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From: cloud-fan <git@git.apache.org>
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Subject: [GitHub] spark pull request #16395: [SPARK-17075][SQL] implemented filter estimation
Content-Type: text/plain
Message-Id: <20170224020711.917A6DFF0B@git1-us-west.apache.org>
Date: Fri, 24 Feb 2017 02:07:11 +0000 (UTC)
archived-at: Fri, 24 Feb 2017 02:07:14 -0000

Github user cloud-fan commented on a diff in the pull request:

    https://github.com/apache/spark/pull/16395#discussion_r102865689
  
    --- Diff: sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/statsEstimation/FilterEstimationSuite.scala ---
    @@ -0,0 +1,403 @@
    +/*
    + * 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._
    +import org.apache.spark.sql.catalyst.plans.logical._
    +import org.apache.spark.sql.catalyst.plans.logical.statsEstimation.EstimationUtils._
    +import org.apache.spark.sql.catalyst.util.DateTimeUtils
    +import org.apache.spark.sql.types._
    +
    +/**
    + * In this test suite, we test predicates containing the following operators:
    + * =, <, <=, >, >=, AND, OR, IS NULL, IS NOT NULL, IN, NOT IN
    + */
    +class FilterEstimationSuite extends StatsEstimationTestBase {
    +
    +  // Suppose our test table has 10 rows and 6 columns.
    +  // First column cint has values: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10
    +  // Hence, distinctCount:10, min:1, max:10, nullCount:0, avgLen:4, maxLen:4
    +  val arInt = AttributeReference("cint", IntegerType)()
    +  val childColStatInt = ColumnStat(distinctCount = 10, min = Some(1), max = Some(10),
    +    nullCount = 0, avgLen = 4, maxLen = 4)
    +
    +  // Second column cdate has 10 values from 2017-01-01 through 2017-01-10.
    +  val dMin = Date.valueOf("2017-01-01")
    +  val dMax = Date.valueOf("2017-01-10")
    +  val arDate = AttributeReference("cdate", DateType)()
    +  val childColStatDate = ColumnStat(distinctCount = 10, min = Some(dMin), max = Some(dMax),
    +    nullCount = 0, avgLen = 4, maxLen = 4)
    +
    +  // Third column ctimestamp has 10 values from "2017-01-01 01:00:00" through
    +  // "2017-01-01 10:00:00" for 10 distinct timestamps (or hours).
    +  val tsMin = Timestamp.valueOf("2017-01-01 01:00:00")
    +  val tsMax = Timestamp.valueOf("2017-01-01 10:00:00")
    +  val arTimestamp = AttributeReference("ctimestamp", TimestampType)()
    +  val childColStatTimestamp = ColumnStat(distinctCount = 10, min = Some(tsMin), max = Some(tsMax),
    +    nullCount = 0, avgLen = 8, maxLen = 8)
    +
    +  // Fourth column cdecimal has 4 values from 0.20 through 0.80 at increment of 0.20.
    +  val decMin = new java.math.BigDecimal("0.200000000000000000")
    +  val decMax = new java.math.BigDecimal("0.800000000000000000")
    +  val arDecimal = AttributeReference("cdecimal", DecimalType(18, 18))()
    +  val childColStatDecimal = ColumnStat(distinctCount = 4, min = Some(decMin), max = Some(decMax),
    +    nullCount = 0, avgLen = 8, maxLen = 8)
    +
    +  // Fifth column cdouble has 10 double values: 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0
    +  val arDouble = AttributeReference("cdouble", DoubleType)()
    +  val childColStatDouble = ColumnStat(distinctCount = 10, min = Some(1.0), max = Some(10.0),
    +    nullCount = 0, avgLen = 8, maxLen = 8)
    +
    +  // Sixth column cstring has 10 String values:
    +  // "A0", "A1", "A2", "A3", "A4", "A5", "A6", "A7", "A8", "A9"
    +  val arString = AttributeReference("cstring", StringType)()
    +  val childColStatString = ColumnStat(distinctCount = 10, min = None, max = None,
    +    nullCount = 0, avgLen = 2, maxLen = 2)
    +
    +  test("cint = 2") {
    +    validateEstimatedStats(
    +      arInt,
    +      Filter(EqualTo(arInt, Literal(2)), childStatsTestPlan(Seq(arInt), 10L)),
    +      ColumnStat(distinctCount = 1, min = Some(2), max = Some(2),
    +        nullCount = 0, avgLen = 4, maxLen = 4),
    +      Some(1L)
    +    )
    +  }
    +
    +  test("cint = 0") {
    +    // This is an out-of-range case since 0 is outside the range [min, max]
    +    validateEstimatedStats(
    +      arInt,
    +      Filter(EqualTo(arInt, Literal(0)), childStatsTestPlan(Seq(arInt), 10L)),
    +      ColumnStat(distinctCount = 10, min = Some(1), max = Some(10),
    +        nullCount = 0, avgLen = 4, maxLen = 4),
    +      Some(0L)
    +    )
    +  }
    +
    +  test("cint < 3") {
    +    validateEstimatedStats(
    +      arInt,
    +      Filter(LessThan(arInt, Literal(3)), childStatsTestPlan(Seq(arInt), 10L)),
    +      ColumnStat(distinctCount = 2, min = Some(1), max = Some(3),
    +        nullCount = 0, avgLen = 4, maxLen = 4),
    +      Some(3L)
    +    )
    +  }
    +
    +  test("cint < 0") {
    +    // This is a corner case since literal 0 is smaller than min.
