These functions are low-level functions designed to be used by experts. Each of these low-level functions is paired with a high-level function that you should use instead:
bq_perform_copy(): bq_table_copy().
bq_perform_query(): bq_dataset_query(), bq_project_query().
bq_perform_upload(): bq_table_upload().
bq_perform_load(): bq_table_load().
bq_perform_extract(): bq_table_save().
bq_perform_extract(
x,
destination_uris,
destination_format = "NEWLINE_DELIMITED_JSON",
compression = "NONE",
...,
print_header = TRUE,
billing = x$project
)bq_perform_upload(
x,
values,
fields = NULL,
create_disposition = "CREATE_IF_NEEDED",
write_disposition = "WRITE_EMPTY",
...,
billing = x$project
)
bq_perform_load(
x,
source_uris,
billing = x$project,
source_format = "NEWLINE_DELIMITED_JSON",
fields = NULL,
nskip = 0,
create_disposition = "CREATE_IF_NEEDED",
write_disposition = "WRITE_EMPTY",
...
)
bq_perform_query(
query,
billing,
...,
parameters = NULL,
destination_table = NULL,
default_dataset = NULL,
create_disposition = "CREATE_IF_NEEDED",
write_disposition = "WRITE_EMPTY",
use_legacy_sql = FALSE,
priority = "INTERACTIVE"
)
bq_perform_query_dry_run(
query,
billing,
...,
default_dataset = NULL,
parameters = NULL,
use_legacy_sql = FALSE
)
bq_perform_copy(
src,
dest,
create_disposition = "CREATE_IF_NEEDED",
write_disposition = "WRITE_EMPTY",
...,
billing = NULL
)
A bq_job.
A bq_table
A character vector of fully-qualified Google Cloud
Storage URIs where the extracted table should be written. Can export
up to 1 Gb of data per file. Use a wild card URI (e.g.
gs://[YOUR_BUCKET]/file-name-*.json) to automatically create any
number of files.
The exported file format. Possible values include "CSV", "NEWLINE_DELIMITED_JSON" and "AVRO". Tables with nested or repeated fields cannot be exported as CSV.
The compression type to use for exported files. Possible values include "GZIP", "DEFLATE", "SNAPPY", and "NONE". "DEFLATE" and "SNAPPY" are only supported for Avro.
Additional arguments passed on to the underlying API call. snake_case names are automatically converted to camelCase.
Whether to print out a header row in the results.
Identifier of project to bill.
Data frame of values to insert.
A bq_fields specification, or something coercible to it
(like a data frame). Leave as NULL to allow BigQuery to auto-detect
the fields.
Specifies whether the job is allowed to create new tables.
The following values are supported:
"CREATE_IF_NEEDED": If the table does not exist, BigQuery creates the table.
"CREATE_NEVER": The table must already exist. If it does not, a 'notFound' error is returned in the job result.
Specifies the action that occurs if the destination table already exists. The following values are supported:
"WRITE_TRUNCATE": If the table already exists, BigQuery overwrites the table data.
"WRITE_APPEND": If the table already exists, BigQuery appends the data to the table.
"WRITE_EMPTY": If the table already exists and contains data, a 'duplicate' error is returned in the job result.
The fully-qualified URIs that point to your data in Google Cloud.
For Google Cloud Storage URIs: Each URI can contain one `'*'`` wildcard character and it must come after the 'bucket' name. Size limits related to load jobs apply to external data sources.
For Google Cloud Bigtable URIs: Exactly one URI can be specified and it has be a fully specified and valid HTTPS URL for a Google Cloud Bigtable table. For Google Cloud Datastore backups: Exactly one URI can be specified. Also, the '*' wildcard character is not allowed.
The format of the data files:
For CSV files, specify "CSV".
For datastore backups, specify "DATASTORE_BACKUP".
For newline-delimited JSON, specify "NEWLINE_DELIMITED_JSON".
For Avro, specify "AVRO".
For parquet, specify "PARQUET".
For orc, specify "ORC".
For source_format = "CSV", the number of header rows to skip.
SQL query string.
Named list of parameters match to query parameters.
Parameter x will be matched to placeholder @x.
Generally, you can supply R vectors and they will be automatically
converted to the correct type. If you need greater control, you can call
bq_param_scalar() or bq_param_array() explicitly.
See https://cloud.google.com/bigquery/docs/parameterized-queries for more details.
A bq_table where results should be stored. If not supplied, results will be saved to a temporary table that lives in a special dataset. You must supply this parameter for large queries (> 128 MB compressed).
A bq_dataset used to automatically qualify table names.
If TRUE will use BigQuery's legacy SQL format.
Specifies a priority for the query. Possible values include "INTERACTIVE" and "BATCH". Batch queries do not start immediately, but are not rate-limited in the same way as interactive queries.
Additional information at:
if (bq_testable()) {
ds <- bq_test_dataset()
bq_mtcars <- bq_table(ds, "mtcars")
job <- bq_perform_upload(bq_mtcars, mtcars)
bq_table_exists(bq_mtcars)
bq_job_wait(job)
bq_table_exists(bq_mtcars)
head(bq_table_download(bq_mtcars))
}
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