cloud-fan commented on a change in pull request #24068: [SPARK-27105][SQL]
Optimize away exponential complexity in ORC predicate conversion
URL: https://github.com/apache/spark/pull/24068#discussion_r282043784
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File path:
sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/FilterPushdownBenchmark.scala
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@@ -371,12 +403,64 @@ object FilterPushdownBenchmark extends BenchmarkBase
with SQLHelper {
withTempTable("orcTable", "parquetTable") {
saveAsTable(df, dir)
Seq(1, 250, 500).foreach { numFilter =>
- val whereExpr = (1 to numFilter).map(i => s"c$i = 0").mkString("
and ")
+ val whereExpr = (1 to numFilter).map(i => s"c$i = 0").mkString("
or ")
// Note: InferFiltersFromConstraints will add more filters to this
given filters
filterPushDownBenchmark(numRows, s"Select 1 row with $numFilter
filters", whereExpr)
}
}
}
}
+
+ runBenchmark(s"Predicate conversion benchmark with unbalanced Expression")
{
+ val numRows = 1
+ val width = 2000
+
+ val columns = (1 to width).map(i => s"id c$i")
+ val df = spark.range(1).selectExpr(columns: _*)
+ Seq(25, 5000, 15000).foreach { numFilter =>
+ val whereExpression = (1 to numFilter)
+ .map {
+ i =>
+ EqualTo(
+ Literal(0),
+ AttributeReference(
+ s"c1",
+ IntegerType,
+ nullable = true)()
+ ).asInstanceOf[Expression]
+ }
+ .foldLeft[Expression](Literal.FalseLiteral)((x, y) => Or(x, y))
+ val benchmark = new Benchmark(s"Select 1 row with $numFilter filters",
+ numRows, minNumIters = 5, output = output)
+ val name = s"Native ORC Vectorized (Pushdown)"
+ benchmark.addCase(name) { _ =>
+ OrcFilters.createFilter(df.schema,
+ DataSourceStrategy.translateFilter(whereExpression).toSeq)
+ }
+ benchmark.run()
+ }
+ }
+
+ runBenchmark(s"Pushdown benchmark with unbalanced Column") {
Review comment:
what's the difference between `Column` and `Expression` in this benchmark?
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