query_exec {bigrquery}R Documentation

Run a asynchronous query and retrieve results.

Description

This is a high-level function that inserts a query job (with insert_query_job()), repeatedly checks the status (with get_job()) until it is complete, then retrieves the results (with list_tabledata())

Usage

query_exec(query, project, destination_table = NULL, default_dataset = NULL,
  page_size = 10000, max_pages = 10, warn = TRUE,
  create_disposition = "CREATE_IF_NEEDED",
  write_disposition = "WRITE_EMPTY", use_legacy_sql = TRUE,
  quiet = getOption("bigrquery.quiet"), ...)

Arguments

query

SQL query string

project

The project name, a string

destination_table

(optional) destination table for large queries, either as a string in the format used by BigQuery, or as a list with project_id, dataset_id, and table_id entries

default_dataset

(optional) default dataset for any table references in query, either as a string in the format used by BigQuery or as a list with project_id and dataset_id entries

page_size

Number of items per page.

max_pages

maximum number of pages to retrieve. Use Inf to retrieve the complete dataset.

warn

If TRUE, warn when there are rows remaining to be pulled down from database.

create_disposition

behavior for table creation. defaults to "CREATE_IF_NEEDED", the only other supported value is "CREATE_NEVER"; see the API documentation for more information

write_disposition

behavior for writing data. defaults to "WRITE_EMPTY", other possible values are "WRITE_TRUNCATE" and "WRITE_APPEND"; see the API documentation for more information

use_legacy_sql

(optional) set to FALSE to enable BigQuery's standard SQL.

quiet

if FALSE, prints informative status messages.

...

Additional arguments merged into the body of the request. snake_case will automatically be converted into camelCase so you can use consistent argument names.

See Also

Google documentation describing asynchronous queries: https://developers.google.com/bigquery/docs/queries#asyncqueries

Google documentation for handling large results: https://developers.google.com/bigquery/querying-data#largequeryresults

Examples

## Not run: 
project <- "fantastic-voyage-389" # put your project ID here
sql <- "SELECT year, month, day, weight_pounds FROM [publicdata:samples.natality] LIMIT 5"
query_exec(sql, project = project)
# Put the results in a table you own (which uses project by default)
query_exec(sql, project = project, destination_table = "my_dataset.results")
# Use a default dataset for the query
sql <- "SELECT year, month, day, weight_pounds FROM natality LIMIT 5"
query_exec(sql, project = project, default_dataset = "publicdata:samples")

## End(Not run)
[Package bigrquery version 0.4.1 Index]