From 60c196e69c1151f22c12344cee6c473f4f1516da Mon Sep 17 00:00:00 2001 From: Tom Schreiber Date: Sat, 10 Oct 2026 16:17:09 +0100 Subject: [PATCH 1/3] Add reproducible reader query-efficiency metrics for Blog 6 --- .../results_t2/utilization/reader/README.md | 6 + .../reader/query-metrics/README.md | 52 + .../reader/query-metrics/chart-data.csv | 259 ++ .../reader/query-metrics/chart-data.json | 3601 +++++++++++++++++ .../data-processing-throughput.csv | 259 ++ .../data-throughput-per-cpu-core.csv | 259 ++ .../reader/query-metrics/derive.py | 266 ++ .../effective-aggregation-throughput.csv | 222 + .../query-metrics/metrics-per-query.csv | 959 +++++ .../reader/query-metrics/provenance.json | 138 + .../queries/00-query-log-fields.sql | 13 + .../queries/01-discover-benchmark-queries.sql | 24 + .../queries/02-export-query-log.sql | 40 + .../queries/03-export-profile-stats.sql | 41 + .../queries/benchmark-aggregations.sql | 67 + .../queries/benchmark-drill-downs.sql | 56 + .../query-metrics/query-latency-per-query.csv | 959 +++++ .../reader/query-metrics/query-latency.csv | 132 + .../query-metrics/query-log-profile-stats.csv | 1242 ++++++ .../reader/query-metrics/query-log.csv | 1242 ++++++ 20 files changed, 9837 insertions(+) create mode 100644 full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/README.md create mode 100644 full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/chart-data.csv create mode 100644 full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/chart-data.json create mode 100644 full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/data-processing-throughput.csv create mode 100644 full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/data-throughput-per-cpu-core.csv create mode 100644 full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/derive.py create mode 100644 full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/effective-aggregation-throughput.csv create mode 100644 full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/metrics-per-query.csv create mode 100644 full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/provenance.json create mode 100644 full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/queries/00-query-log-fields.sql create mode 100644 full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/queries/01-discover-benchmark-queries.sql create mode 100644 full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/queries/02-export-query-log.sql create mode 100644 full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/queries/03-export-profile-stats.sql create mode 100644 full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/queries/benchmark-aggregations.sql create mode 100644 full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/queries/benchmark-drill-downs.sql create mode 100644 full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/query-latency-per-query.csv create mode 100644 full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/query-latency.csv create mode 100644 full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/query-log-profile-stats.csv create mode 100644 full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/query-log.csv diff --git a/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/README.md b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/README.md index 23cff9e..0873f9f 100644 --- a/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/README.md +++ b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/README.md @@ -1,5 +1,11 @@ # ClickHouse Cloud reader utilization (async-insert run) +For measurements during individual query executions, see +[Query throughput, CPU efficiency and latency](query-metrics/). That directory contains the SQL, +recorded result CSVs, metric definitions, and a reproducible data adapter for +the August run. Service-wide averages below include the gaps between scheduled +queries and should not be interpreted as cores used while a query is executing. + This folder contains utilization screenshots for the ClickHouse Cloud read service used in the Snowpipe Streaming vs. async inserts benchmark run. The read service was responsible for serving the continuous query workload while fresh data kept arriving in the writer service via asynchronous inserts. It ran separately from ingest, so the read path and write path were isolated from each other. diff --git a/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/README.md