Add 5-minute AggregatingMergeTree stats rollup for dashboard queries

Pre-aggregate route execution stats into 5-minute buckets using a
materialized view with -State/-Merge combinators. Rewrite stats() and
timeseries() to query the rollup table instead of scanning the wide
base table. Active count remains a real-time query since RUNNING is
transient. Includes idempotent backfill migration.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

cameleer3-server-app/src/main/java/com/cameleer3/server/app/search/ClickHouseSearchEngine.java

@@ -96,79 +96,87 @@ public class ClickHouseSearchEngine implements SearchEngine {
 
     @Override
     public ExecutionStats stats(Instant from, Instant to, String routeId, List<String> agentIds) {
+        // Current period — read from rollup
         var conditions = new ArrayList<String>();
         var params = new ArrayList<Object>();
-        conditions.add("start_time >= ?");
+        conditions.add("bucket >= toStartOfFiveMinutes(?)");
         params.add(Timestamp.from(from));
-        conditions.add("start_time <= ?");
+        conditions.add("bucket <= ?");
         params.add(Timestamp.from(to));
         addScopeFilters(routeId, agentIds, conditions, params);
 
         String where = " WHERE " + String.join(" AND ", conditions);
 
-        String aggregateSql = "SELECT count() AS total_count, " +
+        String rollupSql = "SELECT " +
-                "countIf(status = 'FAILED') AS failed_count, " +
+                "countMerge(total_count) AS total_count, " +
-                "toInt64(ifNotFinite(avg(duration_ms), 0)) AS avg_duration_ms, " +
+                "countIfMerge(failed_count) AS failed_count, " +
-                "toInt64(ifNotFinite(quantile(0.99)(duration_ms), 0)) AS p99_duration_ms, " +
+                "toInt64(ifNotFinite(sumMerge(duration_sum) / countMerge(total_count), 0)) AS avg_duration_ms, " +
-                "countIf(status = 'RUNNING') AS active_count " +
+                "toInt64(ifNotFinite(quantileTDigestMerge(0.99)(p99_duration), 0)) AS p99_duration_ms " +
-                "FROM route_executions" + where;
+                "FROM route_execution_stats_5m" + where;
 
-        // Current period
+        record PeriodStats(long totalCount, long failedCount, long avgDurationMs, long p99LatencyMs) {}
-        record PeriodStats(long totalCount, long failedCount, long avgDurationMs, long p99LatencyMs, long activeCount) {}
+        PeriodStats current = jdbcTemplate.queryForObject(rollupSql,
-        PeriodStats current = jdbcTemplate.queryForObject(aggregateSql,
                 (rs, rowNum) -> new PeriodStats(
                         rs.getLong("total_count"),
                         rs.getLong("failed_count"),
                         rs.getLong("avg_duration_ms"),
-                        rs.getLong("p99_duration_ms"),
+                        rs.getLong("p99_duration_ms")),
-                        rs.getLong("active_count")),
                 params.toArray());
 
-        // Previous period (same window shifted back 24h)
+        // Active count — lightweight real-time query on base table (RUNNING is transient)
+        var activeConditions = new ArrayList<String>();
+        var activeParams = new ArrayList<Object>();
+        activeConditions.add("status = 'RUNNING'");
+        addScopeFilters(routeId, agentIds, activeConditions, activeParams);
+        String activeWhere = " WHERE " + String.join(" AND ", activeConditions);
+        Long activeCount = jdbcTemplate.queryForObject(
+                "SELECT count() FROM route_executions" + activeWhere,
+                Long.class, activeParams.toArray());
+
+        // Previous period (same window shifted back 24h) — read from rollup
         Duration window = Duration.between(from, to);
         Instant prevFrom = from.minus(Duration.ofHours(24));
         Instant prevTo = prevFrom.plus(window);
-        var prevParams = new ArrayList<Object>();
         var prevConditions = new ArrayList<String>();
-        prevConditions.add("start_time >= ?");
+        var prevParams = new ArrayList<Object>();
+        prevConditions.add("bucket >= toStartOfFiveMinutes(?)");
         prevParams.add(Timestamp.from(prevFrom));
-        prevConditions.add("start_time <= ?");
+        prevConditions.add("bucket <= ?");
         prevParams.add(Timestamp.from(prevTo));
         addScopeFilters(routeId, agentIds, prevConditions, prevParams);
         String prevWhere = " WHERE " + String.join(" AND ", prevConditions);
 
