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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.

Factory

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

  • ...: Additional arguments, currently ignored

Methods

ScannerBuilder has the following methods:

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

  • $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.

  • $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.

Examples

# Set up directory for examples
tf <- tempfile()
dir.create(tf)
on.exit(unlink(tf))

write_dataset(mtcars, tf, partitioning="cyl")

ds <- open_dataset(tf)

scan_builder <- ds$NewScan()
scan_builder$Filter(Expression$field_ref("hp") > 100)
#> ScannerBuilder
scan_builder$Project(list(hp_times_ten = 10 * Expression$field_ref("hp")))
#> ScannerBuilder

# Once configured, call $Finish()
scanner <- scan_builder$Finish()

# Can get results as a table
as.data.frame(scanner$ToTable())
#>    hp_times_ten
#> 1          1130
#> 2          1090
#> 3          1100
#> 4          1100
#> 5          1100
#> 6          1050
#> 7          1230
#> 8          1230
#> 9          1750
#> 10         1750
#> 11         2450
#> 12         1800
#> 13         1800
#> 14         1800
#> 15         2050
#> 16         2150
#> 17         2300
#> 18         1500
#> 19         1500
#> 20         2450
#> 21         1750
#> 22         2640
#> 23         3350

# Or as a RecordBatchReader
scanner$ToRecordBatchReader()
#> RecordBatchReader
#> 1 columns
#> hp_times_ten: double
#> 
#> See $metadata for additional Schema metadata