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/*
* 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 java.sql.{Date, Timestamp}
import org.apache.spark.sql.catalyst.expressions.{Alias, Attribute, AttributeMap, AttributeReference}
import org.apache.spark.sql.catalyst.plans.logical._
import org.apache.spark.sql.catalyst.util.DateTimeUtils
import org.apache.spark.sql.types._
class ProjectEstimationSuite extends StatsEstimationTestBase {
test("project with alias") {
val (ar1, colStat1) = (attr("key1"), ColumnStat(distinctCount = 2, min = Some(1),
max = Some(2), nullCount = 0, avgLen = 4, maxLen = 4))
val (ar2, colStat2) = (attr("key2"), ColumnStat(distinctCount = 1, min = Some(10),
max = Some(10), nullCount = 0, avgLen = 4, maxLen = 4))
val child = StatsTestPlan(
outputList = Seq(ar1, ar2),
rowCount = 2,
attributeStats = AttributeMap(Seq(ar1 -> colStat1, ar2 -> colStat2)))
val proj = Project(Seq(ar1, Alias(ar2, "abc")()), child)
val expectedColStats = Seq("key1" -> colStat1, "abc" -> colStat2)
val expectedAttrStats = toAttributeMap(expectedColStats, proj)
val expectedStats = Statistics(
sizeInBytes = 2 * (8 + 4 + 4),
rowCount = Some(2),
attributeStats = expectedAttrStats)
assert(proj.stats(conf) == expectedStats)
}
test("project on empty table") {
val (ar1, colStat1) = (attr("key1"), ColumnStat(distinctCount = 0, min = None, max = None,
nullCount = 0, avgLen = 4, maxLen = 4))
val child = StatsTestPlan(
outputList = Seq(ar1),
rowCount = 0,
attributeStats = AttributeMap(Seq(ar1 -> colStat1)))
checkProjectStats(
child = child,
projectAttrMap = child.attributeStats,
expectedSize = 1,
expectedRowCount = 0)
}
test("test row size estimation") {
val dec1 = Decimal("1.000000000000000000")
val dec2 = Decimal("8.000000000000000000")
val d1 = DateTimeUtils.fromJavaDate(Date.valueOf("2016-05-08"))
val d2 = DateTimeUtils.fromJavaDate(Date.valueOf("2016-05-09"))
val t1 = DateTimeUtils.fromJavaTimestamp(Timestamp.valueOf("2016-05-08 00:00:01"))
val t2 = DateTimeUtils.fromJavaTimestamp(Timestamp.valueOf("2016-05-09 00:00:02"))
val columnInfo: AttributeMap[ColumnStat] = AttributeMap(Seq(
AttributeReference("cbool", BooleanType)() -> ColumnStat(distinctCount = 2,
min = Some(false), max = Some(true), nullCount = 0, avgLen = 1, maxLen = 1),
AttributeReference("cbyte", ByteType)() -> ColumnStat(distinctCount = 2,
min = Some(1.toByte), max = Some(2.toByte), nullCount = 0, avgLen = 1, maxLen = 1),
AttributeReference("cshort", ShortType)() -> ColumnStat(distinctCount = 2,
min = Some(1.toShort), max = Some(3.toShort), nullCount = 0, avgLen = 2, maxLen = 2),
AttributeReference("cint", IntegerType)() -> ColumnStat(distinctCount = 2,
min = Some(1), max = Some(4), nullCount = 0, avgLen = 4, maxLen = 4),
AttributeReference("clong", LongType)() -> ColumnStat(distinctCount = 2,
min = Some(1L), max = Some(5L), nullCount = 0, avgLen = 8, maxLen = 8),
AttributeReference("cdouble", DoubleType)() -> ColumnStat(distinctCount = 2,
min = Some(1.0), max = Some(6.0), nullCount = 0, avgLen = 8, maxLen = 8),
AttributeReference("cfloat", FloatType)() -> ColumnStat(distinctCount = 2,
min = Some(1.0f), max = Some(7.0f), nullCount = 0, avgLen = 4, maxLen = 4),
AttributeReference("cdecimal", DecimalType.SYSTEM_DEFAULT)() -> ColumnStat(distinctCount = 2,
min = Some(dec1), max = Some(dec2), nullCount = 0, avgLen = 16, maxLen = 16),
AttributeReference("cstring", StringType)() -> ColumnStat(distinctCount = 2,
min = None, max = None, nullCount = 0, avgLen = 3, maxLen = 3),
AttributeReference("cbinary", BinaryType)() -> ColumnStat(distinctCount = 2,
min = None, max = None, nullCount = 0, avgLen = 3, maxLen = 3),
AttributeReference("cdate", DateType)() -> ColumnStat(distinctCount = 2,
min = Some(d1), max = Some(d2), nullCount = 0, avgLen = 4, maxLen = 4),
AttributeReference("ctimestamp", TimestampType)() -> ColumnStat(distinctCount = 2,
min = Some(t1), max = Some(t2), nullCount = 0, avgLen = 8, maxLen = 8)
))
val columnSizes: Map[Attribute, Long] = columnInfo.map(kv => (kv._1, getColSize(kv._1, kv._2)))
val child = StatsTestPlan(
outputList = columnInfo.keys.toSeq,
rowCount = 2,
attributeStats = columnInfo)
// Row with single column
columnInfo.keys.foreach { attr =>
withClue(s"For data type ${attr.dataType}") {
checkProjectStats(
child = child,
projectAttrMap = AttributeMap(attr -> columnInfo(attr) :: Nil),
expectedSize = 2 * (8 + columnSizes(attr)),
expectedRowCount = 2)
}
}
// Row with multiple columns
checkProjectStats(
child = child,
projectAttrMap = columnInfo,
expectedSize = 2 * (8 + columnSizes.values.sum),
expectedRowCount = 2)
}
private def checkProjectStats(
child: LogicalPlan,
projectAttrMap: AttributeMap[ColumnStat],
expectedSize: BigInt,
expectedRowCount: BigInt): Unit = {
val proj = Project(projectAttrMap.keys.toSeq, child)
val expectedStats = Statistics(
sizeInBytes = expectedSize,
rowCount = Some(expectedRowCount),
attributeStats = projectAttrMap)
assert(proj.stats(conf) == expectedStats)
}
}
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