Antalya 26.1: Fix view over iceberg

src/Storages/ObjectStorage/StorageObjectStorageSource.cpp

@@ -18,6 +18,8 @@
 #include <Interpreters/Context.h>
 #include <Interpreters/ExpressionActions.h>
 #include <Interpreters/convertFieldToType.h>
+#include <Parsers/ExpressionListParsers.h>
+#include <Parsers/parseQuery.h>
 #include <Processors/Executors/PullingPipelineExecutor.h>
 #include <Processors/Formats/Impl/ParquetMetadataCache.h>
 #include <Processors/Sources/ConstChunkGenerator.h>
@@ -770,6 +772,12 @@ StorageObjectStorageSource::ReaderHolder StorageObjectStorageSource::createReade
                 if (!column.second.second.type->isNullable())
                     continue;
 
+                /// With View over Iceberg table we have someting like 'materialize(time)' as column_name
+                ParserExpression parser;
+                ASTPtr expr = parseQuery(parser, column_name, 0, DBMS_DEFAULT_MAX_PARSER_DEPTH, DBMS_DEFAULT_MAX_PARSER_BACKTRACKS);
+                if (expr->as<ASTFunction>())
+                    continue;
+
                 /// Skip columns produced by prewhere or row-level filter expressions —
                 /// they are computed at read time, not stored in the file.
                 if (format_filter_info

tests/integration/test_storage_iceberg_with_spark/test_read_constant_columns_optimization.py

@@ -183,13 +183,10 @@ def check_events(query_id, event, is_cluster, expected):
             GROUP BY ALL
             FORMAT CSV
             """)
-        # Weird, bu looks like ReadFileMetadata does not used local file cache in 26.1
-        # metadata.json always downloaded in 26.1, once per query or subquery
-        # In 25.8 count was equal to expected, in 26.1 it is expected * 3 + 1 for Local case
-        # expected * 3 + 4 for Cluster case, because each subquery loads mettadata.json
-        assert int(res) == expected * 3 + (4 if is_cluster else 1)
+        assert int(res) == expected
 
-    event = "S3GetObject" if storage_type == "s3" else "AzureGetObject"
+    # Each file contains one row group, so number of reded row groups is equal to readed data files
+    event = "ParquetReadRowGroups"
 
     # Without optimization clickhouse reads all 7 files
     check_events(all_data_expected_query_id, event, run_on_cluster, 7)
@@ -212,4 +209,69 @@ def compare_selects(query):
 
     compare_selects(f"SELECT _path,* FROM {creation_expression} ORDER BY ALL")
     compare_selects(f"SELECT _path,* FROM {creation_expression} WHERE name_old='vasily' ORDER BY ALL")
-    compare_selects(f"SELECT _path,* FROM {creation_expression} WHERE ((tag + length(name_old)) % 2 = 1) ORDER BY ALL")
+    compare_selects(f"SELECT _path,* FROM {creation_expression} WHERE ((tag + length(name_old)) % 2 = 1) ORDER BY ALL")
+
+
+@pytest.mark.parametrize("storage_type", ["s3", "azure"])
+@pytest.mark.parametrize("run_on_cluster", [False, True])
+def test_read_constant_columns_optimization_view(started_cluster_iceberg_with_spark, storage_type, run_on_cluster):
+    instance = started_cluster_iceberg_with_spark.instances["node1"]
+    spark = started_cluster_iceberg_with_spark.spark_session
+    TABLE_NAME = "test_read_constant_columns_optimization_view_" + storage_type + "_" + get_uuid_str()
+
+    def execute_spark_query(query: str):
+        return execute_spark_query_general(
+            spark,
+            started_cluster_iceberg_with_spark,
+            storage_type,
+            TABLE_NAME,
+            query,
+        )
+
+    execute_spark_query(
+        f"""
+            CREATE TABLE {TABLE_NAME} (
+                tag INT,
+                date DATE,
+                date2 DATE,
+                name VARCHAR(50),
+                number BIGINT
+            )
+            USING iceberg
+            PARTITIONED BY (identity(tag), years(date))
+            OPTIONS('format-version'='2')
+        """
+    )
+
+    execute_spark_query(
+        f"""
+        INSERT INTO {TABLE_NAME} VALUES
+        (1, DATE '2024-01-20', DATE '2024-01-20', 'vasya', 5),
+        (1, DATE '2024-01-20', DATE '2024-01-20', 'vasilisa', 5),
+        (1, DATE '2025-01-20', DATE '2025-01-20', 'vasya', 5),
+        (1, DATE '2025-01-20', DATE '2025-01-20', 'vasya', 5),
+        (2, DATE '2025-01-20', DATE '2025-01-20', 'vasilisa', 5),
+        (2, DATE '2025-01-21', DATE '2025-01-20', 'vasilisa', 5)
+    """
+    )
+
+    creation_expression = get_creation_expression(
+        storage_type, TABLE_NAME, started_cluster_iceberg_with_spark, table_function=True, run_on_cluster=run_on_cluster
+    )
+
+    # Check that view over Iceberg table works
+    instance.query(f"CREATE VIEW {TABLE_NAME}_view AS SELECT * FROM {creation_expression}")
+
+    expected = instance.query(f"SELECT * FROM {TABLE_NAME}_view ORDER BY ALL SETTINGS allow_experimental_iceberg_read_optimization=0")
+    # All data
+    optimized = instance.query(f"SELECT * FROM {TABLE_NAME}_view ORDER BY ALL SETTINGS allow_experimental_iceberg_read_optimization=1")
+    assert expected == optimized
+    # Constant column in where
+    optimized = instance.query(f"SELECT * FROM {TABLE_NAME}_view WHERE number=5 ORDER BY ALL SETTINGS allow_experimental_iceberg_read_optimization=1")
+    assert expected == optimized
+    # Partition columns in where
+    optimized = instance.query(f"SELECT * FROM {TABLE_NAME}_view WHERE tag>0 AND date>'2020-01-01' ORDER BY ALL SETTINGS allow_experimental_iceberg_read_optimization=1")
+    assert expected == optimized
+    # Non-constant column in where
+    optimized = instance.query(f"SELECT * FROM {TABLE_NAME}_view WHERE date2!='2020-01-01' ORDER BY ALL SETTINGS allow_experimental_iceberg_read_optimization=1")
+    assert expected == optimized