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Fix rollup queries: alias shadowed AggregateFunction column name
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Browse Source 
countMerge(total_count) in the avg expression resolved to the UInt64
alias 'total_count' instead of the AggregateFunction column. Rename
SELECT aliases (cnt, failed, avg_ms, p99_ms) to avoid shadowing.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
This commit is contained in:
hsiegeln
2026-03-15 11:05:10 +01:00
parent 035356288f
commit f660e88a17
1 changed files with 24 additions and 24 deletions
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48
cameleer3-server-app/src/main/java/com/cameleer3/server/app/search/ClickHouseSearchEngine.java
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@@ -108,19 +108,19 @@ public class ClickHouseSearchEngine implements SearchEngine {
String where = " WHERE " + String.join(" AND ", conditions); String where = " WHERE " + String.join(" AND ", conditions);
String rollupSql = "SELECT " + String rollupSql = "SELECT " +
"countMerge(total_count) AS total_count, " + "countMerge(total_count) AS cnt, " +
"countIfMerge(failed_count) AS failed_count, " + "countIfMerge(failed_count) AS failed, " +
"toInt64(ifNotFinite(sumMerge(duration_sum) / countMerge(total_count), 0)) AS avg_duration_ms, " + "toInt64(ifNotFinite(sumMerge(duration_sum) / countMerge(total_count), 0)) AS avg_ms, " +
"toInt64(ifNotFinite(quantileTDigestMerge(0.99)(p99_duration), 0)) AS p99_duration_ms " + "toInt64(ifNotFinite(quantileTDigestMerge(0.99)(p99_duration), 0)) AS p99_ms " +
"FROM route_execution_stats_5m" + where; "FROM route_execution_stats_5m" + where;
record PeriodStats(long totalCount, long failedCount, long avgDurationMs, long p99LatencyMs) {} record PeriodStats(long totalCount, long failedCount, long avgDurationMs, long p99LatencyMs) {}
PeriodStats current = jdbcTemplate.queryForObject(rollupSql, PeriodStats current = jdbcTemplate.queryForObject(rollupSql,
(rs, rowNum) -> new PeriodStats( (rs, rowNum) -> new PeriodStats(
rs.getLong("total_count"), rs.getLong("cnt"),
rs.getLong("failed_count"), rs.getLong("failed"),
rs.getLong("avg_duration_ms"), rs.getLong("avg_ms"),
rs.getLong("p99_duration_ms")), rs.getLong("p99_ms")),
params.toArray()); params.toArray());
// Active count — lightweight real-time query on base table (RUNNING is transient) // Active count — lightweight real-time query on base table (RUNNING is transient)
@@ -147,18 +147,18 @@ public class ClickHouseSearchEngine implements SearchEngine {
String prevWhere = " WHERE " + String.join(" AND ", prevConditions); String prevWhere = " WHERE " + String.join(" AND ", prevConditions);
String prevRollupSql = "SELECT " + String prevRollupSql = "SELECT " +
"countMerge(total_count) AS total_count, " + "countMerge(total_count) AS cnt, " +
"countIfMerge(failed_count) AS failed_count, " + "countIfMerge(failed_count) AS failed, " +
"toInt64(ifNotFinite(sumMerge(duration_sum) / countMerge(total_count), 0)) AS avg_duration_ms, " + "toInt64(ifNotFinite(sumMerge(duration_sum) / countMerge(total_count), 0)) AS avg_ms, " +
"toInt64(ifNotFinite(quantileTDigestMerge(0.99)(p99_duration), 0)) AS p99_duration_ms " + "toInt64(ifNotFinite(quantileTDigestMerge(0.99)(p99_duration), 0)) AS p99_ms " +
"FROM route_execution_stats_5m" + prevWhere; "FROM route_execution_stats_5m" + prevWhere;
PeriodStats prev = jdbcTemplate.queryForObject(prevRollupSql, PeriodStats prev = jdbcTemplate.queryForObject(prevRollupSql,
(rs, rowNum) -> new PeriodStats( (rs, rowNum) -> new PeriodStats(
rs.getLong("total_count"), rs.getLong("cnt"),
rs.getLong("failed_count"), rs.getLong("failed"),
rs.getLong("avg_duration_ms"), rs.getLong("avg_ms"),
rs.getLong("p99_duration_ms")), rs.getLong("p99_ms")),
prevParams.toArray()); prevParams.toArray());
// Today total (midnight UTC to now) — read from rollup with same scope // Today total (midnight UTC to now) — read from rollup with same scope
@@ -205,20 +205,20 @@ public class ClickHouseSearchEngine implements SearchEngine {
// Re-aggregate 5-minute rollup buckets into the requested interval // Re-aggregate 5-minute rollup buckets into the requested interval
String sql = "SELECT " + String sql = "SELECT " +
"toDateTime(intDiv(toUInt32(bucket), " + intervalSeconds + ") * " + intervalSeconds + ") AS ts_bucket, " + "toDateTime(intDiv(toUInt32(bucket), " + intervalSeconds + ") * " + intervalSeconds + ") AS ts_bucket, " +
"countMerge(total_count) AS total_count, " + "countMerge(total_count) AS cnt, " +
"countIfMerge(failed_count) AS failed_count, " + "countIfMerge(failed_count) AS failed, " +
"toInt64(ifNotFinite(sumMerge(duration_sum) / countMerge(total_count), 0)) AS avg_duration_ms, " + "toInt64(ifNotFinite(sumMerge(duration_sum) / countMerge(total_count), 0)) AS avg_ms, " +
"toInt64(ifNotFinite(quantileTDigestMerge(0.99)(p99_duration), 0)) AS p99_duration_ms " + "toInt64(ifNotFinite(quantileTDigestMerge(0.99)(p99_duration), 0)) AS p99_ms " +
"FROM route_execution_stats_5m" + where + "FROM route_execution_stats_5m" + where +
" GROUP BY ts_bucket ORDER BY ts_bucket"; " GROUP BY ts_bucket ORDER BY ts_bucket";
List<StatsTimeseries.TimeseriesBucket> buckets = jdbcTemplate.query(sql, (rs, rowNum) -> List<StatsTimeseries.TimeseriesBucket> buckets = jdbcTemplate.query(sql, (rs, rowNum) ->
new StatsTimeseries.TimeseriesBucket( new StatsTimeseries.TimeseriesBucket(
rs.getTimestamp("ts_bucket").toInstant(), rs.getTimestamp("ts_bucket").toInstant(),
rs.getLong("total_count"), rs.getLong("cnt"),
rs.getLong("failed_count"), rs.getLong("failed"),
rs.getLong("avg_duration_ms"), rs.getLong("avg_ms"),
rs.getLong("p99_duration_ms"), rs.getLong("p99_ms"),
0L 0L
), ),
params.toArray()); params.toArray());