-        String prevAggregateSql = "SELECT count() AS total_count, " +
+        String prevRollupSql = "SELECT " +
-                "countIf(status = 'FAILED') AS failed_count, " +
+                "countMerge(total_count) AS total_count, " +
-                "toInt64(ifNotFinite(avg(duration_ms), 0)) AS avg_duration_ms, " +
+                "countIfMerge(failed_count) AS failed_count, " +
-                "toInt64(ifNotFinite(quantile(0.99)(duration_ms), 0)) AS p99_duration_ms, " +
+                "toInt64(ifNotFinite(sumMerge(duration_sum) / countMerge(total_count), 0)) AS avg_duration_ms, " +
-                "countIf(status = 'RUNNING') AS active_count " +
+                "toInt64(ifNotFinite(quantileTDigestMerge(0.99)(p99_duration), 0)) AS p99_duration_ms " +
-                "FROM route_executions" + prevWhere;
+                "FROM route_execution_stats_5m" + prevWhere;
 
-        PeriodStats prev = jdbcTemplate.queryForObject(prevAggregateSql,
+        PeriodStats prev = jdbcTemplate.queryForObject(prevRollupSql,
                 (rs, rowNum) -> new PeriodStats(
                         rs.getLong("total_count"),
                         rs.getLong("failed_count"),
                         rs.getLong("avg_duration_ms"),
-                        rs.getLong("p99_duration_ms"),
+                        rs.getLong("p99_duration_ms")),
-                        rs.getLong("active_count")),
                 prevParams.toArray());
 
-        // Today total (midnight UTC to now) with same scope
+        // Today total (midnight UTC to now) — read from rollup with same scope
         Instant todayStart = Instant.now().truncatedTo(java.time.temporal.ChronoUnit.DAYS);
         var todayConditions = new ArrayList<String>();
         var todayParams = new ArrayList<Object>();
-        todayConditions.add("start_time >= ?");
+        todayConditions.add("bucket >= toStartOfFiveMinutes(?)");
         todayParams.add(Timestamp.from(todayStart));
         addScopeFilters(routeId, agentIds, todayConditions, todayParams);
         String todayWhere = " WHERE " + String.join(" AND ", todayConditions);
 
         Long totalToday = jdbcTemplate.queryForObject(
-                "SELECT count() FROM route_executions" + todayWhere,
+                "SELECT countMerge(total_count) FROM route_execution_stats_5m" + todayWhere,
                 Long.class, todayParams.toArray());
 
         return new ExecutionStats(
                 current.totalCount, current.failedCount, current.avgDurationMs,
-                current.p99LatencyMs, current.activeCount,
+                current.p99LatencyMs, activeCount != null ? activeCount : 0L,
                 totalToday != null ? totalToday : 0L,
                 prev.totalCount, prev.failedCount, prev.avgDurationMs, prev.p99LatencyMs);
     }
@@ -186,34 +194,32 @@ public class ClickHouseSearchEngine implements SearchEngine {
 
         var conditions = new ArrayList<String>();
         var params = new ArrayList<Object>();
-        conditions.add("start_time >= ?");
+        conditions.add("bucket >= toStartOfFiveMinutes(?)");
         params.add(Timestamp.from(from));
-        conditions.add("start_time <= ?");
+        conditions.add("bucket <= ?");
         params.add(Timestamp.from(to));
         addScopeFilters(routeId, agentIds, conditions, params);
 
         String where = " WHERE " + String.join(" AND ", conditions);
 
