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Copy file name to clipboardExpand all lines: benchmarks/README.md
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@@ -328,15 +328,17 @@ The `mem_profile` program wraps benchmark execution to measure memory usage stat
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Subcommands supported by mem_profile are the subset of those in `dfbench`.
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Currently supported benchmarks include: Clickbench, H2o, Imdb, SortTpch, Tpch
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Before running benchmarks, `mem_profile` automatically compiles the benchmark binary (`dfbench`) using `cargo build` with the same cargo profile (e.g., --release) as mem_profile itself. By prebuilding the binary and running each query in a separate process, we can ensure accurate memory statistics.
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Before running benchmarks, `mem_profile` automatically compiles the benchmark binary (`dfbench`) using `cargo build`. Note that the build profile used for `dfbench` is not tied to the profile used for running `mem_profile` itself. We can explicitly specify the desired build profile using the `--bench-profile` option (e.g.release-nonlto). By prebuilding the binary and running each query in a separate process, we can ensure accurate memory statistics.
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Currently, `mem_profile` only supports `mimalloc` as the memory allocator, since it relies on `mimalloc`'s API to collect memory statistics.
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Because it runs the compiled binary directly from the target directory, make sure your working directory is the top-level datafusion/ directory, where the target/ is also located.
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The benchmark subcommand (e.g., `tpch`) and all following arguments are passed directly to `dfbench`. Be sure to specify `--bench-profile` before the benchmark subcommand.
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