Github user dongjoon-hyun commented on a diff in the pull request:
https://github.com/apache/spark/pull/22823#discussion_r228400706
--- Diff:
sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/BenchmarkWideTable.scala
---
@@ -1,52 +0,0 @@
-/*
- * 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.benchmark
-
-import org.apache.spark.benchmark.Benchmark
-
-/**
- * Benchmark to measure performance for wide table.
- * To run this:
- * build/sbt "sql/test-only *benchmark.BenchmarkWideTable"
- *
- * Benchmarks in this file are skipped in normal builds.
- */
-class BenchmarkWideTable extends BenchmarkWithCodegen {
-
- ignore("project on wide table") {
- val N = 1 << 20
- val df = sparkSession.range(N)
- val columns = (0 until 400).map{ i => s"id as id$i"}
- val benchmark = new Benchmark("projection on wide table", N)
- benchmark.addCase("wide table", numIters = 5) { iter =>
- df.selectExpr(columns : _*).queryExecution.toRdd.count()
- }
- benchmark.run()
-
- /**
- * Here are some numbers with different split threshold:
- *
- * Split threshold methods Rate(M/s) Per Row(ns)
- * 10 400 0.4 2279
- * 100 200 0.6 1554
- * 1k 37 0.9 1116
--- End diff --
Hi, @davies and @cloud-fan and @kiszk .
This benchmark is added in [Spark
2.1.0](https://github.com/apache/spark/commit/8d35a6f68d6d733212674491cbf31bed73fada0f#diff-71964129f49db97eb030a6d7320af314).
This value `1k` is determined by **manually** changing the split threhold.
This PR wants to [add a configuration in
CodeGenerator.scala](https://github.com/apache/spark/pull/22823/files#diff-8bcc5aea39c73d4bf38aef6f6951d42cR914)
for testing-purpose only.
1. Is the configuration helpful in general purpose?
2. If then, can we make another PR for that first?
3. If not, is it allowed to add this testing parameter?
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