-        // Use epoch-based bucketing for DateTime64 compatibility
+        // Re-aggregate 5-minute rollup buckets into the requested interval
         String sql = "SELECT " +
-                "toDateTime(intDiv(toUInt32(toDateTime(start_time)), " + intervalSeconds + ") * " + intervalSeconds + ") AS bucket, " +
+                "toDateTime(intDiv(toUInt32(bucket), " + intervalSeconds + ") * " + intervalSeconds + ") AS ts_bucket, " +
-                "count() AS total_count, " +
+                "countMerge(total_count) AS total_count, " +
-                "countIf(status = 'FAILED') AS failed_count, " +
+                "countIfMerge(failed_count) AS failed_count, " +
-                "toInt64(ifNotFinite(avg(duration_ms), 0)) AS avg_duration_ms, " +
+                "toInt64(ifNotFinite(sumMerge(duration_sum) / countMerge(total_count), 0)) AS avg_duration_ms, " +
-                "toInt64(ifNotFinite(quantile(0.99)(duration_ms), 0)) AS p99_duration_ms, " +
+                "toInt64(ifNotFinite(quantileTDigestMerge(0.99)(p99_duration), 0)) AS p99_duration_ms " +
-                "countIf(status = 'RUNNING') AS active_count " +
+                "FROM route_execution_stats_5m" + where +
-                "FROM route_executions" + where +
+                " GROUP BY ts_bucket ORDER BY ts_bucket";
-                " GROUP BY bucket " +
-                "ORDER BY bucket";
 
         List<StatsTimeseries.TimeseriesBucket> buckets = jdbcTemplate.query(sql, (rs, rowNum) ->
                 new StatsTimeseries.TimeseriesBucket(
-                        rs.getTimestamp("bucket").toInstant(),
+                        rs.getTimestamp("ts_bucket").toInstant(),
                         rs.getLong("total_count"),
                         rs.getLong("failed_count"),
                         rs.getLong("avg_duration_ms"),
                         rs.getLong("p99_duration_ms"),
-                        rs.getLong("active_count")
+                        0L
                 ),
                 params.toArray());
 

cameleer3-server-app/src/main/resources/clickhouse/07-stats-rollup.sql

@@ -0,0 +1,31 @@
+-- Pre-aggregated 5-minute stats rollup for route executions.
+-- Uses AggregatingMergeTree with -State/-Merge combinators so intermediate
+-- aggregates can be merged across arbitrary time windows and dimensions.
+
+CREATE TABLE IF NOT EXISTS route_execution_stats_5m (
+    bucket            DateTime('UTC'),
+    route_id          LowCardinality(String),
+    agent_id          LowCardinality(String),
+    total_count       AggregateFunction(count, UInt64),
+    failed_count      AggregateFunction(countIf, UInt8),
+    duration_sum      AggregateFunction(sum, UInt64),
+    p99_duration      AggregateFunction(quantileTDigest(0.99), UInt64)
+)
+ENGINE = AggregatingMergeTree()
+PARTITION BY toYYYYMMDD(bucket)
+ORDER BY (agent_id, route_id, bucket)
+TTL bucket + toIntervalDay(30)
+SETTINGS ttl_only_drop_parts = 1;
+
+CREATE MATERIALIZED VIEW IF NOT EXISTS route_execution_stats_5m_mv
+TO route_execution_stats_5m
+AS SELECT
+    toStartOfFiveMinutes(start_time) AS bucket,
+    route_id,
+    agent_id,
+    countState()                            AS total_count,
+    countIfState(status = 'FAILED')         AS failed_count,
+    sumState(duration_ms)                   AS duration_sum,
+    quantileTDigestState(0.99)(duration_ms) AS p99_duration
+FROM route_executions
+GROUP BY bucket, route_id, agent_id;

cameleer3-server-app/src/main/resources/clickhouse/08-stats-rollup-backfill.sql

@@ -0,0 +1,16 @@
+-- One-time idempotent backfill of existing route_executions into the
+-- 5-minute stats rollup table. Safe for repeated execution — the WHERE
+-- clause skips the INSERT if the target table already contains data.
+
+INSERT INTO route_execution_stats_5m
+SELECT
+    toStartOfFiveMinutes(start_time) AS bucket,
+    route_id,
+    agent_id,
+    countState()                            AS total_count,
+    countIfState(status = 'FAILED')         AS failed_count,
+    sumState(duration_ms)                   AS duration_sum,
+    quantileTDigestState(0.99)(duration_ms) AS p99_duration
+FROM route_executions
+WHERE (SELECT count() FROM route_execution_stats_5m) = 0
+GROUP BY bucket, route_id, agent_id;