branch-3.1: [Fix](auto-partition) Fix coredump caused by auto partition and auto increment column

be/src/pipeline/exec/exchange_sink_operator.cpp

@@ -510,13 +510,11 @@ Status ExchangeSinkOperatorX::sink(RuntimeState* state, vectorized::Block* block
         auto input_rows = block->rows();
 
         if (input_rows > 0) {
-            bool has_filtered_rows = false;
-            int64_t filtered_rows = 0;
             local_state._number_input_rows += input_rows;
 
             RETURN_IF_ERROR(local_state._row_distribution.generate_rows_distribution(
-                    *block, convert_block, filtered_rows, has_filtered_rows,
-                    local_state._row_part_tablet_ids, local_state._number_input_rows));
+                    *block, convert_block, local_state._row_part_tablet_ids,
+                    local_state._number_input_rows));
             if (local_state._row_distribution.batching_rows() > 0) {
                 SCOPED_TIMER(local_state._send_new_partition_timer);
                 RETURN_IF_ERROR(local_state._send_new_partition_batch(block));

be/src/vec/sink/vrow_distribution.cpp

@@ -43,17 +43,17 @@
 
 namespace doris::vectorized {
 
-std::pair<vectorized::VExprContextSPtrs, vectorized::VExprSPtrs>
-VRowDistribution::_get_partition_function() {
+std::pair<VExprContextSPtrs, VExprSPtrs> VRowDistribution::_get_partition_function() {
     return {_vpartition->get_part_func_ctx(), _vpartition->get_partition_function()};
 }
 
 Status VRowDistribution::_save_missing_values(
+        const Block& input_block,
         std::vector<std::vector<std::string>>& col_strs, // non-const ref for move
         int col_size, Block* block, std::vector<int64_t> filter,
         const std::vector<const NullMap*>& col_null_maps) {
     // de-duplication for new partitions but save all rows.
-    RETURN_IF_ERROR(_batching_block->add_rows(block, filter));
+    RETURN_IF_ERROR(_batching_block->add_rows(&input_block, filter));
     std::vector<TNullableStringLiteral> cur_row_values;
     for (int row = 0; row < col_strs[0].size(); ++row) {
         cur_row_values.clear();
@@ -78,7 +78,7 @@ Status VRowDistribution::_save_missing_values(
     if (_batching_block->rows() > _batch_size) {
         _deal_batched = true;
     }
-
+    _batching_rows = _batching_block->rows();
     VLOG_NOTICE << "pushed some batching lines, now numbers = " << _batching_rows;
 
     return Status::OK();
@@ -205,7 +205,7 @@ Status VRowDistribution::_replace_overwriting_partition() {
     return status;
 }
 
-void VRowDistribution::_get_tablet_ids(vectorized::Block* block, int32_t index_idx,
+void VRowDistribution::_get_tablet_ids(Block* block, int32_t index_idx,
                                        std::vector<int64_t>& tablet_ids) {
     tablet_ids.reserve(block->rows());
     for (int row_idx = 0; row_idx < block->rows(); row_idx++) {
@@ -221,8 +221,7 @@ void VRowDistribution::_get_tablet_ids(vectorized::Block* block, int32_t index_i
     }
 }
 
-void VRowDistribution::_filter_block_by_skip(vectorized::Block* block,
-                                             RowPartTabletIds& row_part_tablet_id) {
+void VRowDistribution::_filter_block_by_skip(Block* block, RowPartTabletIds& row_part_tablet_id) {
     auto& row_ids = row_part_tablet_id.row_ids;
     auto& partition_ids = row_part_tablet_id.partition_ids;
     auto& tablet_ids = row_part_tablet_id.tablet_ids;
@@ -237,8 +236,7 @@ void VRowDistribution::_filter_block_by_skip(vectorized::Block* block,
 }
 
