAthena_options("vroom")
dbGetTables
that returns Athena hierarchy
as a data.framevroom
Updated R documentation to roxygen2
7.0.2
dbWriteTable
append
parameter checks and uses
existing AWS Athena DDL file type. If file.type
doesn’t
match Athena DDL file type then user will receive a warning
message:warning('Appended `file.type` is not compatible with the existing Athena DDL file type and has been converted to "', File.Type,'".', call. = FALSE)
tolower
conversion due to request #41dbRemoveTable
can now remove S3 files for AWS Athena table
being removed.as.character
was getting wrongly
translated #45INTEGER
being incorrectly translated
in sql_translate_env.R
data-transfer
dbRemoveTable
new parameters are added in unit
testsql_translate_env
until test to cater bug
fixdbWriteTable
now will split gzip
compressed files to improve AWS Athena performance. By default
gzip
compressed files will be split into 20.Performance results
library(DBI)
<- 1e8
X
<- data.frame(w =runif(X),
df x = 1:X,
y = sample(letters, X, replace = T),
z = sample(c(TRUE, FALSE), X, replace = T))
<- dbConnect(RAthena::athena())
con
# upload dataframe with different splits
dbWriteTable(con, "test_split1", df, compress = T, max.batch = nrow(df), overwrite = T) # no splits
dbWriteTable(con, "test_split2", df, compress = T, max.batch = 0.05 * nrow(df), overwrite = T) # 20 splits
dbWriteTable(con, "test_split3", df, compress = T, max.batch = 0.1 * nrow(df), overwrite = T) # 10 splits
AWS Athena performance results from AWS console (query executed:
select count(*) from ....
):
library(DBI)
<- 1e8
X
<- data.frame(w =runif(X),
df x = 1:X,
y = sample(letters, X, replace = T),
z = sample(c(TRUE, FALSE), X, replace = T))
<- dbConnect(RAthena::athena())
con
dbWriteTable(con, "test_split1", df, compress = T, overwrite = T) # default will now split compressed file into 20 equal size files.
Added information message to inform user about what files have been added to S3 location if user is overwriting an Athena table.
copy_to
method now supports compress and max_batch, to
align with dbWriteTable
dbWriteTable
POSIXct
to Athena. This class was
convert incorrectly and AWS Athena would return NA instead.
RAthena
will now correctly convert POSIXct
to
timestamp but will also correct read in timestamp into
POSIXct
NA
in string format. Before RAthena
would
return NA
in string class as ""
this has now
been fixed.RAthena
would translate output into a vector with current
the method dbFetch
n = 0.sql_translate_env
. Previously RAthena
would take the default dplyr::sql_translate_env
, now
RAthena
has a custom method that uses Data types from:
https://docs.aws.amazon.com/athena/latest/ug/data-types.html and window
functions from:
https://docs.aws.amazon.com/athena/latest/ug/functions-operators-reference-section.htmlPOSIXct
class has now been added to data transfer unit
testdplyr sql_translate_env
tests if R functions are
correct translated in to Athena sql
syntax.dbWriteTable
is called. The bug is due to function
sqlCreateTable
which dbWriteTable
calls.
Parameters table
and fields
were set to
NULL
. This has now been fixed.s3.location
parameter is dbWriteTable
can
now be made nullablesqlCreateTable
info message will now only inform user
if colnames have changed and display the column name that have
changedupload_data
has been rebuilt and
removed the old “horrible” if statement with paste
now the
function relies on sprintf
to construct the s3 location
path. This method now is a lot clearer in how the s3 location is created
plus it enables a dbWriteTable
to be simplified.
dbWriteTable
can now upload data to the default s3_staging
directory created in dbConnect
this simplifies
dbWriteTable
to :library(DBI)
<- dbConnect(RAthena::athena())
con
dbWrite(con, "iris", iris)
dbWriteTable
data transfer
test now tests compress, and default
s3.location when transferring datadata.table::fread
. This enables data types to be read in
correctly and not required a second stage to convert data types once
data has been read into Rdata.table::fread
and
data.table::fwrite
have been disabledutil
functions from namespace:
write.table
, read.csv
data.table
to namespacebigint
are convert into R
bit64::integer64
and visa versabigint
to integer64
in data.transfer
unit testdbConnect
methoddbFetch
with chunk sizes between 0 - 999.
Fixed error where for loop
would return error instead of
breaking.py_error
function, set call.
parameter to FALSE
AthenaQuery
s4 class changed to
AthenaResult
dbFetch
added datatype collectiondbFetch
replaced S3 search for query key with output
location from AthenadbClearResult
changed error, to return python error as
warning to warn user doesn’t have permission to delete S3 resourcedbClearResult
replaced S3 search for query key with out
location from AthenadbListTables
now returns vector of tables from
aws glue
instead of using an AWS Athena
query.
This method increases speed of call of querydbListFields
now returns column names from
aws glue
instead of using an AWS Athena
query.. This method increases speed of call of querydbExistsTable
now returns boolean from
aws glue
instead of using an AWS Athena
query.. This method increases speed of call of querycreate_work_group
: Creates a workgroup with the
specified name.delete_work_group
: Deletes the workgroup with the
specified name.list_work_group
: Lists available workgroups for the
account.get_work_group
: Returns information about the workgroup
with the specified name.update_work_group
: Updates the workgroup with the
specified name. The workgroup’s name cannot be changed.get_session_token
to
create temporary session credentialsassume_role
to assume
AWS ARN RoledbConnect
set_aws_env
to set aws tokens
to environmental variablesget_aws_env
to return expected
results from system variablestag_options
to create tag
options for create_work_group
work_group_config
and
work_group_config_update
to create config of work
groupAthenaConnection
dbColumnInfo
method: returns data.frame
containing field_name
and type
time_check
to check how long is
left on the Athena Connection, if less than 15 minutes a warning message
is outputted to notify userdb_collect
for better
integration with dplyrdb_save_query
for better
integration with dplyrdb_copy_to
for better
integration with dplyrdbFetch
Athena data type miss alignmentAthenaConnection
:
request
build Athena query
requestdb_desc
dbConnect
stop_query_execution
to
dbClearResult
if the query is still runningdbWriteTable
)waiter
to poll
, to
align with python’s pollingThese binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.