[jira] [Created] (ARROW-11745) [C++] Improve configurability of random data generation

["Ben Kietzman (Jira)" <ji...@apache.org>]

Ben Kietzman created ARROW-11745:
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             Summary: [C++] Improve configurability of random data generation
                 Key: ARROW-11745
                 URL: https://issues.apache.org/jira/browse/ARROW-11745
             Project: Apache Arrow
          Issue Type: Improvement
          Components: C++
    Affects Versions: 3.0.0
            Reporter: Ben Kietzman
            Assignee: Ben Kietzman


{{arrow::random::RandomArrayGenerator}} is useful for stress testing and benchmarking. Arrays of primitives can be generated with little boilerplate, however it is cumbersome to specify creation of nested arrays or record batches which are necessary for testing $n column operations such as group_by.

My ideal API for random generation takes only a FieldVector, a number of rows, and a seed as arguments. Other options (such as minimum, maximum, unique count, null probability, etc) are specified using field metadata so that they can be provided uniformly or granularly as necessary for a given test case:
{code:c++}
auto random_batch = Generate({
  field("i32", int32()), // i32 may take any value between INT_MAX and INT_MIN
                         // and will be null with default probability 0.01
  field("f32", float32(), false), // f32 will be entirely valid
  field("probability", float64(), true, key_value_metadata({
    // custom random generation properties:
    {"min", "0.0"},
    {"max", "1.0"},
    {"null_probability", "0.0001"},
  }),
  field("list_i32", list(
    field("item", int32(), true, key_value_metadata({
      // custom random generation properties can also be specified for null fields:
      {"min", "0"},
      {"max", "1"},
    })
  )),
}, num_rows, 0xdeadbeef);
{code}



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