 Status VRowDistribution::_filter_block_by_skip_and_where_clause(
-        vectorized::Block* block, const vectorized::VExprContextSPtr& where_clause,
-        RowPartTabletIds& row_part_tablet_id) {
+        Block* block, const VExprContextSPtr& where_clause, RowPartTabletIds& row_part_tablet_id) {
     // TODO
     //SCOPED_RAW_TIMER(&_stat.where_clause_ns);
     int result_index = -1;
@@ -250,25 +248,23 @@ Status VRowDistribution::_filter_block_by_skip_and_where_clause(
     auto& row_ids = row_part_tablet_id.row_ids;
     auto& partition_ids = row_part_tablet_id.partition_ids;
     auto& tablet_ids = row_part_tablet_id.tablet_ids;
-    if (const auto* nullable_column =
-                vectorized::check_and_get_column<vectorized::ColumnNullable>(*filter_column)) {
+    if (const auto* nullable_column = check_and_get_column<ColumnNullable>(*filter_column)) {
         for (size_t i = 0; i < block->rows(); i++) {
             if (nullable_column->get_bool_inline(i) && !_skip[i]) {
                 row_ids.emplace_back(i);
                 partition_ids.emplace_back(_partitions[i]->id);
                 tablet_ids.emplace_back(_tablet_ids[i]);
             }
         }
-    } else if (const auto* const_column =
-                       vectorized::check_and_get_column<vectorized::ColumnConst>(*filter_column)) {
+    } else if (const auto* const_column = check_and_get_column<ColumnConst>(*filter_column)) {
         bool ret = const_column->get_bool(0);
         if (!ret) {
             return Status::OK();
         }
         // should we optimize?
         _filter_block_by_skip(block, row_part_tablet_id);
     } else {
-        const auto& filter = assert_cast<const vectorized::ColumnUInt8&>(*filter_column).get_data();
+        const auto& filter = assert_cast<const ColumnUInt8&>(*filter_column).get_data();
         for (size_t i = 0; i < block->rows(); i++) {
             if (filter[i] != 0 && !_skip[i]) {
                 row_ids.emplace_back(i);
@@ -284,7 +280,7 @@ Status VRowDistribution::_filter_block_by_skip_and_where_clause(
     return Status::OK();
 }
 
-Status VRowDistribution::_filter_block(vectorized::Block* block,
+Status VRowDistribution::_filter_block(Block* block,
                                        std::vector<RowPartTabletIds>& row_part_tablet_ids) {
     for (int i = 0; i < _schema->indexes().size(); i++) {
         _get_tablet_ids(block, i, _tablet_ids);
@@ -300,8 +296,7 @@ Status VRowDistribution::_filter_block(vectorized::Block* block,
 }
 
 Status VRowDistribution::_generate_rows_distribution_for_non_auto_partition(
-        vectorized::Block* block, bool has_filtered_rows,
-        std::vector<RowPartTabletIds>& row_part_tablet_ids) {
+        Block* block, bool has_filtered_rows, std::vector<RowPartTabletIds>& row_part_tablet_ids) {
     auto num_rows = block->rows();
 
     RETURN_IF_ERROR(_tablet_finder->find_tablets(_state, block, num_rows, _partitions,
@@ -315,7 +310,7 @@ Status VRowDistribution::_generate_rows_distribution_for_non_auto_partition(
     return Status::OK();
 }
 
-Status VRowDistribution::_deal_missing_map(vectorized::Block* block,
+Status VRowDistribution::_deal_missing_map(const Block& input_block, Block* block,
                                            const std::vector<uint16_t>& partition_cols_idx,
                                            int64_t& rows_stat_val) {
     // for missing partition keys, calc the missing partition and save in _partitions_need_create
@@ -345,8 +340,8 @@ Status VRowDistribution::_deal_missing_map(vectorized::Block* block,
     }
 
     // calc the end value and save them. in the end of sending, we will create partitions for them and deal them.
-    RETURN_IF_ERROR(
-            _save_missing_values(col_strs, part_col_num, block, _missing_map, col_null_maps));
+    RETURN_IF_ERROR(_save_missing_values(input_block, col_strs, part_col_num, block, _missing_map,
+                                         col_null_maps));
 
     size_t new_bt_rows = _batching_block->rows();
     size_t new_bt_bytes = _batching_block->bytes();
@@ -362,7 +357,7 @@ Status VRowDistribution::_deal_missing_map(vectorized::Block* block,
 }
 
