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https://issues.apache.org/jira/browse/DRILL-7491?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17015052#comment-17015052
 ] 

ASF GitHub Bot commented on DRILL-7491:
---------------------------------------

arina-ielchiieva commented on pull request #1955: DRILL-7491: Incorrect count() 
returned for complex types in parquet
URL: https://github.com/apache/drill/pull/1955#discussion_r366310138
 
 

 ##########
 File path: 
exec/java-exec/src/main/java/org/apache/drill/exec/physical/base/AbstractGroupScanWithMetadata.java
 ##########
 @@ -167,29 +167,43 @@ public boolean isMatchAllMetadata() {
    */
   @Override
   public long getColumnValueCount(SchemaPath column) {
-    long tableRowCount, colNulls;
-    Long nulls;
     ColumnStatistics<?> columnStats = 
getTableMetadata().getColumnStatistics(column);
-    ColumnStatistics<?> nonInterestingColStats = null;
-    if (columnStats == null) {
-      nonInterestingColStats = 
getNonInterestingColumnsMetadata().getColumnStatistics(column);
-    }
+    ColumnStatistics<?> nonInterestingColStats = (columnStats == null)
+        ? getNonInterestingColumnsMetadata().getColumnStatistics(column) : 
null;
 
+    long tableRowCount;
     if (columnStats != null) {
       tableRowCount = 
TableStatisticsKind.ROW_COUNT.getValue(getTableMetadata());
     } else if (nonInterestingColStats != null) {
       tableRowCount = 
TableStatisticsKind.ROW_COUNT.getValue(getNonInterestingColumnsMetadata());
+      columnStats = nonInterestingColStats;
+    } else if (existsNestedStatsForColumn(column, getTableMetadata())
+        || existsNestedStatsForColumn(column, 
getNonInterestingColumnsMetadata())) {
+      return Statistic.NO_COLUMN_STATS;
     } else {
       return 0; // returns 0 if the column doesn't exist in the table.
     }
 
-    columnStats = columnStats != null ? columnStats : nonInterestingColStats;
-    nulls = ColumnStatisticsKind.NULLS_COUNT.getFrom(columnStats);
-    colNulls = nulls != null ? nulls : Statistic.NO_COLUMN_STATS;
+    Long nulls = ColumnStatisticsKind.NULLS_COUNT.getFrom(columnStats);
+    if (nulls == null || Statistic.NO_COLUMN_STATS == nulls || 
Statistic.NO_COLUMN_STATS == tableRowCount) {
+      return Statistic.NO_COLUMN_STATS;
+    } else {
+      return tableRowCount - nulls;
+    }
+  }
 
-    return Statistic.NO_COLUMN_STATS == tableRowCount
-            || Statistic.NO_COLUMN_STATS == colNulls
-            ? Statistic.NO_COLUMN_STATS : tableRowCount - colNulls;
+  /**
+   * For complex columns, stats may be present only for nested fields. For 
example, a column path is `a`,
+   * but stats present for `a`.`b`. So before making a decision that column is 
absent, the case needs
+   * to be tested.
+   *
+   * @param column   column path
+   * @param metadata metadata with column statistics
+   * @return whether stats exists for nested fields
+   */
+  private boolean existsNestedStatsForColumn(SchemaPath column, Metadata 
metadata) {
 
 Review comment:
   I am not quite sure I follow this method logic because when you call this 
method you return that there is no statistics is present but method states that 
it checks that nested column statistics exists. I guess we might need to rename 
method to depict exactly what it does, for example checking if column exists.
   By the way, if stats for nested column exists, can we use it for calculation?
   
 
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> Incorrect count() returned for complex types in parquet
> -------------------------------------------------------
>
>                 Key: DRILL-7491
>                 URL: https://issues.apache.org/jira/browse/DRILL-7491
>             Project: Apache Drill
>          Issue Type: Bug
>          Components: Functions - Drill, Functions - Hive, Storage - Parquet
>    Affects Versions: 1.16.0, 1.17.0
>            Reporter: Igor Guzenko
>            Assignee: Igor Guzenko
>            Priority: Major
>             Fix For: 1.18.0
>
>         Attachments: hive_alltypes.parquet
>
>
> To reproduce use the attached file for {{hive_alltypes.parquet}} (this is 
> parquet file generated by Hive) and try count on columns *c13 - c15.*  For 
> example, 
> {code:sql}
> SELECT count(c13) FROM dfs.tmp.`hive_alltypes.parquet`
> {code}
> *Expected result:* {color:green}3 {color}
> *Actual result:* {color:red}0{color}



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