[SPARK-12640][SQL] Add simple benchmarking utility class and add Parquet scan benchmarks.

[SPARK-12640][SQL] Add simple benchmarking utility class and add Parquet scan benchmarks.

We've run benchmarks ad hoc to measure the scanner performance. We will continue to invest in this
and it makes sense to get these benchmarks into code. This adds a simple benchmarking utility to do
this.

Author: Nong Li <nong@databricks.com>
Author: Nong <nongli@gmail.com>

Closes #10589 from nongli/spark-12640.

1 files changed, 158 insertions, 0 deletions

diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetReadBenchmark.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetReadBenchmark.scala
new file mode 100644
index 0000000000..cab6abde6d
--- /dev/null
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetReadBenchmark.scala
@@ -0,0 +1,158 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.spark.sql.execution.datasources.parquet
+
+import java.io.File
+
+import scala.collection.JavaConverters._
+import scala.util.Try
+
+import org.apache.spark.sql.{SQLConf, SQLContext}
+import org.apache.spark.util.{Benchmark, Utils}
+import org.apache.spark.{SparkConf, SparkContext}
+
+/**
+ * Benchmark to measure parquet read performance.
+ * To run this:
+ *  spark-submit --class <this class> --jars <spark sql test jar>
+ */
+object ParquetReadBenchmark {
+  val conf = new SparkConf()
+  conf.set("spark.sql.parquet.compression.codec", "snappy")
+  val sc = new SparkContext("local[1]", "test-sql-context", conf)
+  val sqlContext = new SQLContext(sc)
+
+  def withTempPath(f: File => Unit): Unit = {
+    val path = Utils.createTempDir()
+    path.delete()
+    try f(path) finally Utils.deleteRecursively(path)
+  }
+
+  def withTempTable(tableNames: String*)(f: => Unit): Unit = {
+    try f finally tableNames.foreach(sqlContext.dropTempTable)
+  }
+
+  def withSQLConf(pairs: (String, String)*)(f: => Unit): Unit = {
+    val (keys, values) = pairs.unzip
+    val currentValues = keys.map(key => Try(sqlContext.conf.getConfString(key)).toOption)
+    (keys, values).zipped.foreach(sqlContext.conf.setConfString)
+    try f finally {
+      keys.zip(currentValues).foreach {
+        case (key, Some(value)) => sqlContext.conf.setConfString(key, value)
+        case (key, None) => sqlContext.conf.unsetConf(key)
+      }
+    }
+  }
+
+  def intScanBenchmark(values: Int): Unit = {
+    withTempPath { dir =>
+      sqlContext.range(values).write.parquet(dir.getCanonicalPath)
+      withTempTable("tempTable") {
+        sqlContext.read.parquet(dir.getCanonicalPath).registerTempTable("tempTable")
+        val benchmark = new Benchmark("Single Int Column Scan", values)
+
+        benchmark.addCase("SQL Parquet Reader") { iter =>
+          sqlContext.sql("select sum(id) from tempTable").collect()
+        }
+
+        benchmark.addCase("SQL Parquet MR") { iter =>
+          withSQLConf(SQLConf.PARQUET_UNSAFE_ROW_RECORD_READER_ENABLED.key -> "false") {
+            sqlContext.sql("select sum(id) from tempTable").collect()
+          }
+        }
+
+        val files = SpecificParquetRecordReaderBase.listDirectory(dir).toArray
+        benchmark.addCase("ParquetReader") { num =>
+          var sum = 0L
+          files.map(_.asInstanceOf[String]).foreach { p =>
+            val reader = new UnsafeRowParquetRecordReader
+            reader.initialize(p, ("id" :: Nil).asJava)
+
+            while (reader.nextKeyValue()) {
+              val record = reader.getCurrentValue
+              if (!record.isNullAt(0)) sum += record.getInt(0)
+            }
+            reader.close()
+        }}
+
+        /*
+          Intel(R) Core(TM) i7-4870HQ CPU @ 2.50GHz
+          Single Int Column Scan:      Avg Time(ms)    Avg Rate(M/s)  Relative Rate
+          -------------------------------------------------------------------------
+          SQL Parquet Reader                 1910.0            13.72         1.00 X
+          SQL Parquet MR                     2330.0            11.25         0.82 X
+          ParquetReader                      1252.6            20.93         1.52 X
+        */
+        benchmark.run()
+      }
+    }
+  }
+
+  def intStringScanBenchmark(values: Int): Unit = {
+    withTempPath { dir =>
+      withTempTable("t1", "tempTable") {
+        sqlContext.range(values).registerTempTable("t1")
+        sqlContext.sql("select id as c1, cast(id as STRING) as c2 from t1")
+            .write.parquet(dir.getCanonicalPath)
+        sqlContext.read.parquet(dir.getCanonicalPath).registerTempTable("tempTable")
+
+        val benchmark = new Benchmark("Int and String Scan", values)
+
+        benchmark.addCase("SQL Parquet Reader") { iter =>
+          sqlContext.sql("select sum(c1), sum(length(c2)) from tempTable").collect
+        }
+
+        benchmark.addCase("SQL Parquet MR") { iter =>
+          withSQLConf(SQLConf.PARQUET_UNSAFE_ROW_RECORD_READER_ENABLED.key -> "false") {
+            sqlContext.sql("select sum(c1), sum(length(c2)) from tempTable").collect
+          }
+        }
+
+        val files = SpecificParquetRecordReaderBase.listDirectory(dir).toArray
+        benchmark.addCase("ParquetReader") { num =>
+          var sum1 = 0L
+          var sum2 = 0L
+          files.map(_.asInstanceOf[String]).foreach { p =>
+            val reader = new UnsafeRowParquetRecordReader
+            reader.initialize(p, null)
+            while (reader.nextKeyValue()) {
+              val record = reader.getCurrentValue
+              if (!record.isNullAt(0)) sum1 += record.getInt(0)
+              if (!record.isNullAt(1)) sum2 += record.getUTF8String(1).numBytes()
+            }
+            reader.close()
+          }
+        }
+
+        /*
+          Intel(R) Core(TM) i7-4870HQ CPU @ 2.50GHz
+          Int and String Scan:         Avg Time(ms)    Avg Rate(M/s)  Relative Rate
+          -------------------------------------------------------------------------
+          SQL Parquet Reader                 2245.6             7.00         1.00 X
+          SQL Parquet MR                     2914.2             5.40         0.77 X
+          ParquetReader                      1544.6            10.18         1.45 X
+        */
+        benchmark.run()
+      }
+    }
+  }
+
+  def main(args: Array[String]): Unit = {
+    intScanBenchmark(1024 * 1024 * 15)
+    intStringScanBenchmark(1024 * 1024 * 10)
+  }
+}