[GitHub] [incubator-paimon] JingsongLi commented on a diff in pull request #1836: [Spark] Spark supports PARTITION MANAGEMENT

["JingsongLi (via GitHub)" <gi...@apache.org>]

JingsongLi commented on code in PR #1836:
URL: https://github.com/apache/incubator-paimon/pull/1836#discussion_r1296938201


##########
paimon-spark/paimon-spark-common/src/main/java/org/apache/paimon/spark/SparkTable.java:
##########
@@ -137,4 +153,97 @@ public Map<String, String> properties() {
             return Collections.emptyMap();
         }
     }
+
+    @Override
+    public StructType partitionSchema() {
+        List<String> partitionKeys = table.partitionKeys();
+        RowType rowType =
+                new RowType(
+                        table.rowType().getFields().stream()
+                                .filter(dataField -> partitionKeys.contains(dataField.name()))
+                                .collect(Collectors.toList()));
+        return SparkTypeUtils.fromPaimonRowType(rowType);
+    }
+
+    @Override
+    public void createPartition(InternalRow internalRow, Map<String, String> map)
+            throws PartitionsAlreadyExistException, UnsupportedOperationException {
+        throw new UnsupportedOperationException();
+    }
+
+    @Override
+    public boolean dropPartition(InternalRow internalRow) {
+        StructType structType = partitionSchema();
+        StructField[] fields = structType.fields();
+        HashMap<String, String> partitions = new HashMap<>();

Review Comment:
   Can you use `RowDataPartitionComputer` here?
   
   And we can convert internalRow to paimon `SparkRow`.



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