* Strategy: * 1. Load real timeline data (30 days default) to pre-warm all caches and query plans * 2. Exercise full DTO conversion pipeline (geometry processing, coordinate extraction) * 3. Force garbage collection to free warmup objects before users arrive *
* Trade-off: Longer startup time (5-8s) for safe first-request handling.
*/
@ApplicationScoped
@Slf4j
public class TimelineWarmupService {
@Inject
TimelineStayRepository stayRepository;
@Inject
TimelineTripRepository tripRepository;
@Inject
TimelineDataGapRepository dataGapRepository;
@Inject
StreamingTimelineConverter converter;
@Inject
EntityManager entityManager;
@ConfigProperty(name = "geopulse.warmup.enabled", defaultValue = "true")
boolean warmupEnabled;
@ConfigProperty(name = "geopulse.warmup.sample-days", defaultValue = "30")
int sampleDays;
@ConfigProperty(name = "geopulse.warmup.max-items", defaultValue = "5000")
int maxWarmupItems;
void onStart(@Observes StartupEvent ev) {
if (!warmupEnabled) {
log.info("Warmup disabled via configuration");
return;
}
log.info("Starting AGGRESSIVE timeline system warmup...");
long startTime = System.currentTimeMillis();
long memoryBefore = getUsedMemory();
try {
// 1. Find a real user to warm up with
UUID warmupUserId = findWarmupUser();
if (warmupUserId == null) {
log.warn("No users found for warmup - skipping data loading");
warmupWithDummyData();
return;
}
warmupRealQueries(warmupUserId);
} finally {
long duration = System.currentTimeMillis() - startTime;
long memoryAfter = getUsedMemory();
long memoryUsed = memoryAfter - memoryBefore;
log.info("Warmup completed in {}ms, memory used: {} MB",
duration, memoryUsed / 1024 / 1024);
// CRITICAL: Force aggressive GC to free warmup objects
forceGarbageCollection();
}
}
private UUID findWarmupUser() {
// Strategy: Find user with MODERATE amount of RECENT timeline data
// Avoids:
// - Users with no recent activity (no warmup benefit)
// - Heavy users with 100K+ recent items (causes memory spike during warmup)
//
// Approach: Find user with 100-5000 timeline items in the LAST X days (stays + trips)
// Orders by item_count DESC to maximize warmup effectiveness
// This exercises the pipeline without consuming excessive memory
Instant endTime = Instant.now();
Instant startTime = endTime.minus(sampleDays, ChronoUnit.DAYS);
String sql = """
SELECT * FROM (
SELECT u.id,
(SELECT COUNT(*) FROM timeline_stays
WHERE user_id = u.id
AND timestamp >= :startTime
AND timestamp <= :endTime) +
(SELECT COUNT(*) FROM timeline_trips
WHERE user_id = u.id
AND timestamp >= :startTime
AND timestamp <= :endTime) as item_count
FROM users u
) subquery
WHERE item_count BETWEEN 10 AND 5000
ORDER BY item_count DESC
LIMIT 1
""";
try {
Object[] result = (Object[]) entityManager.createNativeQuery(sql)
.setParameter("startTime", startTime)
.setParameter("endTime", endTime)
.getSingleResult();
UUID userId = UUID.fromString(result[0].toString());
Long itemCount = ((Number) result[1]).longValue();
log.info("Selected user {} for warmup ({} timeline items in last {} days)",
userId, itemCount, sampleDays);
return userId;
} catch (Exception e) {
log.warn("Could not find user with moderate data, falling back to any user");
// Fallback: just pick first user
List