    +    validateEstimatedStats(
    +      arInt,
    +      Filter(LessThan(arInt, Literal(0)), childStatsTestPlan(Seq(arInt), 10L)),
    +      ColumnStat(distinctCount = 10, min = Some(1), max = Some(10),
    +        nullCount = 0, avgLen = 4, maxLen = 4),
    +      Some(0L)
    +    )
    +  }
    +
    +  test("cint <= 3") {
    +    validateEstimatedStats(
    +      arInt,
    +      Filter(LessThanOrEqual(arInt, Literal(3)), childStatsTestPlan(Seq(arInt), 10L)),
    +      ColumnStat(distinctCount = 2, min = Some(1), max = Some(3),
    +        nullCount = 0, avgLen = 4, maxLen = 4),
    +      Some(3L)
    +    )
    +  }
    +
    +  test("cint > 6") {
    +    validateEstimatedStats(
    +      arInt,
    +      Filter(GreaterThan(arInt, Literal(6)), childStatsTestPlan(Seq(arInt), 10L)),
    +      ColumnStat(distinctCount = 4, min = Some(6), max = Some(10),
    +        nullCount = 0, avgLen = 4, maxLen = 4),
    +      Some(5L)
    +    )
    +  }
    +
    +  test("cint > 10") {
    +    // This is a corner case since max value is 10.
    +    validateEstimatedStats(
    +      arInt,
    +      Filter(GreaterThan(arInt, Literal(10)), childStatsTestPlan(Seq(arInt), 10L)),
    +      ColumnStat(distinctCount = 10, min = Some(1), max = Some(10),
    +        nullCount = 0, avgLen = 4, maxLen = 4),
    +      Some(0L)
    +    )
    +  }
    +
    +  test("cint >= 6") {
    +    validateEstimatedStats(
    +      arInt,
    +      Filter(GreaterThanOrEqual(arInt, Literal(6)), childStatsTestPlan(Seq(arInt), 10L)),
    +      ColumnStat(distinctCount = 4, min = Some(6), max = Some(10),
    +        nullCount = 0, avgLen = 4, maxLen = 4),
    +      Some(5L)
    +    )
    +  }
    +
    +  test("cint IS NULL") {
    +    validateEstimatedStats(
    +      arInt,
    +      Filter(IsNull(arInt), childStatsTestPlan(Seq(arInt), 10L)),
    +      ColumnStat(distinctCount = 0, min = None, max = None,
    +        nullCount = 0, avgLen = 4, maxLen = 4),
    +      Some(0L)
    +    )
    +  }
    +
    +  test("cint IS NOT NULL") {
    +    validateEstimatedStats(
    +      arInt,
    +      Filter(IsNotNull(arInt), childStatsTestPlan(Seq(arInt), 10L)),
    +      ColumnStat(distinctCount = 10, min = Some(1), max = Some(10),
    +        nullCount = 0, avgLen = 4, maxLen = 4),
    +      Some(10L)
    +    )
    +  }
    +
    +  test("cint > 3 AND cint <= 6") {
    +    val condition = And(GreaterThan(arInt, Literal(3)), LessThanOrEqual(arInt, Literal(6)))
    +    validateEstimatedStats(
    +      arInt,
    +      Filter(condition, childStatsTestPlan(Seq(arInt), 10L)),
    +      ColumnStat(distinctCount = 3, min = Some(3), max = Some(6),
    +        nullCount = 0, avgLen = 4, maxLen = 4),
    +      Some(4L)
    +    )
    +  }
    +
    +  test("cint = 3 OR cint = 6") {
    +    val condition = Or(EqualTo(arInt, Literal(3)), EqualTo(arInt, Literal(6)))
    +    validateEstimatedStats(
    +      arInt,
    +      Filter(condition, childStatsTestPlan(Seq(arInt), 10L)),
    +      ColumnStat(distinctCount = 10, min = Some(1), max = Some(10),
    +        nullCount = 0, avgLen = 4, maxLen = 4),
    +      Some(2L)
    +    )
    +  }
    +
    +  test("cint IN (3, 4, 5)") {
    +    validateEstimatedStats(
    +      arInt,
    +      Filter(InSet(arInt, Set(3, 4, 5)), childStatsTestPlan(Seq(arInt), 10L)),
    +      ColumnStat(distinctCount = 3, min = Some(3), max = Some(5),
    +        nullCount = 0, avgLen = 4, maxLen = 4),
