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Posted to github@datafusion.apache.org by "mbutrovich (via GitHub)" <gi...@apache.org> on 2026/04/20 14:49:52 UTC

Re: [PR] docs: Update README and benchmark results for 0.15.0 release [datafusion-comet]

mbutrovich commented on code in PR #3995:
URL: https://github.com/apache/datafusion-comet/pull/3995#discussion_r3111536297


##########
README.md:
##########
@@ -40,75 +40,87 @@ Apache DataFusion Comet is a high-performance accelerator for Apache Spark, buil
 performance of Apache Spark workloads while leveraging commodity hardware and seamlessly integrating with the
 Spark ecosystem without requiring any code changes.
 
-Comet also accelerates Apache Iceberg, when performing Parquet scans from Spark.
-
 [Apache DataFusion]: https://datafusion.apache.org
 
-# Benefits of Using Comet
-
-## Run Spark Queries at DataFusion Speeds
+## Benefits of Using Comet
 
-Comet delivers a performance speedup for many queries, enabling faster data processing and shorter time-to-insights.
+### Reduce Your Spark Compute Costs
 
-The following chart shows the time it takes to run the 22 TPC-H queries against 100 GB of data in Parquet format
-using a single executor with 8 cores. See the [Comet Benchmarking Guide](https://datafusion.apache.org/comet/contributor-guide/benchmarking.html)
-for details of the environment used for these benchmarks.
+Comet's performance improvements translate directly into infrastructure savings. In many cases, jobs that previously
+required a given cluster size can run on roughly half the compute with Comet, producing meaningful cost reductions on

Review Comment:
   "half the resources"



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