b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/README.md new file mode 100644 index 0000000..86cb059 --- /dev/null +++ b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/README.md @@ -0,0 +1,52 @@ +# Reader query metrics + +Measurements behind Blog 6 visual 11a, **Data processing throughput and CPU efficiency**. The four panels use the August 8–9, 2026 ClickHouse run while the raw dataset grows to **113,217,743,918 quotes**. The reader service had one node with 16 CPUs and 64 GiB; the benchmark database was `quotes_async_t4` (the historical results directory remains `results_t2`). + +| Position | Panel | Download | Calculation for one scheduled iteration | +| --- | --- | --- | --- | +| Top left | Data processing throughput | [CSV](data-processing-throughput.csv) | `sum(read_bytes) / sum(query_duration_ms / 1000)` | +| Top right | Data throughput per CPU core | [CSV](data-throughput-per-cpu-core.csv) | `sum(read_bytes) / sum((user_cpu_us + system_cpu_us) / 1000000)` | +| Bottom left | Query latency | [Display CSV](query-latency.csv), [per-query CSV](query-latency-per-query.csv) | Equal mean of query latencies within each family, using the established display smoothing below | +| Bottom right | Effective aggregation throughput | [CSV](effective-aggregation-throughput.csv) | `2 * raw_rows / ((A3.duration_ms + A4.duration_ms) / 1000)` | + +Drill-down curves summarize D1 and D2, shown with dashed lines. Interactive aggregation curves summarize A1–A4, shown with solid lines. Effective aggregation throughput uses **A3 and A4 only**, since both aggregate the entire pre-aggregated table without a symbol filter. + +## SQL and source results + +- [00-query-log-fields.sql](queries/00-query-log-fields.sql) inspects the available log columns. +- [01-discover-benchmark-queries.sql](queries/01-discover-benchmark-queries.sql) identifies the six query shapes and their CPU counters. +- [02-export-query-log.sql](queries/02-export-query-log.sql) is the extraction query behind [query-log.csv](query-log.csv): 1,241 completed initial SELECT executions, with UTC timestamps, hashes, CPU counters, rows and bytes read. +- [03-export-profile-stats.sql](queries/03-export-profile-stats.sql) is the additional profile-event export behind [query-log-profile-stats.csv](query-log-profile-stats.csv). It verifies selected rows/bytes, CPU counters and the `max_threads` setting. +- [benchmark-aggregations.sql](queries/benchmark-aggregations.sql) contains A1–A4, copied from [queries_mv.sql](../../../../queries_mv.sql) in statement order. +- [benchmark-drill-downs.sql](queries/benchmark-drill-downs.sql) contains D1–D2, copied from [queries_raw.sql](../../../../queries_raw.sql) in statement order. + +Both exports remove query IDs, hostnames and repeated query text before committing. Numeric counters, query hashes and timestamps retain their original values. The six SQL statements and their normalized query hashes are recorded in [provenance.json](provenance.json). + +[metrics-per-query.csv](metrics-per-query.csv) contains the 958 active executions joined to runner iterations. [chart-data.csv](chart-data.csv) contains supporting family summaries. [chart-data.json](chart-data.json) contains the exact four-panel payload, units, scales and row coordinates used by the visual. + +## Interpretation + +**Data throughput** measures uncompressed bytes selected by the query engine, not physical disk or network throughput. The chart uses decimal GB/s. It averages neither the idle intervals between scheduled queries nor the per-query rates: it divides the sum of bytes by the sum of execution seconds within each two-query or four-query iteration. + +**Throughput per CPU core** divides those bytes by CPU-seconds consumed across query threads (`UserTimeMicroseconds + SystemTimeMicroseconds`). A CPU-second is one core's worth of execution for one second. Thus MB/CPU-second equals MB/s per average busy core during execution. The denominator is measured CPU work, not the 16 provisioned cores, a count of threads, or elapsed time between queries. Query duration is logged in integer milliseconds; derived rates therefore have limited precision for short queries. + +**Query latency** retains the established Blog 2 display convention. Each query's runner latency is smoothed with a centered rolling median (five observations for D1/D2, seven for A1–A4); the family curve is the equal mean of those