    +      Some(3L)
    +    )
    +  }
    +
    +  test("cint NOT IN (3, 4, 5)") {
    +    validateEstimatedStats(
    +      arInt,
    +      Filter(Not(InSet(arInt, Set(3, 4, 5))), childStatsTestPlan(Seq(arInt), 10L)),
    +      ColumnStat(distinctCount = 10, min = Some(1), max = Some(10),
    +        nullCount = 0, avgLen = 4, maxLen = 4),
    +      Some(7L)
    +    )
    +  }
    +
    +  test("cdate = cast('2017-01-02' AS DATE)") {
    +    val d20170102 = Date.valueOf("2017-01-02")
    +    validateEstimatedStats(
    +      arDate,
    +      Filter(EqualTo(arDate, Literal(d20170102)),
    +        childStatsTestPlan(Seq(arDate), 10L)),
    +      ColumnStat(distinctCount = 1, min = Some(d20170102), max = Some(d20170102),
    +        nullCount = 0, avgLen = 4, maxLen = 4),
    +      Some(1L)
    +    )
    +  }
    +
    +  test("cdate < cast('2017-01-03' AS DATE)") {
    +    val d20170103 = Date.valueOf("2017-01-03")
    +    validateEstimatedStats(
    +      arDate,
    +      Filter(LessThan(arDate, Literal(d20170103)),
    +        childStatsTestPlan(Seq(arDate), 10L)),
    +      ColumnStat(distinctCount = 2, min = Some(dMin), max = Some(d20170103),
    +        nullCount = 0, avgLen = 4, maxLen = 4),
    +      Some(3L)
    +    )
    +  }
    +
    +  test("""cdate IN ( cast('2017-01-03' AS DATE),
    +      cast('2017-01-04' AS DATE), cast('2017-01-05' AS DATE) )""") {
    +    val d20170103 = Date.valueOf("2017-01-03")
    +    val d20170104 = Date.valueOf("2017-01-04")
    +    val d20170105 = Date.valueOf("2017-01-05")
    +    validateEstimatedStats(
    +      arDate,
    +      Filter(In(arDate, Seq(Literal(d20170103), Literal(d20170104), Literal(d20170105))),
    +        childStatsTestPlan(Seq(arDate), 10L)),
    +      ColumnStat(distinctCount = 3, min = Some(d20170103), max = Some(d20170105),
    +        nullCount = 0, avgLen = 4, maxLen = 4),
    +      Some(3L)
    +    )
    +  }
    +
    +  test("ctimestamp = cast('2017-01-01 02:00:00' AS TIMESTAMP)") {
    +    val ts2017010102 = Timestamp.valueOf("2017-01-01 02:00:00")
    +    validateEstimatedStats(
    +      arTimestamp,
    +      Filter(EqualTo(arTimestamp, Literal(ts2017010102)),
    +        childStatsTestPlan(Seq(arTimestamp), 10L)),
    +      ColumnStat(distinctCount = 1, min = Some(ts2017010102), max = Some(ts2017010102),
    +        nullCount = 0, avgLen = 8, maxLen = 8),
    +      Some(1L)
    +    )
    +  }
    +
    +  test("ctimestamp < cast('2017-01-01 03:00:00' AS TIMESTAMP)") {
    +    val ts2017010103 = Timestamp.valueOf("2017-01-01 03:00:00")
    +    validateEstimatedStats(
    +      arTimestamp,
    +      Filter(LessThan(arTimestamp, Literal(ts2017010103)),
    +        childStatsTestPlan(Seq(arTimestamp), 10L)),
    +      ColumnStat(distinctCount = 2, min = Some(tsMin), max = Some(ts2017010103),
    +        nullCount = 0, avgLen = 8, maxLen = 8),
    +      Some(3L)
    +    )
    +  }
    +
    +  test("cdecimal = 0.400000000000000000") {
    +    val dec_0_40 = new java.math.BigDecimal("0.400000000000000000")
    +    validateEstimatedStats(
    +      arDecimal,
    +      Filter(EqualTo(arDecimal, Literal(dec_0_40)),
    +        childStatsTestPlan(Seq(arDecimal), 4L)),
    +      ColumnStat(distinctCount = 1, min = Some(dec_0_40), max = Some(dec_0_40),
    +        nullCount = 0, avgLen = 8, maxLen = 8),
    +      Some(1L)
    +    )
    +  }
    +
    +  test("cdecimal < 0.60 ") {
