[jira] [Created] (ARROW-645) [Format] Mitigating the cost of random access in "wide" record batches

["Wes McKinney (JIRA)" <ji...@apache.org>]

Wes McKinney created ARROW-645:
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             Summary: [Format] Mitigating the cost of random access in "wide" record batches
                 Key: ARROW-645
                 URL: https://issues.apache.org/jira/browse/ARROW-645
             Project: Apache Arrow
          Issue Type: New Feature
          Components: Format
            Reporter: Wes McKinney


In very large schemas, due of the way we are flattening the field and buffer metadata in the RecordBatch:

https://github.com/apache/arrow/blob/master/format/Message.fbs#L271

The cost to reconstruct / load a single array from a RecordBatch can be arbitrarily high. 

As an example, let's consider a schema:

{code}
f0: int32
f1: string
...  omitting 999996 duplicate
f999998: int32
f999999: string
{code}

Here, a record batch has 1 million fields, and in total 1.5 million buffers. The problem with this is: to select a single field out of a record batch, we have to inspect all types leading up to the field of interest to know how many {{FieldNode}} and {{Buffer}} metadata values will have occurred in the serialized metadata before that field's metadata appears.

Solving this is a little bit tricky. One way would be to add optional "field position" and "buffer position" attributes to the {{Field}} table:

https://github.com/apache/arrow/blob/master/format/Message.fbs#L188

So here, we would know that for the {{f1}} field, the field index is 1 and the buffer index is 2. Because a string has 3 buffers associated with it, we would know to select buffers in slots 2, 3, 4 to reconstruct the vector container. 

Let me know if the problem is not clear, and any other ideas about solutions



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