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Diffstat (limited to 'sql/catalyst/src/test')
-rw-r--r-- | sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/util/QuantileSummariesSuite.scala | 126 |
1 files changed, 126 insertions, 0 deletions
diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/util/QuantileSummariesSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/util/QuantileSummariesSuite.scala new file mode 100644 index 0000000000..89b2a22a3d --- /dev/null +++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/util/QuantileSummariesSuite.scala @@ -0,0 +1,126 @@ +/* + * 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.catalyst.util + +import scala.util.Random + +import org.apache.spark.SparkFunSuite + +class QuantileSummariesSuite extends SparkFunSuite { + + private val r = new Random(1) + private val n = 100 + private val increasing = "increasing" -> (0 until n).map(_.toDouble) + private val decreasing = "decreasing" -> (n until 0 by -1).map(_.toDouble) + private val random = "random" -> Seq.fill(n)(math.ceil(r.nextDouble() * 1000)) + + private def buildSummary( + data: Seq[Double], + epsi: Double, + threshold: Int): QuantileSummaries = { + var summary = new QuantileSummaries(threshold, epsi) + data.foreach { x => + summary = summary.insert(x) + } + summary.compress() + } + + private def checkQuantile(quant: Double, data: Seq[Double], summary: QuantileSummaries): Unit = { + val approx = summary.query(quant) + // The rank of the approximation. + val rank = data.count(_ < approx) // has to be <, not <= to be exact + val lower = math.floor((quant - summary.relativeError) * data.size) + val upper = math.ceil((quant + summary.relativeError) * data.size) + val msg = + s"$rank not in [$lower $upper], requested quantile: $quant, approx returned: $approx" + assert(rank >= lower, msg) + assert(rank <= upper, msg) + } + + for { + (seq_name, data) <- Seq(increasing, decreasing, random) + epsi <- Seq(0.1, 0.0001) + compression <- Seq(1000, 10) + } { + + test(s"Extremas with epsi=$epsi and seq=$seq_name, compression=$compression") { + val s = buildSummary(data, epsi, compression) + val min_approx = s.query(0.0) + assert(min_approx == data.min, s"Did not return the min: min=${data.min}, got $min_approx") + val max_approx = s.query(1.0) + assert(max_approx == data.max, s"Did not return the max: max=${data.max}, got $max_approx") + } + + test(s"Some quantile values with epsi=$epsi and seq=$seq_name, compression=$compression") { + val s = buildSummary(data, epsi, compression) + assert(s.count == data.size, s"Found count=${s.count} but data size=${data.size}") + checkQuantile(0.9999, data, s) + checkQuantile(0.9, data, s) + checkQuantile(0.5, data, s) + checkQuantile(0.1, data, s) + checkQuantile(0.001, data, s) + } + } + + // Tests for merging procedure + for { + (seq_name, data) <- Seq(increasing, decreasing, random) + epsi <- Seq(0.1, 0.0001) + compression <- Seq(1000, 10) + } { + + val (data1, data2) = { + val l = data.size + data.take(l / 2) -> data.drop(l / 2) + } + + test(s"Merging ordered lists with epsi=$epsi and seq=$seq_name, compression=$compression") { + val s1 = buildSummary(data1, epsi, compression) + val s2 = buildSummary(data2, epsi, compression) + val s = s1.merge(s2) + val min_approx = s.query(0.0) + assert(min_approx == data.min, s"Did not return the min: min=${data.min}, got $min_approx") + val max_approx = s.query(1.0) + assert(max_approx == data.max, s"Did not return the max: max=${data.max}, got $max_approx") + checkQuantile(0.9999, data, s) + checkQuantile(0.9, data, s) + checkQuantile(0.5, data, s) + checkQuantile(0.1, data, s) + checkQuantile(0.001, data, s) + } + + val (data11, data12) = { + data.sliding(2).map(_.head).toSeq -> data.sliding(2).map(_.last).toSeq + } + + test(s"Merging interleaved lists with epsi=$epsi and seq=$seq_name, compression=$compression") { + val s1 = buildSummary(data11, epsi, compression) + val s2 = buildSummary(data12, epsi, compression) + val s = s1.merge(s2) + val min_approx = s.query(0.0) + assert(min_approx == data.min, s"Did not return the min: min=${data.min}, got $min_approx") + val max_approx = s.query(1.0) + assert(max_approx == data.max, s"Did not return the max: max=${data.max}, got $max_approx") + checkQuantile(0.9999, data, s) + checkQuantile(0.9, data, s) + checkQuantile(0.5, data, s) + checkQuantile(0.1, data, s) + checkQuantile(0.001, data, s) + } + } +} |