independently smoothed values. Through 100B quotes, smoothing uses the observations within that horizon, with every third aggregation observation and the final observation displayed. Beyond 100B, every observation is displayed and the same median windows use the full active run. Windows shrink at their endpoints. The raw per-query CSV is included. Runner elapsed time and server `query_duration_ms` are distinct recorded durations: the former preserves the published latency chart, while the latter is the denominator for the query-log throughput panels. + +**Effective aggregation throughput** expresses the raw quotes represented by a full-table answer, divided by execution time. Pre-aggregates represent the raw dataset without scanning all its quotes on each query. For example, at the endpoint A3 and A4 take 18 and 16 ms respectively; `2 × 113,217,743,918 / 0.034` is **6.66 trillion raw quotes/s**. This is logical answer coverage through pre-aggregation, not an actual raw scan rate or a measurement of sustained query capacity. The two symbol-filtered queries A1/A2 are excluded from this calculation. + +No smoothing or outlier removal is applied to either byte throughput panel or the effective aggregation throughput panel. All their matched active measurements are included. The dashboard-wide idle-time averages and the earlier raster-derived telemetry charts are not inputs to these panels. + +## Matching and reproduction + +The original runner files are [D1/D2](../../../raw/drilldown_20260808T065602Z.jsonl) and [A1–A4](../../../mv/dashboard_20260808T065559Z.jsonl). Every expected query is matched to exactly one query-log execution starting within 20 seconds of its scheduled runner iteration. All 1,240 runner executions match uniquely; an additional A1 execution before the runner started remains in the source CSV. Positive-row iterations through each family's first complete-dataset observation are plotted: 37 D1/D2 iterations and 221 A1–A4 iterations, totaling 958 executions. Later repeated queries are retained in the source export and omitted from the growing-dataset curves. The initial zero-row observations are also retained in the source export. + +The profile export agrees with the first export for all matched CPU counters, durations, rows and bytes. `SelectedRows` equals `read_rows`, `SelectedBytes` equals `read_bytes`, and all 958 active executions explicitly have `max_threads=16`. Query-cache hits are zero. Source hashes, matching rules, counts and formula definitions are recorded in [provenance.json](provenance.json). + +From the repository root, with Python 3.9 or newer and no additional dependencies: + +```sh +python3 full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/derive.py +python3 full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/derive.py --check +``` + +The first command regenerates all derived CSVs, the four-panel JSON and provenance from committed source exports and runner JSONL files. The second verifies byte-for-byte reproducibility without changing files. The SQL exports are bounded by dates, execution time, rows read and result count. diff --git a/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/chart-data.csv b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/chart-data.csv new file mode 100644 index 0000000..157063a --- /dev/null +++ b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/chart-data.csv @@ -0,0 +1,259 @@ +family,iteration,rows_ingested,query_count,cpu_ms_per_query,average_cores_per_query,rows_read_per_query,query_duration_ms +drill,2,3742528876,2,1223.194,1.9023234836702954,4075520,643 +drill,3,7149139248,2,1727.276,3.998324074074074,6864896,432 +drill,4,10451300014,2,1995.844,4.381655323819978,9355264,455.5 +drill,5,13693746344,2,2519.783,3.6974071900220102,12087296,681.5 +drill,6,17207612605,2,2333.1385,5.541896674584323,14786560,421 +drill,7,20600910656,2,2853.3365,4.055915422885572,18329600,703.5 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+drill,18,55419548257,2,3657587126,10.691772,342093632.93568176 +drill,19,58512627462,2,3855767775,11.342396,339942969.28091735 +drill,20,61372336571,2,4057206281,11.924024,340254789.9098492 +drill,21,64300511639,2,4196752775,11.933383,351681729.7324657 +drill,22,67296751626,2,4363457805,12.786340000000001,341259328.70547783 +drill,23,70171105615,2,4543946405,12.988388,349846832.8017303 +drill,24,73014746623,2,4713155387,13.348458999999998,353086104.3211056 +drill,25,75968034150,2,4891735344,13.98807,349707668.32021856 +drill,26,78744711237,2,5075818724,14.679839,345768010.39847916 +drill,27,81363815092,2,5207008721,14.264518,365032223.3811195 +drill,28,83951753947,2,5368489798,15.882083999999999,338021748.15345395 +drill,29,87063780214,2,5515189526,16.609174,332056821.4891361 +drill,30,90313224986,2,5721412772,15.660604,365337937.9237225 +drill,31,93296187953,2,5872414511,16.58161,354152251.2590755 +drill,32,96365836441,2,6104719005,16.940664,360358897.67957145 +drill,33,99569689379,2,6256189211,17.260173,362463876.28907305 +drill,34,102576461275,2,6392525271,18.130830999999997,352577621.56627023 +drill,35,105357098705,2,6503924616,17.722856,366979487.73042 +drill,36,107984702280,2,6664445506,17.846693,373427475.10701287 +drill,37,110886538219,2,6867118042,19.954521,344138455.74143326 +drill,38,113217743918,2,6986522748,17.683699,395082654.8223875 diff --git a/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/derive.py b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/derive.py new file mode 100644 index 0000000..e2514ff --- /dev/null +++ b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/derive.py @@ -0,0 +1,266 @@ +#!/usr/bin/env python3 +"""Reproduce per-query reader metrics and family curves from committed evidence.""" +import argparse +import collections +import csv +import datetime as dt +import hashlib +import io +import json +import pathlib +import statistics + +HERE = pathlib.Path(__file__).resolve().parent +PROVIDER = HERE.parents[3] +REPO = HERE.parents[6] +FULL_ROWS = 113217743918 +HASHES = {'A1': '4268017077458496684', 'A2': '13116456435110875434', + 'A3': '16441976537628221706', 'A4': '16076059573740575684', + 'D1': '14900422428945064879', 'D2': '4120463799277501782'} +NUMERIC = ['query_duration_ms', 'user_cpu_us', 'system_cpu_us', 'has_user_cpu', + 'has_system_cpu', 'read_rows', 'read_bytes', 'query_cache_hits'] +SOURCES = [ + ('drill', 'raw/drilldown_20260808T065602Z.jsonl', ['D1', 'D2']), + ('aggregate', 'mv/dashboard_20260808T065559Z.jsonl', ['A1', 'A2', 'A3', 'A4']), +] + +def stamp(value): + return dt.datetime.fromisoformat(value.replace('Z', '+00:00')).replace(tzinfo=dt.timezone.utc) + +def digest(path): + return hashlib.sha256(path.read_bytes()).hexdigest() + +def csv_text(rows): + stream = io.StringIO(newline='') + writer = csv.DictWriter(stream, fieldnames=list(rows[0]), lineterminator='\n') + writer.writeheader() + writer.writerows(rows) + return stream.getvalue() + +def final_charts(active): + """Four accepted panels; rates use ratios of totals, never idle time.""" + grouped = collections.defaultdict(list) + for row in active: + grouped[row['family'], row['iteration'], row['rows_ingested']].append(row) + family_rows, coverage = [], [] + for (family, iteration, rows), batch in sorted(grouped.items()): + wall_s = sum(r['query_duration_ms'] for r in batch) / 1000 + cpu_s = sum(r['cpu_ms'] for r in batch) / 1000 + family_rows.append({ + 'family': family, 'iteration': iteration, 'rows_ingested': rows, + 'query_count': len(batch), + 'total_read_bytes': sum(r['read_bytes'] for r in batch), + 'total_read_rows': sum(r['read_rows'] for r in batch), + 'total_elapsed_seconds': wall_s, 'total_cpu_seconds': cpu_s, + 'bytes_per_second': sum(r['read_bytes'] for r in batch) / wall_s, + 'bytes_per_cpu_second': sum(r['read_bytes'] for r in batch) / cpu_s, + 'average_busy_cores': cpu_s / wall_s, + }) + full = [r for r in batch if r['benchmark_query'] in ('A3', 'A4')] + if full: + assert len(full) == 2 + elapsed = sum(r['query_duration_ms'] for r in full) / 1000 + coverage.append({ + 'iteration': iteration, 'rows_ingested': rows, 'query_count': 2, + 'raw_quotes_represented': 2 * rows, + 'total_elapsed_seconds': elapsed, + 'quotes_per_second': 2 * rows / elapsed, + }) + latency_raw, latency_display = [], [] + for family, rel, queries in SOURCES: + records = [json.loads(line) for line in (PROVIDER / 'results_t2' / rel).read_text().splitlines()] + end = next(i for i, r in enumerate(records) if r['raw_rows'] == FULL_ROWS) + records = [r for r in records[:end + 1] if r['raw_rows'] > 0] + window = 5 if family == 'drill' else 7 + published = [r for r in records if r['raw_rows'] <= 100_000_000_000] + for r in records: + for q, result in zip(queries, r['result']): + latency_raw.append({'family': family, 'benchmark_query': q, + 'iteration': r['iteration'], 'rows_ingested': r['raw_rows'], + 