Added the extract job: BigQuery -> Cloud Storage

[realAkhmed]

Hello. Have been using this function for a while in my personal fork and always wanted to share it with the community.

This is the code for doing a BigQuery extract job.
Basically, taking a BigQuery table and extracting it into a CSV file(s) inside Cloud Storage bucket.

The following code contains an example of how to use it

 # specify your project ID here
project <- "<my_project_id>"

 # specify your Cloud Storage bucket name (note the wildcard)
bucket <- "gs://<my_bucket>/shakespeare*.csv"

# Now run the extract_exec - it will return the number of files that were extracted
extract_exec("publicdata:samples.shakespeare", project = project, destinationUris = bucket)

Shakespeare is a small dataset so you won't get charged a lot for that example.

The structure of this file is modeled after insert_upload_job and insert_query_job

[craigcitro]

I think you lost the end of the sentence?

[hadley]

Also needs to be wrapper

[hadley]

@realAkhmed are you interested in finishing off this PR?

[realAkhmed]

@hadley Absolutely! Just wasn't sure if the package is still actively developed.

This particular PR was very useful for me internally since it opens way for what I called as collect_by_export() -- collecting huge results from BigQuery by automatically saving a query to a temporary table, then exporting it to CSV, then downloading CSV, then parsing CSV locally. This works much faster than a regular collect() on very large query results.

[craigcitro]

@realAkhmed agreed that this is indeed a faster route in general -- but CSV as a transport format isn't great for the case that your table includes nested or repeated fields.

I'd be curious what @hadley knows about potentially converting avro to a dataframe, since that would give us full fidelity exports.

[hadley]

These should use snake case to be consistent with the rest of bigrquery

[hadley]

I'd also recommend putting one parameter on each line.

[hadley]

Remove extra parens?

[IronistM]

💯 claps for this!

[hadley]

I'm just going to merge this so I can work on locally.

[realAkhmed]

Thanks @hadley ! Somewhat slow to respond at the moment (the teaching season) -- will come back to address the issues raised by you and @craigcitro once done with it!