Yes, we have the performance number against Snappy. It's included in our proposal. The performance various depending on workloads.
> For the sort workload (input, intermediate data, output are all > compression-enabled, 3TB data scale, 5 workers, 2 replica for data) with Map > Reduce, using QATCodec brings 7.29% performance gain and 7.5% better > compression ratio. For the sort workload (input and intermediate data are > compression-enabled, 3TB data scale) with Spark, it brings 14.3% performance > gain, 7.5% better compression ratio. Also we measured in Hive on MR with > TPCx-BB workload [3] (3TB data scale), it brings 12.98% performance gain, > 13.65% better compression ratio. Thanks Ferdinand Xu -----Original Message----- From: brijoobopanna [mailto:brijoobopa...@huawei.com] Sent: Monday, November 5, 2018 5:45 PM To: dev@carbondata.apache.org Subject: Re: Proposal to integrate QATCodec into Carbondata Thanks por proposing this QATCodec If any performance benchmarks are already available wrt Snappy or ZSTD -- Sent from: http://apache-carbondata-dev-mailing-list-archive.1130556.n5.nabble.com/
