yiguolei commented on code in PR #15917:
URL: https://github.com/apache/doris/pull/15917#discussion_r1126011291
##########
be/src/olap/rowset/segment_v2/segment_iterator.cpp:
##########
@@ -1196,58 +1220,91 @@ void SegmentIterator::_vec_init_lazy_materialization() {
_is_need_short_eval = true;
}
- // Step 2: check non-predicate read costs to determine whether need lazy
materialization
- // fill _non_predicate_columns.
- // After some optimization, we suppose lazy materialization is better
performance.
+ // make _schema_block_id_map
+ _schema_block_id_map.resize(_schema.columns().size());
+ for (int i = 0; i < _schema.num_column_ids(); i++) {
+ auto cid = _schema.column_id(i);
+ _schema_block_id_map[cid] = i;
+ }
+
+ // Step2: extract columns that can execute expr context
+ _is_common_expr_column.resize(_schema.columns().size(), false);
+ if (_enable_common_expr_pushdown && _remaining_vconjunct_root != nullptr) {
+ _extract_common_expr_columns(_remaining_vconjunct_root);
+ if (!_common_expr_columns.empty()) {
+ _is_need_expr_eval = true;
+ for (auto cid : _schema.column_ids()) {
+ // pred column also needs to be filtered by expr
+ if (_is_common_expr_column[cid] || _is_pred_column[cid]) {
+ auto loc = _schema_block_id_map[cid];
+ _columns_to_filter.push_back(loc);
+ }
+ }
+ }
+ }
+
+ // Step 3: fill non predicate columns and second read column
+ // if _schema columns size equal to pred_column_ids size,
lazy_materialization_read is false,
+ // all columns are lazy materialization columns without non predicte
column.
+ // If common expr pushdown exists, and expr column is not contained in
lazy materialization columns,
+ // add to second read column, which will be read after lazy materialization
if (_schema.column_ids().size() > pred_column_ids.size()) {
for (auto cid : _schema.column_ids()) {
if (!_is_pred_column[cid]) {
- _non_predicate_columns.push_back(cid);
if (_is_need_vec_eval || _is_need_short_eval) {
_lazy_materialization_read = true;
}
+ if (!_is_common_expr_column[cid]) {
+ _non_predicate_columns.push_back(cid);
+ } else {
+ _second_read_column_ids.push_back(cid);
+ }
}
}
}
- // Step 3: fill column ids for read and output
+ // Step 4: fill first read columns
if (_lazy_materialization_read) {
// insert pred cid to first_read_columns
for (auto cid : pred_column_ids) {
_first_read_column_ids.push_back(cid);
}
- } else if (!_is_need_vec_eval &&
- !_is_need_short_eval) { // no pred exists, just read and output
column
+ } else if (!_is_need_vec_eval && !_is_need_short_eval &&
+ !_is_need_expr_eval) { // no pred exists, just read and output
column
for (int i = 0; i < _schema.num_column_ids(); i++) {
auto cid = _schema.column_id(i);
_first_read_column_ids.push_back(cid);
}
- } else { // pred exits, but we can eliminate lazy materialization
- // insert pred/non-pred cid to first read columns
- std::set<ColumnId> pred_id_set;
- pred_id_set.insert(_short_cir_pred_column_ids.begin(),
_short_cir_pred_column_ids.end());
- pred_id_set.insert(_vec_pred_column_ids.begin(),
_vec_pred_column_ids.end());
- std::set<ColumnId> non_pred_set(_non_predicate_columns.begin(),
- _non_predicate_columns.end());
-
- for (int i = 0; i < _schema.num_column_ids(); i++) {
- auto cid = _schema.column_id(i);
- if (pred_id_set.find(cid) != pred_id_set.end()) {
- _first_read_column_ids.push_back(cid);
- } else if (non_pred_set.find(cid) != non_pred_set.end()) {
+ } else {
+ if (_is_need_vec_eval || _is_need_short_eval) {
+ // TODO To refactor, because we suppose lazy materialization is
better performance.
+ // pred exits, but we can eliminate lazy materialization
+ // insert pred/non-pred cid to first read columns
+ std::set<ColumnId> pred_id_set;
+ pred_id_set.insert(_short_cir_pred_column_ids.begin(),
+ _short_cir_pred_column_ids.end());
+ pred_id_set.insert(_vec_pred_column_ids.begin(),
_vec_pred_column_ids.end());
+ std::set<ColumnId> non_pred_set(_non_predicate_columns.begin(),
+ _non_predicate_columns.end());
+
+ // _second_read_column_ids must be empty. Otherwise
_lazy_materialization_read must not false.
Review Comment:
ADD CHECK(!_second_read_column_ids.empty())
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