`sample()`

Samples a future computation and returns its result as an actual Julia value

sample(future)

Description

Banyan is a suite of libraries with functions for processing big data. These functions operate on and return futures. To convert a future into an actual Julia value, you may either compute it for an exact result or sample it for an approximation.

Required Parameters

`future` (`Future`)

The future to sample.

Returns (`Any`)

The Julia value that results from sampling the future.

Example Usage

df = read_parquet("s3://inventory/availability.parquet")
df_filtered = filter(row -> row.availability < 3, df)
println(sample(df_filtered))
println(compute(df_filtered))

sample()