A Scanner iterates over a Dataset's fragments and returns data according to given row filtering and column projection. A ScannerBuilder can help create one.


Scanner$create() wraps the ScannerBuilder interface to make a Scanner. It takes the following arguments:

  • dataset: A Dataset or arrow_dplyr_query object, as returned by the dplyr methods on Dataset.

  • projection: A character vector of column names to select columns or a named list of expressions

  • filter: A Expression to filter the scanned rows by, or TRUE (default) to keep all rows.

  • use_threads: logical: should scanning use multithreading? Default TRUE

  • use_async: logical: should the async scanner (performs better on high-latency/highly parallel filesystems like S3) be used? Default FALSE

  • ...: Additional arguments, currently ignored


ScannerBuilder has the following methods:

  • $Project(cols): Indicate that the scan should only return columns given by cols, a character vector of column names

  • $Filter(expr): Filter rows by an Expression.

  • $UseThreads(threads): logical: should the scan use multithreading? The method's default input is TRUE, but you must call the method to enable multithreading because the scanner default is FALSE.

  • $UseAsync(use_async): logical: should the async scanner be used?

  • $BatchSize(batch_size): integer: Maximum row count of scanned record batches, default is 32K. If scanned record batches are overflowing memory then this method can be called to reduce their size.

  • $schema: Active binding, returns the Schema of the Dataset

  • $Finish(): Returns a Scanner

Scanner currently has a single method, $ToTable(), which evaluates the query and returns an Arrow Table.