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bigrquery 0.4.1.9000

New API

Complete overhaul of the low-level API to make it easier to use. (The primary motivation is to make the package more enjoyable for me to maintain but it should also be helpful if you need to do anything unsupported by the higher-level DBI and dplyr backends). Changes to the code have been paired with improved documentation and greater unit test coverage.

The old API has been soft-deprecated - it will continue to work, but no further development will occur. It will be formally deprecated in the next version, and then removed in the version after that.

  • Consistent naming scheme: All API functions now have the form bq_object_verb(), e.g. bq_table_create(), or bq_dataset_delete(). The old API will continue to exist, but I highly recommend moving to the new API.

  • S3 helper classes: bq_table(), bq_dataset(), bq_job(), bq_field() and bq_fields() constructor functions create S3 objects corresponding to important BigQuery objects (#150). These are paired with as_ coercion functions and used throughout the new API. This deprecates format_table(), format_dataset(), parse_table() and parse_dataset().

  • Easier local testing: New bq_test_project() and bq_test_dataset() make it easier to run bigrquery tests locally. All you need to do is create a new BigQuery project, set up billing, and make sure the project name is set in the BIGQUERY_TEST_PROJECT environment variable, then call bq_test_init().

  • More efficient data transer: the new api makes extensive user of the fields query parameter ensuring the bigrquery only downloads data that it actually uses (#153).

  • The new API uses standard SQL. To use legacy_sql set use_legacy_sql = TRUE in the query functions.

New feautres

  • bq_table_create() can now specify fields. (#204)

  • bq_project_query() and bq_dataset_query() can now supply query parameters (#191).

  • bq_table_load() loads data from a Google CloudStorage URI and is paired with bq_table_save() to save data to a Google CloudStorage URI (#155)

Other bug fixes and improvements

  • The dplyr interface can work with literal SQL once more (#218).

  • dplyr::compute() now works (@realAkhmed, #52).

  • The DBI interface has been updated to use the new low-level API. This means that it defaults to using modern SQL not legacy SQL. Use use_legacy_sql = TRUE in DBI::dbConnect() if you need to use legacy SQL (#147).

  • query_exec() fixed error caused by progress bar for queries with empty result (@byapparov, #206)

  • Request error messages will now contain the "reason", which can contain useful information for debugging (#209).

  • Improved SQL translation for pmax(), pmin(), sd(), all(), and any() (#176, #179, @jarodmeng). And for paste0(), cor() and cov() (@edgararuiz).

Version 0.4.1

  • Fix SQL translation omissions discovered by dbplyr 1.1.0

Version 0.4.0

New features

  • dplyr support has been updated to require dplyr 0.7.0 and use dbplyr. This means that you can now more naturally work directly with DBI connections. dplyr now also uses modern BigQuery SQL which supports a broader set of translations. Along the way I've also fixed some SQL generation bugs (#48).

  • The DBI driver gets a new name: bigquery().

  • New insert_extract_job() make it possible to extract data and save in google storage (@realAkhmed, #119).

  • New insert_table() allows you to insert empty tables into a dataset.

  • All POST requests (inserts, updates, copies and query_exec) now take .... This allows you to add arbitrary additional data to the request body making it possible to use parts of the BigQuery API that are otherwise not exposed (#149). snake_case argument names are automatically converted to camelCase so you can stick consistently to snake case in your R code.

  • Full support for DATE, TIME, and DATETIME types (#128).

Big fixes and minor improvements

  • All bigrquery requests now have a custom user agent that specifies the versions of bigrquery and httr that are used (#151).

  • dbConnect() gains new use_legacy_sql, page_size, and quiet arguments that are passed onto query_exec(). These allow you to control query options at the connection level.

  • insert_upload_job() now sends data in newline-delimited JSON instead of csv (#97). This should be considerably faster and avoids character encoding issues (#45). POSIXlt columns are now also correctly coerced to TIMESTAMPS (#98).

  • insert_query_job() and query_exec() gain new arguments:

    • quiet = TRUE will suppress the progress bars if needed.
    • use_legacy_sql = FALSE option allows you to opt-out of the legacy SQL system (#124, @backlin)

  • list_tables() (#108) and list_datasets() (#141) are now paginated. By default they retrieve 50 items per page, and will iterate until they get everything.

  • list_tabledata() and query_exec() now give a nicer progress bar, including estimated time remaining (#100).

  • query_exec() should be considerably faster because profiling revealed that ~40% of the time taken by was a single line inside a function that helps parse BigQuery's json into an R data frame. I replaced the slow R code with a faster C function.

  • set_oauth2.0_cred() allows user to supply their own Google OAuth application when setting credentials (#130, @jarodmeng)

  • wait_for() uses now reports the query total bytes billed, which is more accurate because it takes into account caching and other factors.

  • list_tabledata returns empty table on max_pages=0 (#184, @ras44 @byapparov)

Version 0.3.0

  • New set_service_token() allows you to use OAuth service token instead of interactive authentication.from

  • ^ is correctly translated to pow() (#110).

  • Provide full DBI compliant interface (@krlmlr).

  • Backend now translates iflese() to IF (@realAkhmed, #53).

Version 0.2.0.

  • Compatiable with latest httr.

  • Computation of the SQL data type that corresponds to a given R object is now more robust against unknown classes. (#95, @krlmlr)

  • A data frame with full schema information is returned for zero-row results. (#88, @krlmlr)

  • New exists_table(). (#91, @krlmlr)

  • New arguments create_disposition and write_disposition to insert_upload_job(). (#92, @krlmlr)

  • Renamed option bigquery.quiet to bigrquery.quiet. (#89, @krlmlr)

  • New format_dataset() and format_table(). (#81, @krlmlr)

  • New list_tabledata_iter() that allows fetching a table in chunks of varying size. (#77, #87, @krlmlr)

  • Add support for API keys via the BIGRQUERY_API_KEY environment variable. (#49)