Github user nongli commented on a diff in the pull request:
https://github.com/apache/spark/pull/11749#discussion_r56277494
--- Diff:
sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetReadBenchmark.scala
---
@@ -299,10 +299,112 @@ object ParquetReadBenchmark {
}
}
+ def stringWithNullsScanBenchmark(values: Int, fractionOfNulls: Double):
Unit = {
+ withTempPath { dir =>
+ withTempTable("t1", "tempTable") {
+ sqlContext.range(values).registerTempTable("t1")
+ sqlContext.sql(s"select IF(rand(1) < $fractionOfNulls, NULL,
cast(id as STRING)) as c1, " +
+ s"IF(rand(2) < $fractionOfNulls, NULL, cast(id as STRING)) as c2
from t1")
+ .write.parquet(dir.getCanonicalPath)
+
sqlContext.read.parquet(dir.getCanonicalPath).registerTempTable("tempTable")
+
+ val benchmark = new Benchmark("String with Nulls Scan", values)
+
+ benchmark.addCase("SQL Parquet Vectorized") { iter =>
+ sqlContext.sql("select sum(length(c2)) from tempTable where c1
is " +
+ "not NULL and c2 is not NULL").collect()
+ }
+
+ val files =
SpecificParquetRecordReaderBase.listDirectory(dir).toArray
+ benchmark.addCase("PR Vectorized") { num =>
+ var sum = 0
+ files.map(_.asInstanceOf[String]).foreach { p =>
+ val reader = new UnsafeRowParquetRecordReader
+ try {
+ reader.initialize(p, ("c1" :: "c2" :: Nil).asJava)
+ val batch = reader.resultBatch()
+ while (reader.nextBatch()) {
+ val rowIterator = batch.rowIterator()
+ while (rowIterator.hasNext) {
+ val row = rowIterator.next()
+ val value = row.getUTF8String(0)
+ if (!row.isNullAt(0) && !row.isNullAt(1)) sum +=
value.numBytes()
+ }
+ }
+ } finally {
+ reader.close()
+ }
+ }
+ }
+
+ benchmark.addCase("PR Vectorized (Null Filtering)") { num =>
+ var sum = 0L
+ files.map(_.asInstanceOf[String]).foreach { p =>
+ val reader = new UnsafeRowParquetRecordReader
+ try {
+ reader.initialize(p, ("c1" :: "c2" :: Nil).asJava)
+ val batch = reader.resultBatch()
+ batch.filterNullsInColumn(0)
+ batch.filterNullsInColumn(1)
+ while (reader.nextBatch()) {
+ val rowIterator = batch.rowIterator()
+ while (rowIterator.hasNext) {
+ sum += rowIterator.next().getUTF8String(0).numBytes()
+ }
+ }
+ } finally {
+ reader.close()
+ }
+ }
+ }
+
+ /*
+ =======================
+ Fraction of NULLs: 0
+ =======================
+
+ Intel(R) Core(TM) i7-4960HQ CPU @ 2.60GHz
+ String with Nulls Scan: Best/Avg Time(ms) Rate(M/s)
Per Row(ns) Relative
+
-------------------------------------------------------------------------------------------
+ SQL Parquet Vectorized 1164 / 1333 9.0
111.0 1.0X
+ PR Vectorized 809 / 882 13.0
77.1 1.4X
+ PR Vectorized (Null Filtering) 723 / 800 14.5
69.0 1.6X
+
+ =======================
+ Fraction of NULLs: 0.5
+ =======================
+
+ Intel(R) Core(TM) i7-4960HQ CPU @ 2.60GHz
+ String with Nulls Scan: Best/Avg Time(ms) Rate(M/s)
Per Row(ns) Relative
+
-------------------------------------------------------------------------------------------
+ SQL Parquet Vectorized 983 / 1001 10.7
93.8 1.0X
+ PR Vectorized 699 / 728 15.0
66.7 1.4X
+ PR Vectorized (Null Filtering) 722 / 746 14.5
68.9 1.4X
+
+ =======================
--- End diff --
Instead of commenting it this way, can you put the fraction in the
benchmark name?
e.g. String with Nulls Scan (95%)
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