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ForbesLindesay avatar ForbesLindesay commented on June 2, 2024

Yes, this is the intended behaviour. batchSize and highWaterMark control the behaviour in the underlying db queries, so tuning the batch size and high water mark can improve throughput/performance, but the "chunks" returned in the stream are still individual records. If you need to batch them, you can write a separate utility that pulls a set number of items from the stream and emits that array as a chunk. Something like:

async function* batchStream<T>(source: AsyncIterator<T>, batchSize: number): AsyncIterator<T[]> {
  let batch = []
  for await (const record of source) {
    batch.push(record)
    if (batch.length === batchSize) {
      yield batch
      batch = []
    }
  }
  if (batch.length) yield batch
}

const query = sql`
        SELECT * FROM procedure(${collection}, ${channel}, ${merged})
`
const stream = db.queryNodeStream(query, { batchSize: 10, highWaterMark: 16 * 1024 })

for await (const chunk of batchStream(stream, 10))....

P.S. the batchSize is how many records to fetch at a time, the highWaterMark is how many records to allow the stream to buffer before applying back pressure (if you are consuming items slower than they are being returned form the database). 16 * 1024 would be a very large number of records to have as your high water mark if your batch size is only 10.

from atdatabases.

droganov avatar droganov commented on June 2, 2024

Hello @ForbesLindesay
Thank you for the update, yes, that's how I solved it

from atdatabases.

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