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[Java] Support for combining multiple vectors under VectorSchemaRoot #23358

@asfimport

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@asfimport

Hi,

 

pyarrow.Table.combine_chunks provides a nice functionality of combining multiple batch records under a single pyarrow.Table.

 

I am currently working on a downstream application which reads data from BigQuery. BigQuery storage api supports data output in Arrow format but streams data in many batches of size 1024 or less number of rows.

It would be really nice to have Arrow Java api provide this functionality under an abstraction like VectorSchemaRoot.

After getting guidance from [~emkornfield@gmail.com], I tried to write my own implementation by copying data vector by vector using TransferPair's copyValueSafe

But, unless I am missing some thing obvious, turns out it only copies one value at a time. That means a lot of looping trying copyValueSafe millions of rows from source vector index to target vector index. Ideally I would want to concatenate/link the underlying buffers rather than copying one cell at a time.

 

Eg, if I have :

List<VectorSchemaRoot> batchList = new ArrayList<>();
try (ArrowStreamReader reader = new ArrowStreamReader(new ByteArrayInputStream(out.toByteArray()), allocator)) {
    Schema schema = reader.getVectorSchemaRoot().getSchema();
    for (int i = 0; i < 5; i++) {
        // This will be loaded with new values on every call to loadNextBatch
        VectorSchemaRoot readBatch = reader.getVectorSchemaRoot();
        reader.loadNextBatch();
        batchList.add(readBatch);
    }
}

//VectorSchemaRoot.combineChunks(batchList, newVectorSchemaRoot);

 

A method like VectorSchemaRoot.combineChunks(List)?

I did read the VectorSchemaRoot discussion on https://issues.apache.org/jira/browse/ARROW-6896 and am not sure if its the right thing to use here.

 

 

PS. Feel free to update the title of this feature request with more appropriate wordings.

 

Cheers,

Yogesh

 

 

Reporter: Yogesh Tewari
Assignee: Liya Fan / @liyafan82

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Note: This issue was originally created as ARROW-7048. Please see the migration documentation for further details.

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