[fix](parquet)Fix data column and null map column not equal when reading Parquet complex type cross-page data

be/src/vec/exec/format/parquet/vparquet_column_reader.cpp

@@ -329,6 +329,18 @@ Status ScalarColumnReader::_read_nested_column(ColumnPtr& doris_column, DataType
         // just read the remaining values of the last row in previous page,
         // so there's no a new row should be read.
         batch_size = 0;
+        /*
+         * Since the function is repeatedly called to fetch data for the batch size,
+         * it causes `_rep_levels.resize(0); _def_levels.resize(0);`, resulting in the
+         * definition and repetition levels of the reader only containing the latter
+         * part of the batch (i.e., missing some parts). Therefore, when using the
+         * definition and repetition levels to fill the null_map for structs and maps,
+         * the function should not be called multiple times before filling.
+        * todo:
+         * We may need to consider reading the entire batch of data at once, as this approach
+         * would be more user-friendly in terms of function usage. However, we must consider that if the
+         * data spans multiple pages, memory usage may increase significantly.
+         */
     } else {
         _rep_levels.resize(0);
         _def_levels.resize(0);
@@ -835,7 +847,7 @@ Status StructColumnReader::read_column_data(ColumnPtr& doris_column, DataTypePtr
             continue;
         }
 
-        _read_column_names.insert(doris_name);
+        _read_column_names.emplace_back(doris_name);
 
         //        select_vector.reset();
         size_t field_rows = 0;
@@ -847,6 +859,15 @@ Status StructColumnReader::read_column_data(ColumnPtr& doris_column, DataTypePtr
                     is_dict_filter));
             *read_rows = field_rows;
             *eof = field_eof;
+            /*
+             * Considering the issue in the `_read_nested_column` function where data may span across pages, leading
+             * to missing definition and repetition levels, when filling the null_map of the struct later, it is
+             * crucial to use the definition and repetition levels from the first read column
+             * (since `_read_nested_column` is not called repeatedly).
+             *
+             *  It is worth mentioning that, theoretically, any sub-column can be chosen to fill the null_map,
+             *  and selecting the shortest one will offer better performance
+             */
         } else {
             while (field_rows < *read_rows && !field_eof) {
                 size_t loop_rows = 0;

be/src/vec/exec/format/parquet/vparquet_column_reader.h

@@ -298,24 +298,24 @@ class StructColumnReader : public ParquetColumnReader {
         if (!_read_column_names.empty()) {
             // can't use _child_readers[*_read_column_names.begin()]
             // because the operator[] of std::unordered_map is not const :(
-            return _child_readers.find(*_read_column_names.begin())->second->get_rep_level();
+            return _child_readers.find(_read_column_names.front())->second->get_rep_level();
         }
         return _child_readers.begin()->second->get_rep_level();
     }
 
     const std::vector<level_t>& get_def_level() const override {
         if (!_read_column_names.empty()) {
-            return _child_readers.find(*_read_column_names.begin())->second->get_def_level();
+            return _child_readers.find(_read_column_names.front())->second->get_def_level();
         }
         return _child_readers.begin()->second->get_def_level();
     }
 
     Statistics statistics() override {
         Statistics st;
-        for (const auto& reader : _child_readers) {
-            // make sure the field is read
-            if (_read_column_names.find(reader.first) != _read_column_names.end()) {
-                Statistics cst = reader.second->statistics();
+        for (const auto& column_name : _read_column_names) {
+            auto reader = _child_readers.find(column_name);
+            if (reader != _child_readers.end()) {
+                Statistics cst = reader->second->statistics();
                 st.merge(cst);
             }
         }
@@ -332,7 +332,7 @@ class StructColumnReader : public ParquetColumnReader {
 
 private:
     std::unordered_map<std::string, std::unique_ptr<ParquetColumnReader>> _child_readers;
-    std::set<std::string> _read_column_names;
+    std::vector<std::string> _read_column_names;
 };
 
 }; // namespace doris::vectorized

regression-test/data/external_table_p0/tvf/test_tvf_p2.out → regression-test/data/external_table_p0/tvf/test_tvf_p0.out

@@ -65,3 +65,12 @@
 -- !viewfs --
 25001	25001	25001
 
+-- !row_cross_pages_2 --
+149923	149923
+
+-- !row_cross_pages_3 --
+74815	74815
+
+-- !row_cross_pages_4 --
+457	457
+

regression-test/data/external_table_p2/hive/test_parquet_complex_cross_page.out

@@ -0,0 +1,10 @@
+-- This file is automatically generated. You should know what you did if you want to edit this
+-- !1 --
+1
+
+-- !2 --
+5000
+
+-- !3 --
+5000
+

regression-test/suites/external_table_p0/tvf/test_tvf_p2.groovy → regression-test/suites/external_table_p0/tvf/test_tvf_p0.groovy

@@ -15,7 +15,7 @@
 // specific language governing permissions and limitations
 // under the License.
 
