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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