>> def insertValues(rnd: String): Flow[Int, Boolean] = {
>> Flow[Int].mapAsyncUnordered(k => redis.set(k + rnd, message))
>> }
>> val maxSeq = 5000000
>> val seqSource = Source( () => (1 to maxSeq).iterator )
>>
>> *val streamWithSeqSource =
>> seqSource.via(insertValues(random1)).runWith(blackhole)*
>>
>> My understanding is that the next request is send to Redis from the
>> client only after a "single" Future is completed. Is this correct ?
>>
>
> No, the number of allowed uncompleted Futures is defined by the buffer
> size. If there wouldn't be a parallelization between Futures then there
> would be no need for an ordered and unordered version of the same operation.
>
>
Understood. So a map version will always be slower.
> Is there a way I can batch a bunch of set requests and wait for them to
>> be over before I can send a new batch ?
>>
>
> If there would be a version of set that accepts a Seq[] of writes, let's
> say "batchSet" then you could use:
>
> seqSource.grouped(100).mapAsyncUnordered(ks => redis.batchSet(...))
>
> Where grouped makes maximum 100 sized groups from the stream of elements
> resulting in a stream of sequences. You need API support for that from the
> Redis client though.
>
Yeah I tried that. Here is the code and the network IO. Throughput is
better, of course at the cost of latency. I've not figured out a way to
measure latency. Once I've a reliable way of doing so I can figure out what
the difference in latency is.
seqSource.grouped(100).mapAsyncUnordered { grp => {
val tran = redis.transaction()
for (i <- grp) yield {
tran.set(i + random2, message)
}
tran.exec()
}
}.runWith(blackhole)
<https://lh6.googleusercontent.com/-uheE7cqhSgQ/VJn6arTCdxI/AAAAAAAAvaY/hNZgyozl1JE/s1600/5million_1k_messages_grouped100.png>
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