-suite("test_tvf_p2", "p0,external,tvf,external_docker,hive") {
+suite("test_tvf_p0", "p0,external,tvf,external_docker,hive") {
     String enabled = context.config.otherConfigs.get("enableHiveTest")
     if (enabled != null && enabled.equalsIgnoreCase("true")) {
         String nameNodeHost = context.config.otherConfigs.get("externalEnvIp")
@@ -46,7 +46,7 @@ suite("test_tvf_p2", "p0,external,tvf,external_docker,hive") {
             "format" = "orc");
         """
 
-        // a row of complex type may be stored across more pages
+        // (1): a row of complex type may be stored across more pages
         qt_row_cross_pages """select count(id), count(m1), count(m2)
             from hdfs(
             "uri" = "hdfs://${nameNodeHost}:${hdfsPort}/catalog/tvf/parquet/row_cross_pages.parquet",
@@ -73,5 +73,25 @@ suite("test_tvf_p2", "p0,external,tvf,external_docker,hive") {
             "format" = "parquet",
             "fs.viewfs.mounttable.my-cluster.link./ns1" = "hdfs://${nameNodeHost}:${hdfsPort}/",
             "fs.viewfs.mounttable.my-cluster.homedir" = "/ns1")"""
+
+        // (2): a row of complex type may be stored across more pages 
+        qt_row_cross_pages_2  """select count(id), count(experiment)
+            from hdfs(
+            "uri" = "hdfs://${nameNodeHost}:${hdfsPort}/catalog/tvf/parquet/row_cross_pages_2.parquet",
+            "format" = "parquet");
+        """ //149923
+
+        qt_row_cross_pages_3  """select count(id), count(experiment)
+            from hdfs(
+            "uri" = "hdfs://${nameNodeHost}:${hdfsPort}/catalog/tvf/parquet/row_cross_pages_2.parquet",
+            "format" = "parquet") where id > 49923 ;
+        """  // 74815 
+
+        qt_row_cross_pages_4  """select count(id), count(experiment)
+            from hdfs(
+            "uri" = "hdfs://${nameNodeHost}:${hdfsPort}/catalog/tvf/parquet/row_cross_pages_2.parquet",
+            "format" = "parquet")  where id < 300 ;
+        """ //457 
+
     }
 }

regression-test/suites/external_table_p2/hive/test_parquet_complex_cross_page.groovy

@@ -0,0 +1,52 @@
+// Licensed to the Apache Software Foundation (ASF) under one
+// or more contributor license agreements.  See the NOTICE file
+// distributed with this work for additional information
+// regarding copyright ownership.  The ASF licenses this file
+// to you under the Apache License, Version 2.0 (the
+// "License"); you may not use this file except in compliance
+// with the License.  You may obtain a copy of the License at
+//
+//   http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing,
+// software distributed under the License is distributed on an
+// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+// KIND, either express or implied.  See the License for the
+// specific language governing permissions and limitations
+// under the License.
+
+suite("test_parquet_complex_cross_page", "p2,external,hive,external_remote,external_remote_hive") {
+
+    String enabled = context.config.otherConfigs.get("enableExternalHudiTest")
+    //hudi hive use same catalog in p2.
+    if (enabled == null || !enabled.equalsIgnoreCase("true")) {
+        logger.info("disable test")
+        return;
+    }
+
+    String props = context.config.otherConfigs.get("hudiEmrCatalog")    
+    String hms_catalog_name = "test_parquet_complex_cross_page"
+
+    sql """drop catalog if exists ${hms_catalog_name};"""
+    sql """
+        CREATE CATALOG IF NOT EXISTS ${hms_catalog_name}
+        PROPERTIES ( 
+            ${props}
+            ,'hive.version' = '3.1.3'
+        );
+    """
+
+    logger.info("catalog " + hms_catalog_name + " created")
+    sql """switch ${hms_catalog_name};"""
+    logger.info("switched to catalog " + hms_catalog_name)
+    sql """ use regression;"""
+
+    sql """ set dry_run_query=true; """ 
+
+    qt_1 """  SELECT *  FROM test_parquet_complex_cross_page WHERE device_id='DZ692'  and format_time between 1737693770300 and 1737693770500 
+    and date between '20250124' and '20250124'  and project='GA20230001' ; """ 
+    qt_2 """ SELECT functions_pnc_ssm_road_di_objects from test_parquet_complex_cross_page ; """ 
+    qt_3 """ select * from test_parquet_complex_cross_page ; """ 
+
+    sql """drop catalog ${hms_catalog_name};"""
+}