    +    val dec_0_60 = new java.math.BigDecimal("0.600000000000000000")
    +    validateEstimatedStats(
    +      arDecimal,
    +      Filter(LessThan(arDecimal, Literal(dec_0_60, DecimalType(12, 2))),
    +        childStatsTestPlan(Seq(arDecimal), 4L)),
    +      ColumnStat(distinctCount = 3, min = Some(decMin), max = Some(dec_0_60),
    +        nullCount = 0, avgLen = 8, maxLen = 8),
    +      Some(3L)
    +    )
    +  }
    +
    +  test("cdouble < 3.0") {
    +    validateEstimatedStats(
    +      arDouble,
    +      Filter(LessThan(arDouble, Literal(3.0)), childStatsTestPlan(Seq(arDouble), 10L)),
    +      ColumnStat(distinctCount = 2, min = Some(1.0), max = Some(3.0),
    +        nullCount = 0, avgLen = 8, maxLen = 8),
    +      Some(3L)
    +    )
    +  }
    +
    +  test("cstring = 'A2'") {
    +    validateEstimatedStats(
    +      arString,
    +      Filter(EqualTo(arString, Literal("A2")), childStatsTestPlan(Seq(arString), 10L)),
    +      ColumnStat(distinctCount = 1, min = None, max = None,
    +        nullCount = 0, avgLen = 2, maxLen = 2),
    +      Some(1L)
    +    )
    +  }
    +
    +  // There is no min/max statistics for String type.  We estimate 10 rows returned.
    +  test("cstring < 'A2'") {
    +    validateEstimatedStats(
    +      arString,
    +      Filter(LessThan(arString, Literal("A2")), childStatsTestPlan(Seq(arString), 10L)),
    +      ColumnStat(distinctCount = 10, min = None, max = None,
    +        nullCount = 0, avgLen = 2, maxLen = 2),
    +      Some(10L)
    +    )
    +  }
    +
    +  // This is a corner test case.  We want to test if we can handle the case when the number of
    +  // valid values in IN clause is greater than the number of distinct values for a given column.
    +  // For example, column has only 2 distinct values 1 and 6.
    +  // The predicate is: column IN (1, 2, 3, 4, 5).
    +  test("cint IN (1, 2, 3, 4, 5)") {
    +    val cornerChildColStatInt = ColumnStat(distinctCount = 2, min = Some(1), max = Some(6),
    +      nullCount = 0, avgLen = 4, maxLen = 4)
    +    val cornerChildStatsTestplan = StatsTestPlan(
    +      outputList = Seq(arInt),
    +      rowCount = 2L,
    +      attributeStats = AttributeMap(Seq(arInt -> cornerChildColStatInt))
    +    )
    +    validateEstimatedStats(
    +      arInt,
    +      Filter(InSet(arInt, Set(1, 2, 3, 4, 5)), cornerChildStatsTestplan),
    +      ColumnStat(distinctCount = 2, min = Some(1), max = Some(5),
    +        nullCount = 0, avgLen = 4, maxLen = 4),
    +      Some(2L)
    +    )
    +  }
    +
    +  private def childStatsTestPlan(outList: Seq[Attribute], tableRowCount: BigInt): StatsTestPlan = {
    +    StatsTestPlan(
    +      outputList = outList,
    +      rowCount = tableRowCount,
    +      attributeStats = AttributeMap(Seq(
    +        arInt -> childColStatInt,
    +        arDate -> childColStatDate,
    +        arTimestamp -> childColStatTimestamp,
    +        arDecimal -> childColStatDecimal,
    +        arDouble -> childColStatDouble,
    +        arString -> childColStatString
    +      ))
    +    )
    +  }
    +
    +  private def validateEstimatedStats(
    +      ar: AttributeReference,
    +      filterNode: Filter,
    +      expectedColStats: ColumnStat,
    +      rowCount: Option[BigInt] = None)
    --- End diff --
    
    use `BigInt` please, all the callers pass a `Some(value)`


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