Github user viirya commented on the issue: https://github.com/apache/spark/pull/13371 @liancheng I rerun the benchmark that excludes the time of writing Parquet file: test("Benchmark for Parquet") { val N = 1 << 50 withParquetTable((0 until N).map(i => (101, i)), "t") { val benchmark = new Benchmark("Parquet reader", N) benchmark.addCase("reading Parquet file", 10) { iter => sql("SELECT _1 FROM t where t._1 < 100").collect() } benchmark.run() } } `withParquetTable` in default will run tests for vectorized reader non-vectorized readers. I only let it run vectorized reader. After this patch: Java HotSpot(TM) 64-Bit Server VM 1.8.0_25-b17 on Linux 3.13.0-57-generic Westmere E56xx/L56xx/X56xx (Nehalem-C) Parquet reader: Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative ------------------------------------------------------------------------------------------------ reading Parquet file 76 / 88 3.4 291.0 1.0X Before this patch: Java HotSpot(TM) 64-Bit Server VM 1.8.0_25-b17 on Linux 3.13.0-57-generic Westmere E56xx/L56xx/X56xx (Nehalem-C) Parquet reader: Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative ------------------------------------------------------------------------------------------------ reading Parquet file 81 / 91 3.2 310.2 1.0X Next, I run the benchmark for non-pushdown case using the same benchmark code but with disabled pushdown configuration. After this patch: Parquet reader: Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative ------------------------------------------------------------------------------------------------ reading Parquet file 80 / 95 3.3 306.5 1.0X Before this patch: Parquet reader: Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative ------------------------------------------------------------------------------------------------ reading Parquet file 80 / 103 3.3 306.7 1.0X For non-pushdown case, from the results, I think this patch doesn't affect normal code path.
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