 Status VRowDistribution::_generate_rows_distribution_for_auto_partition(
-        vectorized::Block* block, const std::vector<uint16_t>& partition_cols_idx,
+        const Block& input_block, Block* block, const std::vector<uint16_t>& partition_cols_idx,
         bool has_filtered_rows, std::vector<RowPartTabletIds>& row_part_tablet_ids,
         int64_t& rows_stat_val) {
     auto num_rows = block->rows();
@@ -384,13 +379,13 @@ Status VRowDistribution::_generate_rows_distribution_for_auto_partition(
     RETURN_IF_ERROR(_filter_block(block, row_part_tablet_ids));
 
     if (!_missing_map.empty()) {
-        RETURN_IF_ERROR(_deal_missing_map(block, partition_cols_idx, rows_stat_val));
+        RETURN_IF_ERROR(_deal_missing_map(input_block, block, partition_cols_idx, rows_stat_val));
     }
     return Status::OK();
 }
 
 Status VRowDistribution::_generate_rows_distribution_for_auto_overwrite(
-        vectorized::Block* block, const std::vector<uint16_t>& partition_cols_idx,
+        const Block& input_block, Block* block, const std::vector<uint16_t>& partition_cols_idx,
         bool has_filtered_rows, std::vector<RowPartTabletIds>& row_part_tablet_ids,
         int64_t& rows_stat_val) {
     auto num_rows = block->rows();
@@ -413,7 +408,8 @@ Status VRowDistribution::_generate_rows_distribution_for_auto_overwrite(
 
         // allow and really need to create during auto-detect-overwriting.
         if (!_missing_map.empty()) {
-            RETURN_IF_ERROR(_deal_missing_map(block, partition_cols_idx, rows_stat_val));
+            RETURN_IF_ERROR(
+                    _deal_missing_map(input_block, block, partition_cols_idx, rows_stat_val));
         }
     } else {
         RETURN_IF_ERROR(_tablet_finder->find_tablets(_state, block, num_rows, _partitions,
@@ -467,20 +463,19 @@ void VRowDistribution::_reset_row_part_tablet_ids(
 }
 
 Status VRowDistribution::generate_rows_distribution(
-        vectorized::Block& input_block, std::shared_ptr<vectorized::Block>& block,
-        int64_t& filtered_rows, bool& has_filtered_rows,
+        Block& input_block, std::shared_ptr<Block>& block,
         std::vector<RowPartTabletIds>& row_part_tablet_ids, int64_t& rows_stat_val) {
     auto input_rows = input_block.rows();
     _reset_row_part_tablet_ids(row_part_tablet_ids, input_rows);
 
-    int64_t prev_filtered_rows =
-            _block_convertor->num_filtered_rows() + _tablet_finder->num_filtered_rows();
+    // we store the batching block with value of `input_block`. so just do all of these again.
+    bool has_filtered_rows = false; // validate may filter some rows. pass for setting _skip
     RETURN_IF_ERROR(_block_convertor->validate_and_convert_block(
             _state, &input_block, block, *_vec_output_expr_ctxs, input_rows, has_filtered_rows));
 
     // batching block rows which need new partitions. deal together at finish.
     if (!_batching_block) [[unlikely]] {
-        std::unique_ptr<Block> tmp_block = block->create_same_struct_block(0);
+        std::unique_ptr<Block> tmp_block = input_block.create_same_struct_block(0);
         _batching_block = MutableBlock::create_unique(std::move(*tmp_block));
     }
 
@@ -498,7 +493,7 @@ Status VRowDistribution::generate_rows_distribution(
             // we just calc left range here. leave right to FE to avoid dup calc.
             RETURN_IF_ERROR(part_funcs[i]->execute(part_ctxs[i].get(), block.get(), &result_idx));
 
-            VLOG_DEBUG << "Partition-calculated block:" << block->dump_data(0, 1);
+            VLOG_DEBUG << "Partition-calculated block:\n" << block->dump_data(0, 1);
             DCHECK(result_idx != -1);
 
             partition_cols_idx.push_back(result_idx);
@@ -511,20 +506,18 @@ Status VRowDistribution::generate_rows_distribution(
     Status st = Status::OK();
     if (_vpartition->is_auto_detect_overwrite() && !_deal_batched) {
         // when overwrite, no auto create partition allowed.
-        st = _generate_rows_distribution_for_auto_overwrite(block.get(), partition_cols_idx,
-                                                            has_filtered_rows, row_part_tablet_ids,
-                                                            rows_stat_val);
+        st = _generate_rows_distribution_for_auto_overwrite(input_block, block.get(),
+                                                            partition_cols_idx, has_filtered_rows,
+                                                            row_part_tablet_ids, rows_stat_val);
     } else if (_vpartition->is_auto_partition() && !_deal_batched) {
-        st = _generate_rows_distribution_for_auto_partition(block.get(), partition_cols_idx,
-                                                            has_filtered_rows, row_part_tablet_ids,
-                                                            rows_stat_val);
+        st = _generate_rows_distribution_for_auto_partition(input_block, block.get(),
+                                                            partition_cols_idx, has_filtered_rows,
+                                                            row_part_tablet_ids, rows_stat_val);
     } else { // not auto partition
         st = _generate_rows_distribution_for_non_auto_partition(block.get(), has_filtered_rows,
                                                                 row_part_tablet_ids);
     }
 
