Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/16395#discussion_r101655531
--- Diff:
sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/statsEstimation/FilterEstimationSuite.scala
---
@@ -0,0 +1,376 @@
+/*
+ * 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 cdate has 10 values from 0.20 through 2.00 at increment
of 0.2.
+ val decMin = new java.math.BigDecimal("0.200000000000000000")
+ val decMax = new java.math.BigDecimal("2.000000000000000000")
+ val arDecimal = AttributeReference("cdecimal", DecimalType(12, 2))()
+ val childColStatDecimal = ColumnStat(distinctCount = 10, min =
Some(decMin), max = Some(decMax),
+ nullCount = 0, avgLen = 8, maxLen = 8)
+
+ // Fifth column cfloat has 10 float values: 1.0, 2.0, 3.0, 4.0, 5.0,
6.0, 7.0, 8.0, 9.0, 10.0
+ val arFloat = AttributeReference("cfloat", FloatType)()
+ val childColStatFloat = ColumnStat(distinctCount = 10, min = Some(1.0),
max = Some(10.0),
+ nullCount = 0, avgLen = 4, maxLen = 4)
+
+ // Sixth 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", FloatType)()
--- End diff --
DoubleType
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