maropu commented on a change in pull request #30334: URL: https://github.com/apache/spark/pull/30334#discussion_r589122426
########## File path: sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/statsEstimation/UnionEstimationSuite.scala ########## @@ -0,0 +1,240 @@ +/* + * 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.statsEstimation + +import org.apache.spark.sql.catalyst.expressions.{AttributeMap, AttributeReference} +import org.apache.spark.sql.catalyst.plans.logical +import org.apache.spark.sql.catalyst.plans.logical.{ColumnStat, Union} +import org.apache.spark.sql.types.{ByteType, DateType, Decimal, DecimalType, DoubleType, FloatType, IntegerType, LongType, ShortType, TimestampType} + +class UnionEstimationSuite extends StatsEstimationTestBase { + + test("test row size estimation") { + val attrInt = AttributeReference("cint", IntegerType)() + + val sz = Some(BigInt(1024)) + val child1 = StatsTestPlan( + outputList = Seq(attrInt), + rowCount = 2, + attributeStats = AttributeMap(Nil), + size = sz) + + val child2 = StatsTestPlan( + outputList = Seq(attrInt), + rowCount = 2, + attributeStats = AttributeMap(Nil), + size = sz) + + val union = Union(Seq(child1, child2)) + val expectedStats = logical.Statistics(sizeInBytes = 2 * 1024, rowCount = Some(4)) + assert(union.stats === expectedStats) + } + + test("col stats estimation") { + val sz = Some(BigInt(1024)) + + val attrInt = AttributeReference("cint", IntegerType)() + val attrDouble = AttributeReference("cdouble", DoubleType)() + val attrShort = AttributeReference("cshort", ShortType)() + val attrLong = AttributeReference("clong", LongType)() + val attrByte = AttributeReference("cbyte", ByteType)() + val attrFloat = AttributeReference("cfloat", FloatType)() + val attrDecimal = AttributeReference("cdecimal", DecimalType(5, 4))() + val attrDate = AttributeReference("cdate", DateType)() + val attrTimestamp = AttributeReference("ctimestamp", TimestampType)() + + val s1 = 1.toShort + val s2 = 4.toShort + val b1 = 1.toByte + val b2 = 4.toByte + val columnInfo: AttributeMap[ColumnStat] = AttributeMap( + Seq( + attrInt -> ColumnStat( + distinctCount = Some(2), + min = Some(1), + max = Some(4), + nullCount = Some(0), + avgLen = Some(4), + maxLen = Some(4)), + attrDouble -> ColumnStat( + distinctCount = Some(2), + min = Some(5.0), + max = Some(4.0), + nullCount = Some(0), + avgLen = Some(4), + maxLen = Some(4)), + attrShort -> ColumnStat(min = Some(s1), max = Some(s2)), + attrLong -> ColumnStat(min = Some(1L), max = Some(4L)), + attrByte -> ColumnStat(min = Some(b1), max = Some(b2)), + attrFloat -> ColumnStat(min = Some(1.1f), max = Some(4.1f)), + attrDecimal -> ColumnStat(min = Some(Decimal(13.5)), max = Some(Decimal(19.5))), + attrDate -> ColumnStat(min = Some(1), max = Some(4)), + attrTimestamp -> ColumnStat(min = Some(1L), max = Some(4L)))) + + val s3 = 2.toShort + val s4 = 6.toShort + val b3 = 2.toByte + val b4 = 6.toByte + val columnInfo1: AttributeMap[ColumnStat] = AttributeMap( + Seq( + AttributeReference("cint1", IntegerType)() -> ColumnStat( + distinctCount = Some(2), + min = Some(3), + max = Some(6), + nullCount = Some(0), + avgLen = Some(8), + maxLen = Some(8)), + AttributeReference("cdouble1", DoubleType)() -> ColumnStat( + distinctCount = Some(2), + min = Some(2.0), + max = Some(7.0), + nullCount = Some(0), + avgLen = Some(8), + maxLen = Some(8)), + AttributeReference("cshort1", ShortType)() -> ColumnStat(min = Some(s3), max = Some(s4)), + AttributeReference("clong1", LongType)() -> ColumnStat(min = Some(2L), max = Some(6L)), + AttributeReference("cbyte1", ByteType)() -> ColumnStat(min = Some(b3), max = Some(b4)), + AttributeReference("cfloat1", FloatType)() -> ColumnStat( + min = Some(2.2f), + max = Some(6.1f)), + AttributeReference("cdecimal1", DecimalType(5, 4))() -> ColumnStat( + min = Some(Decimal(14.5)), + max = Some(Decimal(19.9))), + AttributeReference("cdate1", DateType)() -> ColumnStat(min = Some(3), max = Some(6)), + AttributeReference("ctimestamp1", TimestampType)() -> ColumnStat( + min = Some(3L), + max = Some(6L)))) + + val child1 = StatsTestPlan( + outputList = columnInfo.keys.toSeq.sortWith(_.exprId.id < _.exprId.id), + rowCount = 2, + attributeStats = columnInfo, + size = sz) + + val child2 = StatsTestPlan( + outputList = columnInfo1.keys.toSeq.sortWith(_.exprId.id < _.exprId.id), + rowCount = 2, + attributeStats = columnInfo1, + size = sz) + + val union = Union(Seq(child1, child2)) + + val expectedStats = logical.Statistics( + sizeInBytes = 2 * 1024, + rowCount = Some(4), + attributeStats = AttributeMap( + Seq( + attrInt -> ColumnStat(min = Some(1), max = Some(6)), + attrDouble -> ColumnStat(min = Some(2.0), max = Some(7.0)), + attrShort -> ColumnStat(min = Some(s1), max = Some(s4)), + attrLong -> ColumnStat(min = Some(1L), max = Some(6L)), + attrByte -> ColumnStat(min = Some(b1), max = Some(b4)), + attrFloat -> ColumnStat(min = Some(1.1f), max = Some(6.1f)), + attrDecimal -> ColumnStat(min = Some(Decimal(13.5)), max = Some(Decimal(19.9))), + attrDate -> ColumnStat(min = Some(1), max = Some(6)), + attrTimestamp -> ColumnStat(min = Some(1L), max = Some(6L))))) + assert(union.stats === expectedStats) + } + + test("col stats estimation for decimal data type with different precision and scale") { Review comment: Ah, my bad... We can safely assume input decimals have the same precision&scale in analyzed plans, so we don't need this test case. ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: [email protected] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
