Github user HyukjinKwon commented on a diff in the pull request:
https://github.com/apache/spark/pull/21742#discussion_r201570499
--- Diff:
external/avro/src/test/scala/org/apache/spark/sql/avro/AvroReadBenchmark.scala
---
@@ -0,0 +1,62 @@
+/*
+ * 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.avro
+
+import java.io.File
+import java.util.concurrent.TimeUnit
+
+import org.apache.spark.sql.SparkSession
+
+// scalastyle:off println
+
+/**
+ * This object runs a simple benchmark test on the avro files in
benchmarkFilesDir. It measures
+ * how long does it take to convert them into DataFrame and run count()
method on them. See
+ * README on how to invoke it.
+ */
+object AvroReadBenchmark {
+
+ def main(args: Array[String]) {
+ val benchmarkDirFiles = new File(AvroFileGenerator.outputDir).list
+ if (benchmarkDirFiles == null || benchmarkDirFiles.isEmpty) {
+ sys.error(s"The benchmark directory ($AvroFileGenerator.outputDir)
does not exist or " +
+ "is empty. First you should generate some files to run a benchmark
with (see README)")
+ }
+
+ val spark =
SparkSession.builder().master("local[2]").appName("AvroReadBenchmark")
+ .getOrCreate()
+
+ spark.read.avro(AvroFileGenerator.outputDir).count()
+
+ println("\n\n\nStaring benchmark test - creating DataFrame from
benchmark avro files\n\n\n")
+
+ val startTime = System.nanoTime
+ spark
+ .read
+ .avro(AvroFileGenerator.outputDir)
+ .select("string")
+ .count()
+ val endTime = System.nanoTime
--- End diff --
In that case, shall we do the whole benchmark separately?
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