'latency_seconds': result[0]}) + # Preserve the Blog 2 100B display horizon and its sampling convention. + indices = list(range(0, len(published), 1 if family == 'drill' else 3)) + if indices[-1] != len(published) - 1: + indices.append(len(published) - 1) + indices.extend(range(len(published), len(records))) + for i in indices: + source = published if i < len(published) else records + neighbors = source[max(0, i - window // 2):min(len(source), i + window // 2 + 1)] + latency = statistics.mean(statistics.median(r['result'][q][0] for r in neighbors) + for q in range(len(queries))) + latency_display.append({'family': family, 'iteration': records[i]['iteration'], + 'rows_ingested': records[i]['raw_rows'], 'latency_seconds': latency}) + assert len(coverage) == 221 and len(latency_display) == 131 + assert len(latency_raw) == 958 + ids = [('drill', 'drilldown', 'Drill-downs', '5 4'), + ('aggregate', 'aggregation', 'Interactive aggs', '')] + def series(rows, field): + return [{'id': sid, 'label': label, 'dash': dash, + 'points': [[r['rows_ingested'] / FULL_ROWS, r[field]] for r in rows if r['family'] == family]} + for family, sid, label, dash in ids] + def panel(pid, unit, maximum, ticks, curves, axis=None, minimum=None, sampled=True): + value = {'id': pid, 'unit': unit, 'yMax': maximum, 'yTicks': ticks, + 'color': '#e9ec5b', 'sampled': sampled, 'series': curves} + if axis: + value['axisUnit'] = axis + if minimum: + value['yMin'] = minimum + return value + data = {'fullRows': FULL_ROWS, 'rowTicks': [0, 25, 50, 75, 100], + 'playback': {'durationMs': 15000, 'holdMs': 2000}, 'panels': [ + panel('throughput', 'bytes-rate', 4.5e9, [0, 1.5e9, 3e9, 4.5e9], + series(family_rows, 'bytes_per_second'), 'Uncompressed GB/s'), + panel('efficiency', 'bytes-core-rate', 450e6, [0, 150e6, 300e6, 450e6], + series(family_rows, 'bytes_per_cpu_second'), 'Uncompressed MB/s/core'), + panel('latency', 'seconds', 2, [.01, .1, 1], + series(latency_display, 'latency_seconds'), minimum=.005, sampled=False), + panel('coverage', 'coverage-rate', 8e12, [0, 2e12, 4e12, 6e12, 8e12], + [{'id': 'full-table-aggs', 'label': 'Full-table aggs · A3/A4', 'dash': '', + 'points': [[r['rows_ingested'] / FULL_ROWS, r['quotes_per_second']] for r in coverage]}], + 'Trillion raw quotes/s'), + ]} + return { + 'data-processing-throughput.csv': csv_text([{k: r[k] for k in + ['family', 'iteration', 'rows_ingested', 'query_count', 'total_read_bytes', + 'total_elapsed_seconds', 'bytes_per_second']} for r in family_rows]), + 'data-throughput-per-cpu-core.csv': csv_text([{k: r[k] for k in + ['family', 'iteration', 'rows_ingested', 'query_count', 'total_read_bytes', + 'total_cpu_seconds', 'bytes_per_cpu_second']} for r in family_rows]), + 'effective-aggregation-throughput.csv': csv_text(coverage), + 'query-latency-per-query.csv': csv_text(latency_raw), + 'query-latency.csv': csv_text(latency_display), + 'chart-data.json': json.dumps(data, indent=2) + '\n', + } + +def derive(): + raw = list(csv.DictReader((HERE / 'query-log.csv').open(encoding='utf-8-sig'))) + assert len(raw) == 1241 + assert len({(r['benchmark_query'], r['started_at_utc']) for r in raw}) == len(raw) + for r in raw: + assert r['query_hash'] == HASHES[r['benchmark_query']] + for column in NUMERIC: + r[column] = int(r[column]) + assert r['query_duration_ms'] > 0 + assert r['user_cpu_us'] + r['system_cpu_us'] > 0 + assert r['has_user_cpu'] or r['has_system_cpu'] + assert r['query_cache_hits'] == 0 + profiles = list(csv.DictReader((HERE / 'query-log-profile-stats.csv').open())) + index = {(r['benchmark_query'], r['started_at_utc']): r for r in profiles} + assert len(index) == len(profiles) == len(raw) + for r in raw: + p = index[r['benchmark_query'], r['started_at_utc']] + for field in ['query_duration_ms', 'user_cpu_us', 'system_cpu_us', 'read_rows', 'read_bytes']: + assert int(p[field]) == r[field], (r['benchmark_query'], field) + assert int(p['selected_rows']) == r['read_rows'] + assert int(p['selected_bytes']) == r['read_bytes'] + used, active, curves, inputs = set(), [], [], [] + for family, rel, queries in SOURCES: + path = PROVIDER / 'results_t2' / rel + observations = [json.loads(line) for line in path.read_text().splitlines()] + inputs.append({'path': str(path.relative_to(REPO)), 'sha256': digest(path), + 'observations': len(observations)}) + completed = False + family_points = [] + for observation in observations: + start = stamp(observation['iteration_started_at']) + batch = [] + for q in queries: + candidates = [r for r in raw if r['benchmark_query'] == q + and 0 <= (stamp(r['started_at_utc']) - start).total_seconds() < 20] + assert len(candidates) == 1, (q, observation['iteration'], len(candidates)) + r = candidates[0] + key = (q, r['started_at_utc']) + assert key not in used + used.add(key) + cpu_ms = (r['user_cpu_us'] + r['system_cpu_us']) / 1000 + batch.append({ + 'family': family, 'benchmark_query': q, 'iteration': observation['iteration'], + 'started_at_utc': r['started_at_utc'], 'rows_ingested': observation['raw_rows'], + 'query_duration_ms': r['query_duration_ms'], + 'user_cpu_us': r['user_cpu_us'], 'system_cpu_us': r['system_cpu_us'], + 'cpu_ms': cpu_ms, 'average_cores': cpu_ms / r['query_duration_ms'], + 'read_rows': r['read_rows'], 'read_bytes': r['read_bytes'], + 'bytes_per_second': r['read_bytes'] / (r['query_duration_ms'] / 1000), + 'bytes_per_cpu_second': r['read_bytes'] / (cpu_ms / 1000), + }) + rows = observation['raw_rows'] + included = rows > 0 and not completed + if rows >= FULL_ROWS: + completed = True + if not included: + continue + active.extend(batch) + family_points.append({ + 'family': family, 'iteration': observation['iteration'], 'rows_ingested': rows, + 'query_count': len(batch), + 'cpu_ms_per_query': statistics.mean(r['cpu_ms'] for r in batch), + 'average_cores_per_query': sum(r['cpu_ms'] for r in batch) / sum(r['query_duration_ms'] for r in batch), + 'rows_read_per_query': statistics.mean(r['read_rows'] for r in batch), + 'query_duration_ms': statistics.mean(r['query_duration_ms'] for r in batch), + }) + assert len(family_points) == (37 if family == 'drill' else 221) + assert family_points[-1]['rows_ingested'] == FULL_ROWS + assert all(a['rows_ingested'] < b['rows_ingested'] for a, b in zip(family_points, family_points[1:])) + curves.extend(family_points) + assert len(used) == 1240 and len(active) == 958 + excluded = [r for r in raw if (r['benchmark_query'], r['started_at_utc']) not in used] + assert len(excluded) == 1 and excluded[0]['started_at_utc'].startswith('2026-08-08 06:54:40') + metadata = { + 'database': 'quotes_async_t4', 'complete_dataset_rows': FULL_ROWS, + 'source_query_log': {'path': str((HERE / 'query-log.csv').relative_to(REPO)), + 'sha256': digest(HERE / 'query-log.csv'), 'records': len(raw)}, + 'runner_sources': inputs, 'query_hashes': HASHES, + 'matched_runner_executions': len(used), 'active_executions': len(active), + 'active_counts': dict(collections.Counter(r['benchmark_query'] for r in active)), + 'match': 'One query of each expected type in [iteration_started_at, +20 seconds).', + 'active_window': 'Positive-row iterations through first full-dataset observation inclusive; later repeats excluded.', + 'cpu_ms_formula': '(UserTimeMicroseconds + SystemTimeMicroseconds) / 1000', + 'average_cores_formula': 'cpu_ms / query_duration_ms per query; family average is sum(cpu_ms) / sum(query_duration_ms), weighted by elapsed time', + 'rows_read_formula': 'Arithmetic mean of query_log.read_rows across the two or four queries in each iteration', + 'duration_precision': 'Integer milliseconds; average cores are approximate, particularly for very short aggregation queries.', + 'smoothing': 'None', 'outlier_exclusions': [], 'query_cache_hits': 0, + 'unmatched_before_runner': [{k: r[k] for k in ['benchmark_query', 'started_at_utc']} for r in excluded], + 'zero_row_baseline': 'Retained in query-log.csv, omitted from plotted metrics.', + 'endpoint': {f: [r for r in curves if r['family'] == f][-1] for f in ['drill', 'aggregate']}, + } + metadata['accepted_panels'] = ['Data processing throughput', 'Data throughput per CPU core', + 'Query latency', 'Effective aggregation throughput'] + metadata['family_rate_formula'] = 'sum(read_bytes) / sum(query_duration_ms / 1000) per scheduled iteration' + metadata['per_core_rate_formula'] = 'sum(read_bytes) / sum((user_cpu_us + system_cpu_us) / 1000000) per scheduled iteration' + metadata['per_core_unit'] = 'Bytes per CPU-second; equivalent to bytes/s divided by time-weighted average busy cores. Not divided by 16 provisioned cores.' + metadata['effective_aggregation_formula'] = '2 * runner.raw_rows / ((A3.query_duration_ms + A4.query_duration_ms) / 1000)' + metadata['effective_aggregation_scope'] = 'A3 and A4 full-table aggregations only; raw quotes represented by current pre-aggregates. Logical answer coverage, not raw