Does setting MaxStreamCount to 1 preserve row order in BigQuery Storage Read API?

Other Questions API
1

I’m working with BigQuery Storage Read API in my Go application to process large datasets. I know that when using multiple streams, the API doesn’t preserve the original row order from the table.

For my specific workflow, I need to keep rows in their original sequence (like they’re sorted by timestamp or ID in the source table). This makes my data processing pipeline much easier to handle.

I’m thinking about forcing single stream usage like this:

sessionRequest := &storagepb.CreateReadSessionRequest{
    Parent: fmt.Sprintf("projects/%s", projectConfig.ID),
    ReadSession: &storagepb.ReadSession{
        Table:      targetTable,
        DataFormat: formatType,
        ReadOptions: readConfig,
    },
    MaxStreamCount:          1,
    PreferredMinStreamCount: 1,
}

Will this approach actually guarantee that rows come out in the same order as they appear in the BigQuery table? Or do I need additional steps to ensure proper ordering?

2

Setting MaxStreamCount to 1 won’t preserve row order in BigQuery Storage Read API. Even with one stream, there’s no guarantee you’ll get rows in the original table order. BigQuery’s storage is distributed and built for performance, not sequential reads.

I hit this same problem last year with time-series data. You get a consistent snapshot of the table, but the order is basically random. The Storage Read API docs are clear about this - row ordering isn’t guaranteed no matter how many streams you use.

If you need ordered data, add an ORDER BY clause to your source query before creating the read session, or sort the data client-side after reading. For large datasets, I found client-side sorting worked better since it avoided timeouts on sorted queries.

3

unfortunatly, single stream wont help with ordering. bigquery’s storage api doesnt guarantee row order - thats just how the underlying storage works. even with maxstreamcount set to 1, ur still reading from distributed storage thats optimized for speed, not order. i tried this before and still got scrambled rows. your best options r using order by in ur initial query or sorting in ur go app after reading the data.

4

Nope, forcing a single stream won’t fix the ordering issue. Found this out the hard way migrating from standard BigQuery API to Storage Read API last month. BigQuery’s storage doesn’t maintain row order no matter how many streams you use. Storage Read API pulls directly from BigQuery’s columnar storage, which is optimized for compression and query speed - not keeping things in insertion order. Even with one stream, you’re getting data chunks that were stored for analytics performance, not the order they went in. I ended up adding explicit ordering to my source query before creating the read session. Adds overhead but gives consistent results. Or if your table has a natural ordering column like timestamp, you can partition reads by time ranges and process them one by one.