-    filtered_rows = _block_convertor->num_filtered_rows() + _tablet_finder->num_filtered_rows() -
-                    prev_filtered_rows;
     return st;
 }
 

be/src/vec/sink/vrow_distribution.h

@@ -127,55 +127,55 @@ class VRowDistribution {
     // mv where clause
     // v1 needs index->node->row_ids - tabletids
     // v2 needs index,tablet->rowids
-    Status generate_rows_distribution(vectorized::Block& input_block,
-                                      std::shared_ptr<vectorized::Block>& block,
-                                      int64_t& filtered_rows, bool& has_filtered_rows,
+    Status generate_rows_distribution(Block& input_block, std::shared_ptr<Block>& block,
                                       std::vector<RowPartTabletIds>& row_part_tablet_ids,
                                       int64_t& rows_stat_val);
+    // have 2 ways remind to deal batching block:
+    // 1. in row_distribution, _batching_rows reaches the threshold, this class set _deal_batched = true.
+    // 2. in caller, after last block and before close, set _deal_batched = true.
     bool need_deal_batching() const { return _deal_batched && _batching_rows > 0; }
     size_t batching_rows() const { return _batching_rows; }
     // create partitions when need for auto-partition table using #_partitions_need_create.
     Status automatic_create_partition();
     void clear_batching_stats();
 
     // for auto partition
-    std::unique_ptr<MutableBlock> _batching_block;
+    std::unique_ptr<MutableBlock> _batching_block; // same structure with input_block
     bool _deal_batched = false; // If true, send batched block before any block's append.
 
 private:
-    std::pair<vectorized::VExprContextSPtrs, vectorized::VExprSPtrs> _get_partition_function();
+    std::pair<VExprContextSPtrs, VExprSPtrs> _get_partition_function();
 
-    Status _save_missing_values(std::vector<std::vector<std::string>>& col_strs, int col_size,
+    Status _save_missing_values(const Block& input_block,
+                                std::vector<std::vector<std::string>>& col_strs, int col_size,
                                 Block* block, std::vector<int64_t> filter,
                                 const std::vector<const NullMap*>& col_null_maps);
 
-    void _get_tablet_ids(vectorized::Block* block, int32_t index_idx,
-                         std::vector<int64_t>& tablet_ids);
+    void _get_tablet_ids(Block* block, int32_t index_idx, std::vector<int64_t>& tablet_ids);
 
-    void _filter_block_by_skip(vectorized::Block* block, RowPartTabletIds& row_part_tablet_id);
+    void _filter_block_by_skip(Block* block, RowPartTabletIds& row_part_tablet_id);
 
-    Status _filter_block_by_skip_and_where_clause(vectorized::Block* block,
-                                                  const vectorized::VExprContextSPtr& where_clause,
+    Status _filter_block_by_skip_and_where_clause(Block* block,
+                                                  const VExprContextSPtr& where_clause,
                                                   RowPartTabletIds& row_part_tablet_id);
 
-    Status _filter_block(vectorized::Block* block,
-                         std::vector<RowPartTabletIds>& row_part_tablet_ids);
+    Status _filter_block(Block* block, std::vector<RowPartTabletIds>& row_part_tablet_ids);
 
     Status _generate_rows_distribution_for_auto_partition(
-            vectorized::Block* block, const std::vector<uint16_t>& partition_col_idx,
+            const Block& input_block, Block* block, const std::vector<uint16_t>& partition_col_idx,
             bool has_filtered_rows, std::vector<RowPartTabletIds>& row_part_tablet_ids,
             int64_t& rows_stat_val);
     // the whole process to deal missing rows. will call _save_missing_values
-    Status _deal_missing_map(vectorized::Block* block,
+    Status _deal_missing_map(const Block& input_block, Block* block,
                              const std::vector<uint16_t>& partition_cols_idx,
                              int64_t& rows_stat_val);
 