rows scanned or sustained query capacity.' + metadata['latency_display'] = {'source': 'runner result[query_number][0], seconds', + 'family_mean': 'Equal mean of independently smoothed query latencies', + 'median_windows': {'drill': 5, 'aggregate': 7}, + 'horizon': 'Through 100B rows, median windows use observations in that horizon; beyond 100B, use the full positive-row active window through first complete dataset.', + 'sampling': 'Drill: every observation. Aggregate: every third observation through 100B, always include the last; every observation beyond 100B.', + 'boundary': 'Centered windows shrink at either endpoint.', 'outlier_exclusions': []} + metadata['sanitization'] = 'Removed query IDs, hostnames and repeated query text; measurements, hashes and UTC timestamps retained.' + metadata['profile_validation'] = { + 'path': str((HERE / 'query-log-profile-stats.csv').relative_to(REPO)), + 'sha256': digest(HERE / 'query-log-profile-stats.csv'), 'records': len(profiles), + 'matched_counter_values_equal': True, + 'selected_rows_equals_read_rows': True, 'selected_bytes_equals_read_bytes': True, + 'active_max_threads': sorted({int(index[r['benchmark_query'], r['started_at_utc']]['max_threads_setting']) for r in active}), + } + assert metadata['profile_validation']['active_max_threads'] == [16] + metadata['sql_sources'] = [{'path': str(p.relative_to(REPO)), 'sha256': digest(p)} + for p in sorted((HERE / 'queries').glob('*.sql'))] + return {**final_charts(active), 'metrics-per-query.csv': csv_text(active), 'chart-data.csv': csv_text(curves), + 'provenance.json': json.dumps(metadata, indent=2) + '\n'} + +def main(): + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument('--check', action='store_true', help='Verify committed outputs without rewriting them') + args = parser.parse_args() + for name, expected in derive().items(): + path = HERE / name + if args.check: + assert path.read_text() == expected, f'Stale derived evidence: {path}' + else: + path.write_text(expected) + print('Verified' if args.check else 'Generated', '958 per-query measurements and 258 family observations.') + +if __name__ == '__main__': + main() diff --git a/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/effective-aggregation-throughput.csv b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/effective-aggregation-throughput.csv new file mode 100644 index 0000000..8ef970a --- /dev/null +++ b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/effective-aggregation-throughput.csv @@ -0,0 +1,222 @@ +iteration,rows_ingested,query_count,raw_quotes_represented,total_elapsed_seconds,quotes_per_second +2,724786266,2,1449572532,0.01,144957253200.0 +3,1370669828,2,2741339656,0.014,195809975428.5714 +4,1975682003,2,3951364006,0.069,57266145014.49275 +5,2574084882,2,5148169764,0.018,286009431333.3334 +6,3146910669,2,6293821338,0.018,349656741000.0 +7,3738865972,2,7477731944,0.02,373886597200.0 +8,4293755746,2,8587511492,0.021,408929118666.6666 +9,4891042750,2,9782085500,0.021,465813595238.0952 +10,5469535309,2,10939070618,0.025,437562824720.0 +11,6010532017,2,12021064034,0.023,522654958000.0 +12,6539371357,2,13078742714,0.022,594488305181.8182 +13,7146131616,2,14292263232,0.02,714613161600.0 +14,7727462172,2,15454924344,0.022,702496561090.9092 +15,8305203448,2,16610406896,0.022,755018495272.7273 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18:45:59.756949,110384302735,16,106531,53759,160.29,10.018125,1867651,63500134,3968758375.0,396157801.4848088 +aggregate,A1,217,2026-08-09 18:55:59.989625,110882914315,7,20005,3631,23.636,3.3765714285714283,65637,4645513,663644714.2857143,196543958.36859027 +aggregate,A2,217,2026-08-09 18:56:00.068765,110882914315,12,25834,10871,36.705,3.05875,244691,9493896,791158000.0,258654025.3371475 +aggregate,A3,217,2026-08-09 18:56:00.152835,110882914315,20,138835,30392,169.227,8.46135,1887265,42972301,2148615050.0,253932888.95979953 +aggregate,A4,217,2026-08-09 18:56:00.246878,110882914315,17,86692,73614,160.306,9.429764705882354,1887265,64167010,3774529999.9999995,400278280.2889474 +aggregate,A1,218,2026-08-09 19:05:59.485717,111392632185,9,13545,12736,26.281,2.920111111111111,63190,4472367,496929666.6666667,170174917.24059206 +aggregate,A2,218,2026-08-09 19:05:59.564950,111392632185,12,32353,3789,36.142,3.0118333333333336,243414,9445128,787094000.0,261333849.8146201 