rdblue commented on code in PR #6622:
URL: https://github.com/apache/iceberg/pull/6622#discussion_r1094817232


##########
spark/v3.3/spark/src/main/java/org/apache/iceberg/spark/source/SparkScanBuilder.java:
##########
@@ -158,6 +182,141 @@ public Filter[] pushedFilters() {
     return pushedFilters;
   }
 
+  @Override
+  public boolean pushAggregation(Aggregation aggregation) {
+    if (!pushDownAggregate(aggregation)) {
+      return false;
+    }
+
+    AggregateEvaluator aggregateEvaluator;
+    try {
+      List<Expression> aggregates =
+          Arrays.stream(aggregation.aggregateExpressions())
+              .map(agg -> SparkAggregates.convert(agg))
+              .collect(Collectors.toList());
+      aggregateEvaluator = AggregateEvaluator.create(schema, aggregates);
+    } catch (Exception e) {
+      LOG.info("Can't push down aggregates: " + e.getMessage());
+      return false;
+    }
+
+    if 
(!metricsModeSupportsAggregatePushDown(aggregateEvaluator.aggregates())) {
+      LOG.info("The MetricsMode doesn't support aggregate push down.");
+      return false;
+    }
+
+    List<ManifestFile> manifests = getSnapshot().allManifests(table.io());
+
+    for (ManifestFile manifest : manifests) {
+      try (ManifestReader<DataFile> reader = ManifestFiles.read(manifest, 
table.io())) {
+        for (DataFile dataFile : reader) {
+          aggregateEvaluator.update(dataFile.copy());
+        }
+      } catch (IOException e) {
+        LOG.info("Can't push down aggregates: " + e.getMessage());
+        return false;
+      }
+    }
+
+    Object[] res = aggregateEvaluator.result();
+    applyDataTypeConversionIfNecessary(res);
+
+    List<Object> valuesInSparkInternalRow = java.util.Arrays.asList(res);
+    this.pushedAggregateRows = new InternalRow[1];
+    pushedAggregateRows[0] =
+        
InternalRow.fromSeq(JavaConverters.asScalaBuffer(valuesInSparkInternalRow).toSeq());

Review Comment:
   There's a wrapper that we can use so we don't need to convert to Scala, 
`StructInternalRow`. That would also handle conversion to Spark 
representations, like `UTF8String`.



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