Question

我使用Bigrquery软件包尝试了两种方式，

library(bigrquery)
library(DBI)

con <- dbConnect(
  bigrquery::bigquery(),
  project = "YOUR PROJECT ID HERE",
  dataset = "YOUR DATASET"
)
test<- dbGetQuery(con, sql, n = 10000, max_pages = Inf)

和

sql <- `YOUR LARGE QUERY HERE` #long query saved to View and its select here
tb <- bigrquery::bq_project_query(project, sql)
bq_table_download(tb, max_results = 1000)

但没有出现错误"Error: Requested Resource Too Large to Return [responseTooLarge]"，可能是相关的问题here，但是我对完成工作的任何工具都感兴趣：我已经尝试了概述的here解决方案，但是失败了

如何从BigQuery将大型数据集加载到R？

Answer 1

我看到有人创造了一种使这更容易的方法。涉及到一些 setup，但您可以使用 Google Storage API like so 进行下载：

## Auth is done automagically using Application Default Credentials.
## Use the following command once to set it up :
## gcloud auth application-default login --billing-project={project}
library(bigrquerystorage)

# TODO(developer): Set the project_id variable.
# project_id <- 'your-project-id'
#
# The read session is created in this project. This project can be
# different from that which contains the table.

rows <- bqs_table_download(
  x = "bigquery-public-data:usa_names.usa_1910_current"
  , parent = project_id
  # , snapshot_time = Sys.time() # a POSIX time
  , selected_fields = c("name", "number", "state"),
  , row_restriction = 'state = "WA"'
  # , as_tibble = TRUE # FALSE : arrow, TRUE : arrow->as.data.frame
)

sprintf("Got %d unique names in states: %s",
        length(unique(rows$name)),
        paste(unique(rows$state), collapse = " "))

# Replace bigrquery::bq_download_table
library(bigrquery)
rows <- bigrquery::bq_table_download("bigquery-public-data.usa_names.usa_1910_current")
# Downloading 6,122,890 rows in 613 pages.
overload_bq_table_download(project_id)
rows <- bigrquery::bq_table_download("bigquery-public-data.usa_names.usa_1910_current")
# Streamed 6122890 rows in 5980 messages.

Answer 2

根据@hrbrmstr的建议，the documentation特别提到：

> #' @param page_size The number of rows returned per page. Make this smaller
> #'   if you have many fields or large records and you are seeing a
> #'   'responseTooLarge' error.

在r-project.org的本文档中，您将在the explanation of this function (page 13)中阅读其他建议：

这将检索page_size块中的行。最适合较小查询的结果（例如<100 MB）。对于较大的查询，它是更好地将结果导出到存储在Google云中的CSV文件中，使用bq命令行工具在本地下载。

Answer 3

我也刚开始使用BigQuery。我认为应该是这样的。

可以从CRAN安装当前的bigrquery版本：

install.packages("bigrquery")

可以从GitHub安装最新的开发版本：

install.packages('devtools')
devtools::install_github("r-dbi/bigrquery")

用法低级API

library(bigrquery)
billing <- bq_test_project() # replace this with your project ID 
sql <- "SELECT year, month, day, weight_pounds FROM `publicdata.samples.natality`"

tb <- bq_project_query(billing, sql)
#> Auto-refreshing stale OAuth token.
bq_table_download(tb, max_results = 10)

DBI

library(DBI)

con <- dbConnect(
  bigrquery::bigquery(),
  project = "publicdata",
  dataset = "samples",
  billing = billing
)
con 
#> <BigQueryConnection>
#>   Dataset: publicdata.samples
#>   Billing: bigrquery-examples

dbListTables(con)
#> [1] "github_nested"   "github_timeline" "gsod"            "natality"       
#> [5] "shakespeare"     "trigrams"        "wikipedia"

dbGetQuery(con, sql, n = 10)



library(dplyr)

natality <- tbl(con, "natality")

natality %>%
  select(year, month, day, weight_pounds) %>% 
  head(10) %>%
  collect()

Answer 4

这帮了我大忙。

# Make page_size some value greater than the default (10000)
x <- 50000

bq_table_download(tb, page_size=x)

当心，如果将page_size设置为任意高的值（在我的情况下为100000），您将开始看到很多空行。

对于给定的表大小，正确的page_size值应该是什么还没有找到好的“经验法则”。

如何从BigQuery将大型数据集加载到R？

4 个答案: