HIVE-29332: StatsUtils to stop using "0" defaults on numeric columns without optional high/low info

ql/src/java/org/apache/hadoop/hive/ql/ddl/ShowUtils.java

@@ -189,15 +189,19 @@ public static String[] extractColumnValues(FieldSchema column, boolean isColumnS
           }
         } else if (statsData.isSetDoubleStats()) {
           DoubleColumnStatsData doubleStats = statsData.getDoubleStats();
-          values.addAll(Lists.newArrayList("" + doubleStats.getLowValue(), "" + doubleStats.getHighValue(),
+          String lowVal = doubleStats.isSetLowValue() ? "" + doubleStats.getLowValue() : "";
+          String highVal = doubleStats.isSetHighValue() ? "" + doubleStats.getHighValue() : "";
+          values.addAll(Lists.newArrayList(lowVal, highVal,
               "" + doubleStats.getNumNulls(), "" + doubleStats.getNumDVs(), "", "", "", "",
               convertToString(doubleStats.getBitVectors())));
           if (histogramEnabled) {
             values.add(convertHistogram(statsData.getDoubleStats().getHistogram(), statsData.getSetField()));
           }
         } else if (statsData.isSetLongStats()) {
           LongColumnStatsData longStats = statsData.getLongStats();
-          values.addAll(Lists.newArrayList("" + longStats.getLowValue(), "" + longStats.getHighValue(),
+          String lowVal = longStats.isSetLowValue() ? "" + longStats.getLowValue() : "";
+          String highVal = longStats.isSetHighValue() ? "" + longStats.getHighValue() : "";
+          values.addAll(Lists.newArrayList(lowVal, highVal,
               "" + longStats.getNumNulls(), "" + longStats.getNumDVs(), "", "", "", "",
               convertToString(longStats.getBitVectors())));
           if (histogramEnabled) {

ql/src/java/org/apache/hadoop/hive/ql/ddl/table/info/desc/DescTableOperation.java

@@ -249,7 +249,7 @@ private void getColumnDataForPartitionKeyColumn(Table table, List<FieldSchema> c
     ColStatistics.Range r = cs.getRange();
     StatObjectConverter.fillColumnStatisticsData(partCol.getType(), data, r == null ? null : r.minValue,
         r == null ? null : r.maxValue, r == null ? null : r.minValue, r == null ? null : r.maxValue,
-        r == null ? null : r.minValue.toString(), r == null ? null : r.maxValue.toString(),
+        r == null || r.minValue == null ? null : r.minValue.toString(), r == null || r.maxValue == null ? null : r.maxValue.toString(),
         cs.getNumNulls(), cs.getCountDistint(), null, null, cs.getAvgColLen(),
         cs.getAvgColLen(), cs.getNumTrues(), cs.getNumFalses());
     ColumnStatisticsObj cso = new ColumnStatisticsObj(partCol.getName(), partCol.getType(), data);

ql/src/java/org/apache/hadoop/hive/ql/stats/StatsUtils.java

@@ -799,33 +799,13 @@ public static ColStatistics getColStatistics(ColumnStatisticsObj cso, String col
     if (colTypeLowerCase.equals(serdeConstants.TINYINT_TYPE_NAME)
         || colTypeLowerCase.equals(serdeConstants.SMALLINT_TYPE_NAME)
         || colTypeLowerCase.equals(serdeConstants.INT_TYPE_NAME)) {
-      cs.setCountDistint(csd.getLongStats().getNumDVs());
-      cs.setNumNulls(csd.getLongStats().getNumNulls());
-      cs.setAvgColLen(JavaDataModel.get().primitive1());
-      cs.setRange(csd.getLongStats().getLowValue(), csd.getLongStats().getHighValue());
-      cs.setBitVectors(csd.getLongStats().getBitVectors());
-      cs.setHistogram(csd.getLongStats().getHistogram());
+      populateColStatisticsFromLongStats(csd.getLongStats(), cs, JavaDataModel.get().primitive1());
     } else if (colTypeLowerCase.equals(serdeConstants.BIGINT_TYPE_NAME)) {
-      cs.setCountDistint(csd.getLongStats().getNumDVs());
-      cs.setNumNulls(csd.getLongStats().getNumNulls());
-      cs.setAvgColLen(JavaDataModel.get().primitive2());
-      cs.setRange(csd.getLongStats().getLowValue(), csd.getLongStats().getHighValue());
-      cs.setBitVectors(csd.getLongStats().getBitVectors());
-      cs.setHistogram(csd.getLongStats().getHistogram());
+      populateColStatisticsFromLongStats(csd.getLongStats(), cs, JavaDataModel.get().primitive2());
     } else if (colTypeLowerCase.equals(serdeConstants.FLOAT_TYPE_NAME)) {
-      cs.setCountDistint(csd.getDoubleStats().getNumDVs());
-      cs.setNumNulls(csd.getDoubleStats().getNumNulls());
-      cs.setAvgColLen(JavaDataModel.get().primitive1());
-      cs.setRange(csd.getDoubleStats().getLowValue(), csd.getDoubleStats().getHighValue());
-      cs.setBitVectors(csd.getDoubleStats().getBitVectors());
-      cs.setHistogram(csd.getDoubleStats().getHistogram());
+      populateColStatisticsFromDoubleStats(csd.getDoubleStats(), cs, JavaDataModel.get().primitive1());
     } else if (colTypeLowerCase.equals(serdeConstants.DOUBLE_TYPE_NAME)) {
-      cs.setCountDistint(csd.getDoubleStats().getNumDVs());
-      cs.setNumNulls(csd.getDoubleStats().getNumNulls());
-      cs.setAvgColLen(JavaDataModel.get().primitive2());
-      cs.setRange(csd.getDoubleStats().getLowValue(), csd.getDoubleStats().getHighValue());
-      cs.setBitVectors(csd.getDoubleStats().getBitVectors());
-      cs.setHistogram(csd.getDoubleStats().getHistogram());
+      populateColStatisticsFromDoubleStats(csd.getDoubleStats(), cs, JavaDataModel.get().primitive2());
     } else if (colTypeLowerCase.equals(serdeConstants.STRING_TYPE_NAME)
         || colTypeLowerCase.startsWith(serdeConstants.CHAR_TYPE_NAME)
         || colTypeLowerCase.startsWith(serdeConstants.VARCHAR_TYPE_NAME)) {
@@ -894,6 +874,34 @@ public static ColStatistics getColStatistics(ColumnStatisticsObj cso, String col
     return cs;
   }
 
+  // Populate ColStatistics from LongColumnStatsData, checking isSet for optional i64 fields
+  private static void populateColStatisticsFromLongStats(
+      org.apache.hadoop.hive.metastore.api.LongColumnStatsData longStats,
+      ColStatistics cs, double avgColLen) {
+    cs.setCountDistint(longStats.getNumDVs());
+    cs.setNumNulls(longStats.getNumNulls());
+    cs.setAvgColLen(avgColLen);
+    Long lowVal = longStats.isSetLowValue() ? longStats.getLowValue() : null;
+    Long highVal = longStats.isSetHighValue() ? longStats.getHighValue() : null;
+    cs.setRange(lowVal, highVal);
+    cs.setBitVectors(longStats.getBitVectors());
+    cs.setHistogram(longStats.getHistogram());
+  }
+
+  // Populate ColStatistics from DoubleColumnStatsData, checking isSet for optional double fields
+  private static void populateColStatisticsFromDoubleStats(
+      org.apache.hadoop.hive.metastore.api.DoubleColumnStatsData doubleStats,
+      ColStatistics cs, double avgColLen) {
+    cs.setCountDistint(doubleStats.getNumDVs());
+    cs.setNumNulls(doubleStats.getNumNulls());
+    cs.setAvgColLen(avgColLen);
+    Double lowVal = doubleStats.isSetLowValue() ? doubleStats.getLowValue() : null;
+    Double highVal = doubleStats.isSetHighValue() ? doubleStats.getHighValue() : null;
+    cs.setRange(lowVal, highVal);
+    cs.setBitVectors(doubleStats.getBitVectors());
+    cs.setHistogram(doubleStats.getHistogram());
+  }
+
   private static ColStatistics estimateColStats(long numRows, String colName, HiveConf conf,
       List<ColumnInfo> schema) {
     ColumnInfo cinfo = getColumnInfoForColumn(colName, schema);

ql/src/test/org/apache/hadoop/hive/ql/ddl/TestShowUtils.java

@@ -0,0 +1,150 @@
+/*
+ * 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.hadoop.hive.ql.ddl;
+
+import static org.junit.jupiter.api.Assertions.assertEquals;
+import static org.junit.jupiter.api.Assertions.assertNotNull;
+
+import java.util.stream.Stream;
+
+import org.apache.hadoop.hive.metastore.api.ColumnStatisticsData;
+import org.apache.hadoop.hive.metastore.api.ColumnStatisticsObj;
+import org.apache.hadoop.hive.metastore.api.DoubleColumnStatsData;
+import org.apache.hadoop.hive.metastore.api.FieldSchema;
+import org.apache.hadoop.hive.metastore.api.LongColumnStatsData;
+import org.apache.hadoop.hive.serde.serdeConstants;
+import org.junit.jupiter.params.ParameterizedTest;
+import org.junit.jupiter.params.provider.Arguments;
+import org.junit.jupiter.params.provider.MethodSource;
+
+public class TestShowUtils {
+
+  @ParameterizedTest(name = "{0} - {1}")
+  @MethodSource("longStatsTestData")
+  public void testExtractColumnValues_LongStats(String typeName, String scenarioName,
+      Long lowValue, Long highValue, String expectedMin, String expectedMax) {
+    FieldSchema column = new FieldSchema("test_col", typeName, null);
+
+    ColumnStatisticsObj cso = new ColumnStatisticsObj();
+    cso.setColName("test_col");
+    cso.setColType(typeName);
+
+    LongColumnStatsData longStats = new LongColumnStatsData();
+    longStats.setNumDVs(100);
+    longStats.setNumNulls(10);
+    if (lowValue != null) {
+      longStats.setLowValue(lowValue);
+    }
+    if (highValue != null) {
+      longStats.setHighValue(highValue);
+    }
+
+    ColumnStatisticsData data = new ColumnStatisticsData();
+    data.setLongStats(longStats);
+    cso.setStatsData(data);
+
+    String[] result = ShowUtils.extractColumnValues(column, true, cso, false);
+
+    assertNotNull(result, "Result array should not be null");
+    assertEquals("test_col", result[0], "Column name mismatch");
+    assertEquals(typeName, result[1], "Column type mismatch");
+    assertEquals(expectedMin, result[2], "Min value mismatch");
+    assertEquals(expectedMax, result[3], "Max value mismatch");
+    assertEquals("10", result[4], "NumNulls mismatch");
+    assertEquals("100", result[5], "NumDVs mismatch");
+  }
+
+  @ParameterizedTest(name = "{0} - {1}")
+  @MethodSource("doubleStatsTestData")
+  public void testExtractColumnValues_DoubleStats(String typeName, String scenarioName,
+      Double lowValue, Double highValue, String expectedMin, String expectedMax) {
+    FieldSchema column = new FieldSchema("test_col", typeName, null);
+
+    ColumnStatisticsObj cso = new ColumnStatisticsObj();
+    cso.setColName("test_col");
+    cso.setColType(typeName);
+
+    DoubleColumnStatsData doubleStats = new DoubleColumnStatsData();
+    doubleStats.setNumDVs(100);
+    doubleStats.setNumNulls(10);
+    if (lowValue != null) {
+      doubleStats.setLowValue(lowValue);
+    }
+    if (highValue != null) {
+      doubleStats.setHighValue(highValue);
+    }
+
+    ColumnStatisticsData data = new ColumnStatisticsData();
+    data.setDoubleStats(doubleStats);
+    cso.setStatsData(data);
+
+    String[] result = ShowUtils.extractColumnValues(column, true, cso, false);
+
+    assertNotNull(result, "Result array should not be null");
+    assertEquals("test_col", result[0], "Column name mismatch");
+    assertEquals(typeName, result[1], "Column type mismatch");
+    assertEquals(expectedMin, result[2], "Min value mismatch");
+    assertEquals(expectedMax, result[3], "Max value mismatch");
+    assertEquals("10", result[4], "NumNulls mismatch");
+    assertEquals("100", result[5], "NumDVs mismatch");
+  }
+
+  static Stream<Arguments> longStatsTestData() {
+    return Stream.of(
+      // {typeName, scenarioName, lowValue, highValue, expectedMin, expectedMax}
+      Arguments.of(serdeConstants.TINYINT_TYPE_NAME, "BothValuesSet", 1L, 1000L, "1", "1000"),
+      Arguments.of(serdeConstants.TINYINT_TYPE_NAME, "NoValuesSet", null, null, "", ""),
+      Arguments.of(serdeConstants.TINYINT_TYPE_NAME, "OnlyLowValueSet", 100L, null, "100", ""),
+      Arguments.of(serdeConstants.TINYINT_TYPE_NAME, "OnlyHighValueSet", null, 1000L, "", "1000"),
+      Arguments.of(serdeConstants.TINYINT_TYPE_NAME, "NegativeHighValueOnly", null, -5L, "", "-5"),
+      Arguments.of(serdeConstants.SMALLINT_TYPE_NAME, "BothValuesSet", 1L, 1000L, "1", "1000"),
+      Arguments.of(serdeConstants.SMALLINT_TYPE_NAME, "NoValuesSet", null, null, "", ""),
+      Arguments.of(serdeConstants.SMALLINT_TYPE_NAME, "OnlyLowValueSet", 100L, null, "100", ""),
+      Arguments.of(serdeConstants.SMALLINT_TYPE_NAME, "OnlyHighValueSet", null, 1000L, "", "1000"),
+      Arguments.of(serdeConstants.SMALLINT_TYPE_NAME, "NegativeHighValueOnly", null, -5L, "", "-5"),
+      Arguments.of(serdeConstants.INT_TYPE_NAME, "BothValuesSet", 1L, 1000L, "1", "1000"),
+      Arguments.of(serdeConstants.INT_TYPE_NAME, "NoValuesSet", null, null, "", ""),
+      Arguments.of(serdeConstants.INT_TYPE_NAME, "OnlyLowValueSet", 100L, null, "100", ""),
+      Arguments.of(serdeConstants.INT_TYPE_NAME, "OnlyHighValueSet", null, 1000L, "", "1000"),
+      Arguments.of(serdeConstants.INT_TYPE_NAME, "NegativeHighValueOnly", null, -5L, "", "-5"),
+      Arguments.of(serdeConstants.BIGINT_TYPE_NAME, "BothValuesSet", 1L, 1000L, "1", "1000"),
+      Arguments.of(serdeConstants.BIGINT_TYPE_NAME, "NoValuesSet", null, null, "", ""),
+      Arguments.of(serdeConstants.BIGINT_TYPE_NAME, "OnlyLowValueSet", 100L, null, "100", ""),
+      Arguments.of(serdeConstants.BIGINT_TYPE_NAME, "OnlyHighValueSet", null, 1000L, "", "1000"),
+      Arguments.of(serdeConstants.BIGINT_TYPE_NAME, "NegativeHighValueOnly", null, -5L, "", "-5")
+    );
+  }
+
+  static Stream<Arguments> doubleStatsTestData() {
+    return Stream.of(
+      // {typeName, scenarioName, lowValue, highValue, expectedMin, expectedMax}
+      Arguments.of(serdeConstants.FLOAT_TYPE_NAME, "BothValuesSet", 1.5, 1000.5, "1.5", "1000.5"),
+      Arguments.of(serdeConstants.FLOAT_TYPE_NAME, "NoValuesSet", null, null, "", ""),
+      Arguments.of(serdeConstants.FLOAT_TYPE_NAME, "OnlyLowValueSet", 100.5, null, "100.5", ""),
+      Arguments.of(serdeConstants.FLOAT_TYPE_NAME, "OnlyHighValueSet", null, 1000.5, "", "1000.5"),
+      Arguments.of(serdeConstants.FLOAT_TYPE_NAME, "NegativeHighValueOnly", null, -5.5, "", "-5.5"),
+      Arguments.of(serdeConstants.DOUBLE_TYPE_NAME, "BothValuesSet", 1.5, 1000.5, "1.5", "1000.5"),
+      Arguments.of(serdeConstants.DOUBLE_TYPE_NAME, "NoValuesSet", null, null, "", ""),
+      Arguments.of(serdeConstants.DOUBLE_TYPE_NAME, "OnlyLowValueSet", 100.5, null, "100.5", ""),
+      Arguments.of(serdeConstants.DOUBLE_TYPE_NAME, "OnlyHighValueSet", null, 1000.5, "", "1000.5"),
+      Arguments.of(serdeConstants.DOUBLE_TYPE_NAME, "NegativeHighValueOnly", null, -5.5, "", "-5.5")
+    );
+  }
+
+}