     Status _generate_rows_distribution_for_non_auto_partition(
-            vectorized::Block* block, bool has_filtered_rows,
+            Block* block, bool has_filtered_rows,
             std::vector<RowPartTabletIds>& row_part_tablet_ids);
 
     Status _generate_rows_distribution_for_auto_overwrite(
-            vectorized::Block* block, const std::vector<uint16_t>& partition_cols_idx,
+            const Block& input_block, Block* block, const std::vector<uint16_t>& partition_cols_idx,
             bool has_filtered_rows, std::vector<RowPartTabletIds>& row_part_tablet_ids,
             int64_t& rows_stat_val);
     Status _replace_overwriting_partition();

be/src/vec/sink/writer/vtablet_writer.cpp

@@ -1977,8 +1977,6 @@ Status VTabletWriter::write(RuntimeState* state, doris::vectorized::Block& input
     SCOPED_RAW_TIMER(&_send_data_ns);
 
     std::shared_ptr<vectorized::Block> block;
-    bool has_filtered_rows = false;
-    int64_t filtered_rows = 0;
     _number_input_rows += rows;
     // update incrementally so that FE can get the progress.
     // the real 'num_rows_load_total' will be set when sink being closed.
@@ -1989,8 +1987,7 @@ Status VTabletWriter::write(RuntimeState* state, doris::vectorized::Block& input
 
     _row_distribution_watch.start();
     RETURN_IF_ERROR(_row_distribution.generate_rows_distribution(
-            input_block, block, filtered_rows, has_filtered_rows, _row_part_tablet_ids,
-            _number_input_rows));
+            input_block, block, _row_part_tablet_ids, _number_input_rows));
 
     ChannelDistributionPayloadVec channel_to_payload;
 

be/src/vec/sink/writer/vtablet_writer_v2.cpp

@@ -481,17 +481,13 @@ Status VTabletWriterV2::write(RuntimeState* state, Block& input_block) {
     DorisMetrics::instance()->load_rows->increment(input_rows);
     DorisMetrics::instance()->load_bytes->increment(input_bytes);
 
-    bool has_filtered_rows = false;
-    int64_t filtered_rows = 0;
-
     SCOPED_RAW_TIMER(&_send_data_ns);
     // This is just for passing compilation.
     _row_distribution_watch.start();
 
     std::shared_ptr<vectorized::Block> block;
     RETURN_IF_ERROR(_row_distribution.generate_rows_distribution(
-            input_block, block, filtered_rows, has_filtered_rows, _row_part_tablet_ids,
-            _number_input_rows));
+            input_block, block, _row_part_tablet_ids, _number_input_rows));
     RowsForTablet rows_for_tablet;
     _generate_rows_for_tablet(_row_part_tablet_ids, rows_for_tablet);
 

regression-test/suites/partition_p1/auto_partition/ddl/iot.sql

@@ -0,0 +1,19 @@
+INSERT OVERWRITE TABLE auto_inc_target PARTITION (*)
+SELECT '2099-12-01' AS close_account_month,
+    ROW_NUMBER() OVER () AS auto_increment_id,
+    0 AS close_account_status,
+    `_id`,
+    main.`transaction_id` AS transaction_id,
+    CURRENT_TIMESTAMP() AS insert_time
+FROM (
+        SELECT `_id`,
+            `transaction_id`
+        FROM auto_inc_src
+        WHERE dt = '2025-12-22'
+    ) main
+    LEFT JOIN (
+        SELECT DISTINCT transaction_id
+        FROM auto_inc_target
+        WHERE close_account_status = 1
+    ) et ON main.transaction_id = et.transaction_id
+WHERE et.transaction_id IS NULL

regression-test/suites/partition_p1/auto_partition/ddl/src.sql

@@ -0,0 +1,11 @@
+CREATE TABLE `auto_inc_src` (
+  `dt` date NOT NULL COMMENT "统计日期",
+  `_id` varchar(255) NULL COMMENT "表ID",
+  `transaction_id` varchar(255) NULL COMMENT "交易ID",
+  `insert_time` datetime NULL COMMENT "数仓数据更新时间"
+)
+DUPLICATE KEY(`dt`)
+DISTRIBUTED BY HASH(`transaction_id`) BUCKETS AUTO
+PROPERTIES (
+"replication_allocation" = "tag.location.default: 1"
+);