“* 1000 statements in in each batch” sounds like you are doing batching in
both cases. I wouldn't expect things to get better with larger sizes than
that. We’ve generally found more like 100 is the sweet spot but I’m sure it’s
data specific.
On Sun, 18 Mar 2018 at 21:17 onmstester onmstester
I'm using a queue of 100 ExecuteAsyncs * 1000 statements in in each batch =
100K insert queue in non-batch scenario.
Using more than 1000 statememnts per batch throws batch limit exception and
some documents recommend no to change batch_size_limit??!
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On Sun, 18
When you say batch was worth than async in terms of throughput are you
comparing throughput with the same number of threads or something? I would
have thought if you have much less CPU usage on the client with batching
and your Cassandra cluster doesn’t sound terribly stressed then there is
room
Input data does not preserve good locality and I've already tested batch
insert, it was worse than executeAsync in case of throughput but much less CPU
usage at client side.
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On Sun, 18 Mar 2018 12:46:02 +0330 Ben Slater
ben.sla...@instaclustr.com wrote
You will probably find grouping writes into small batches improves overall
performance (if you are not doing it already). See the following
presentation for some more info:
https://www.slideshare.net/Instaclustr/microbatching-highperformance-writes
Cheers
Ben
On Sun, 18 Mar 2018 at 19:23
I need to insert some millions records in seconds in Cassandra. Using one
client with asyncExecute with folllowing configs:
maxConnectionsPerHost = 5
maxRequestsPerHost = 32K
maxAsyncQueue at client side = 100K
I could achieve 25% of throughtput i needed, client CPU is more than 80% and
