[GitHub] [iceberg] szehon-ho commented on a change in pull request #3862: Spark: Supports partition management in V2 Catalog

[GitBox <gi...@apache.org>]

szehon-ho commented on a change in pull request #3862:
URL: https://github.com/apache/iceberg/pull/3862#discussion_r813470752



##########
File path: spark/v3.2/spark/src/main/java/org/apache/iceberg/spark/source/SparkTable.java
##########
@@ -272,6 +283,65 @@ public void deleteWhere(Filter[] filters) {
     }
   }
 
+  @Override
+  public StructType partitionSchema() {
+    return (StructType) SparkSchemaUtil.convert(Partitioning.partitionType(table()));
+  }
+
+  @Override
+  public void createPartition(InternalRow ident, Map<String, String> properties) throws UnsupportedOperationException {
+    throw new UnsupportedOperationException("Cannot explicitly create partitions in Iceberg tables");
+  }
+
+  @Override
+  public boolean dropPartition(InternalRow ident) {
+    throw new UnsupportedOperationException("Cannot explicitly drop partitions in Iceberg tables");
+  }
+
+  @Override
+  public void replacePartitionMetadata(InternalRow ident, Map<String, String> properties)
+          throws UnsupportedOperationException {
+    throw new UnsupportedOperationException("Iceberg partitions do not support metadata");
+  }
+
+  @Override
+  public Map<String, String> loadPartitionMetadata(InternalRow ident) throws UnsupportedOperationException {
+    throw new UnsupportedOperationException("Iceberg partitions do not support metadata");
+  }
+
+  @Override
+  public InternalRow[] listPartitionIdentifiers(String[] names, InternalRow ident) {
+    // support show partitions
+    List<InternalRow> rows = Lists.newArrayList();
+    Dataset<Row> df = SparkTableUtil.loadMetadataTable(sparkSession(), icebergTable, MetadataTableType.PARTITIONS);
+    if (names.length > 0) {
+      StructType schema = partitionSchema();
+      df.collectAsList().forEach(row -> {
+        GenericRowWithSchema genericRow = (GenericRowWithSchema) row.apply(0);
+        boolean exits = true;
+        int index = 0;
+        while (index < names.length) {
+          DataType dataType = schema.apply(names[index]).dataType();

Review comment:
       Yea I think if we can have it be a light wrapper for metadata 'partition' table, it will be better (instead of Partioning.partitionType to get the schma), is it possible here?  




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