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new 2f7052206e4 Revert "[fix] (compaction) fix compaction score in time
series policy (#40242)" (#44491)
2f7052206e4 is described below
commit 2f7052206e479567807f59a186f14feb42281479
Author: Sun Chenyang <[email protected]>
AuthorDate: Fri Nov 22 21:18:25 2024 +0800
Revert "[fix] (compaction) fix compaction score in time series policy
(#40242)" (#44491)
revert #40242
---
.../cumulative_compaction_time_series_policy.cpp | 68 +++++++++++++++++++++-
...mulative_compaction_time_series_policy_test.cpp | 2 +-
2 files changed, 68 insertions(+), 2 deletions(-)
diff --git a/be/src/olap/cumulative_compaction_time_series_policy.cpp
b/be/src/olap/cumulative_compaction_time_series_policy.cpp
index 6fa4b8d0143..64e51c77641 100644
--- a/be/src/olap/cumulative_compaction_time_series_policy.cpp
+++ b/be/src/olap/cumulative_compaction_time_series_policy.cpp
@@ -27,11 +27,14 @@ namespace doris {
uint32_t
TimeSeriesCumulativeCompactionPolicy::calc_cumulative_compaction_score(Tablet*
tablet) {
uint32_t score = 0;
+ uint32_t level0_score = 0;
bool base_rowset_exist = false;
const int64_t point = tablet->cumulative_layer_point();
+ int64_t level0_total_size = 0;
RowsetMetaSharedPtr first_meta;
int64_t first_version = INT64_MAX;
+ std::list<RowsetMetaSharedPtr> checked_rs_metas;
// NOTE: tablet._meta_lock is hold
auto& rs_metas = tablet->tablet_meta()->all_rs_metas();
// check the base rowset and collect the rowsets of cumulative part
@@ -50,6 +53,12 @@ uint32_t
TimeSeriesCumulativeCompactionPolicy::calc_cumulative_compaction_score(
} else {
// collect the rowsets of cumulative part
score += rs_meta->get_compaction_score();
+ if (rs_meta->compaction_level() == 0) {
+ level0_total_size += rs_meta->total_disk_size();
+ level0_score += rs_meta->get_compaction_score();
+ } else {
+ checked_rs_metas.push_back(rs_meta);
+ }
}
}
@@ -64,7 +73,64 @@ uint32_t
TimeSeriesCumulativeCompactionPolicy::calc_cumulative_compaction_score(
return 0;
}
- return score;
+ // Condition 1: the size of input files for compaction meets the
requirement of parameter compaction_goal_size
+ int64_t compaction_goal_size_mbytes =
+ tablet->tablet_meta()->time_series_compaction_goal_size_mbytes();
+ if (level0_total_size >= compaction_goal_size_mbytes * 1024 * 1024) {
+ return score;
+ }
+
+ // Condition 2: the number of input files reaches the threshold specified
by parameter compaction_file_count_threshold
+ if (level0_score >=
tablet->tablet_meta()->time_series_compaction_file_count_threshold()) {
+ return score;
+ }
+
+ // Condition 3: level1 achieve compaction_goal_size
+ if (tablet->tablet_meta()->time_series_compaction_level_threshold() >= 2) {
+ checked_rs_metas.sort([](const RowsetMetaSharedPtr& a, const
RowsetMetaSharedPtr& b) {
+ return a->version().first < b->version().first;
+ });
+ int32_t rs_meta_count = 0;
+ int64_t continuous_size = 0;
+ for (const auto& rs_meta : checked_rs_metas) {
+ rs_meta_count++;
+ continuous_size += rs_meta->total_disk_size();
+ if (rs_meta_count >= 2) {
+ if (continuous_size >= compaction_goal_size_mbytes * 1024 *
1024) {
+ return score;
+ }
+ }
+ }
+ }
+
+ int64_t now = UnixMillis();
+ int64_t last_cumu = tablet->last_cumu_compaction_success_time();
+ if (last_cumu != 0) {
+ int64_t cumu_interval = now - last_cumu;
+
+ // Condition 4: the time interval between compactions exceeds the
value specified by parameter _compaction_time_threshold_second
+ if (cumu_interval >
+
(tablet->tablet_meta()->time_series_compaction_time_threshold_seconds() *
1000)) {
+ return score;
+ }
+ } else if (score > 0) {
+ // If the compaction process has not been successfully executed,
+ // the condition for triggering compaction based on the last
successful compaction time (condition 3) will never be met
+ tablet->set_last_cumu_compaction_success_time(now);
+ }
+
+ // Condition 5: If there is a continuous set of empty rowsets, prioritize
merging.
+ std::vector<RowsetSharedPtr> input_rowsets;
+ std::vector<RowsetSharedPtr> candidate_rowsets =
+ tablet->pick_candidate_rowsets_to_cumulative_compaction();
+ tablet->calc_consecutive_empty_rowsets(
+ &input_rowsets, candidate_rowsets,
+
tablet->tablet_meta()->time_series_compaction_empty_rowsets_threshold());
+ if (!input_rowsets.empty()) {
+ return score;
+ }
+
+ return 0;
}
void TimeSeriesCumulativeCompactionPolicy::calculate_cumulative_point(
diff --git a/be/test/olap/cumulative_compaction_time_series_policy_test.cpp
b/be/test/olap/cumulative_compaction_time_series_policy_test.cpp
index 3e88e424e43..01963d591be 100644
--- a/be/test/olap/cumulative_compaction_time_series_policy_test.cpp
+++ b/be/test/olap/cumulative_compaction_time_series_policy_test.cpp
@@ -404,7 +404,7 @@ TEST_F(TestTimeSeriesCumulativeCompactionPolicy,
calc_cumulative_compaction_scor
const uint32_t score =
_tablet->calc_compaction_score(CompactionType::CUMULATIVE_COMPACTION,
cumulative_compaction_policy);
- EXPECT_EQ(9, score);
+ EXPECT_EQ(0, score);
}
TEST_F(TestTimeSeriesCumulativeCompactionPolicy,
calc_cumulative_compaction_score_big_rowset) {
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