okumin commented on a change in pull request #1531:
URL: https://github.com/apache/hive/pull/1531#discussion_r501697579



##########
File path: 
ql/src/java/org/apache/hadoop/hive/ql/optimizer/stats/annotation/StatsRulesProcFactory.java
##########
@@ -2921,6 +2920,97 @@ public Object process(Node nd, Stack<Node> stack, 
NodeProcessorCtx procCtx,
     }
   }
 
+  /**
+   * LateralViewJoinOperator changes the data size and column level statistics.
+   *
+   * A diagram of LATERAL VIEW.
+   *
+   *   [Lateral View Forward]
+   *          /     \
+   *    [Select]  [Select]
+   *        |        |
+   *        |     [UDTF]
+   *        \       /
+   *   [Lateral View Join]
+   *
+   * For each row of the source, the left branch just picks columns and the 
right branch processes UDTF.
+   * And then LVJ joins a row from the left branch with rows from the right 
branch.
+   * The join has one-to-many relationship since UDTF can generate multiple 
rows.
+   *
+   * This rule multiplies the stats from the left branch by T(right) / T(left) 
and sums up the both sides.
+   */
+  public static class LateralViewJoinStatsRule extends DefaultStatsRule 
implements SemanticNodeProcessor {
+    @Override
+    public Object process(Node nd, Stack<Node> stack, NodeProcessorCtx procCtx,
+                          Object... nodeOutputs) throws SemanticException {
+      final LateralViewJoinOperator lop = (LateralViewJoinOperator) nd;
+      final AnnotateStatsProcCtx aspCtx = (AnnotateStatsProcCtx) procCtx;
+      final HiveConf conf = aspCtx.getConf();
+
+      if (!isAllParentsContainStatistics(lop)) {
+        return null;
+      }
+
+      final List<Operator<? extends OperatorDesc>> parents = 
lop.getParentOperators();
+      if (parents.size() != 2) {
+        LOG.warn("LateralViewJoinOperator should have just two parents but 
actually has "
+                + parents.size() + " parents.");
+        return null;
+      }
+
+      final Statistics selectStats = 
parents.get(LateralViewJoinOperator.SELECT_TAG).getStatistics();
+      final Statistics udtfStats = 
parents.get(LateralViewJoinOperator.UDTF_TAG).getStatistics();
+
+      final double factor = (double) udtfStats.getNumRows() / (double) 
selectStats.getNumRows();
+      final long selectDataSize = 
StatsUtils.safeMult(selectStats.getDataSize(), factor);
+      final long dataSize = StatsUtils.safeAdd(selectDataSize, 
udtfStats.getDataSize());
+      Statistics joinedStats = new Statistics(udtfStats.getNumRows(), 
dataSize, 0, 0);
+
+      if (satisfyPrecondition(selectStats) && satisfyPrecondition(udtfStats)) {
+        final Map<String, ExprNodeDesc> columnExprMap = lop.getColumnExprMap();
+        final RowSchema schema = lop.getSchema();
+
+        joinedStats.updateColumnStatsState(selectStats.getColumnStatsState());
+        final List<ColStatistics> selectColStats = StatsUtils
+                .getColStatisticsFromExprMap(conf, selectStats, columnExprMap, 
schema);
+        joinedStats.addToColumnStats(multiplyColStats(selectColStats, factor));
+
+        joinedStats.updateColumnStatsState(udtfStats.getColumnStatsState());
+        final List<ColStatistics> udtfColStats = StatsUtils
+                .getColStatisticsFromExprMap(conf, udtfStats, columnExprMap, 
schema);
+        joinedStats.addToColumnStats(udtfColStats);
+
+        joinedStats = applyRuntimeStats(aspCtx.getParseContext().getContext(), 
joinedStats, lop);
+        lop.setStatistics(joinedStats);
+
+        if (LOG.isDebugEnabled()) {
+          LOG.debug("[0] STATS-" + lop.toString() + ": " + 
joinedStats.extendedToString());
+        }
+      } else {
+        joinedStats = applyRuntimeStats(aspCtx.getParseContext().getContext(), 
joinedStats, lop);
+        lop.setStatistics(joinedStats);
+
+        if (LOG.isDebugEnabled()) {
+          LOG.debug("[1] STATS-" + lop.toString() + ": " + 
joinedStats.extendedToString());
+        }
+      }
+      return null;
+    }
+
+    private List<ColStatistics> multiplyColStats(List<ColStatistics> 
colStatistics, double factor) {
+      for (ColStatistics colStats : colStatistics) {
+        colStats.setNumFalses(StatsUtils.safeMult(colStats.getNumFalses(), 
factor));
+        colStats.setNumTrues(StatsUtils.safeMult(colStats.getNumTrues(), 
factor));
+        colStats.setNumNulls(StatsUtils.safeMult(colStats.getNumNulls(), 
factor));
+        // When factor > 1, the same records are duplicated and countDistinct 
never changes.
+        if (factor < 1.0) {
+          
colStats.setCountDistint(StatsUtils.safeMult(colStats.getCountDistint(), 
factor));

Review comment:
       Ceiled. I moved this method since I'd like to reuse it for HIVE-24240.
   
https://github.com/apache/hive/commit/50396346eaed5d6bab4ff87dd079918a769a7ebd




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