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19:25:59.464512,112455078822,7,15196,8976,24.172,3.4531428571428573,65337,4623630,660518571.4285715,191280407.08257487 +aggregate,A2,220,2026-08-09 19:25:59.539415,112455078822,12,28109,7015,35.124,2.927,232787,9032511,752709250.0,257160659.37820292 +aggregate,A3,220,2026-08-09 19:25:59.618525,112455078822,25,150128,22542,172.67,6.9068,1906482,43410169,1736406760.0,251405391.78780335 +aggregate,A4,220,2026-08-09 19:25:59.714243,112455078822,19,134493,31817,166.31,8.753157894736843,1906482,64820388,3411599368.421053,389756406.7103601 +aggregate,A1,221,2026-08-09 19:35:59.951124,112958830367,7,11115,8561,19.676,2.8108571428571425,52247,3698915,528416428.57142854,187991207.56251273 +aggregate,A2,221,2026-08-09 19:36:00.025099,112958830367,13,27198,8680,35.878,2.759846153846154,238997,9274795,713445769.2307693,258509253.58158204 +aggregate,A3,221,2026-08-09 19:36:00.108547,112958830367,19,139508,34958,174.466,9.182421052631579,1912692,43553093,2292268052.631579,249636565.29065832 +aggregate,A4,221,2026-08-09 19:36:00.199902,112958830367,17,119677,47595,167.272,9.839529411764705,1912692,65031528,3825383999.9999995,388777129.46578026 +aggregate,A1,222,2026-08-09 19:45:59.428295,113217743918,7,8272,6271,14.543,2.0775714285714284,34406,2331678,333096857.14285713,160329918.17369184 +aggregate,A2,222,2026-08-09 19:45:59.508186,113217743918,13,22454,8434,30.888,2.3760000000000003,213837,8247769,634443769.2307693,267021788.3967884 +aggregate,A3,222,2026-08-09 19:45:59.596845,113217743918,18,107447,61802,169.249,9.402722222222222,1887532,42981043,2387835722.2222223,253951532.948496 +aggregate,A4,222,2026-08-09 19:45:59.686895,113217743918,16,95058,64434,159.492,9.96825,1887532,64176088,4011005500.0,402378100.4689891 diff --git a/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/provenance.json b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/provenance.json new file mode 100644 index 0000000..c81b30a --- /dev/null +++ b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/provenance.json @@ -0,0 +1,138 @@ +{ + "database": "quotes_async_t4", + "complete_dataset_rows": 113217743918, + "source_query_log": { + "path": "full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/query-log.csv", + "sha256": "584aa0abcecab47e6f0c866503347ccb02d7edf290e78db50f3a9e1fc125944e", + "records": 1241 + }, + "runner_sources": [ + { + "path": "full-path-realtime/quotes/clickhouse-cloud/results_t2/raw/drilldown_20260808T065602Z.jsonl", + "sha256": "fa4033841b2d0596c227b0baacfc666086d41bdcceb9173da9e3c9e699f1f378", + "observations": 48 + }, + { + "path": "full-path-realtime/quotes/clickhouse-cloud/results_t2/mv/dashboard_20260808T065559Z.jsonl", + "sha256": "0fbfd6c089fc9e5ef4af88199db2bc08acc6f538a56d2be50a55a06d5765e960", + "observations": 286 + } + ], + "query_hashes": { + "A1": "4268017077458496684", + "A2": "13116456435110875434", + "A3": "16441976537628221706", + "A4": "16076059573740575684", + "D1": "14900422428945064879", + "D2": "4120463799277501782" + }, + "matched_runner_executions": 1240, + "active_executions": 958, + "active_counts": { + "D1": 37, + "D2": 37, + "A1": 221, + "A2": 221, + "A3": 221, + "A4": 221 + }, + "match": "One query of each expected type in [iteration_started_at, +20 seconds).", + "active_window": "Positive-row iterations through first full-dataset observation inclusive; later repeats excluded.", + "cpu_ms_formula": "(UserTimeMicroseconds + SystemTimeMicroseconds) / 1000", + "average_cores_formula": "cpu_ms / query_duration_ms per query; family average is sum(cpu_ms) / sum(query_duration_ms), weighted by elapsed time", + "rows_read_formula": "Arithmetic mean of query_log.read_rows across the two or four queries in each iteration", + "duration_precision": "Integer milliseconds; average cores are approximate, particularly for very short aggregation queries.", + "smoothing": "None", + "outlier_exclusions": [], + "query_cache_hits": 0, + "unmatched_before_runner": [ + { + "benchmark_query": "A1", + "started_at_utc": "2026-08-08 06:54:40.809273" + } + ], + "zero_row_baseline": "Retained in query-log.csv, omitted from plotted metrics.", + "endpoint": { + "drill": { + "family": "drill", + "iteration": 38, + "rows_ingested": 113217743918, + "query_count": 2, + "cpu_ms_per_query": 8841.8495, + "average_cores_per_query": 9.366365995762711, + "rows_read_per_query": 89612288, + "query_duration_ms": 944 + }, + "aggregate": { + "family": "aggregate", + "iteration": 222, + "rows_ingested": 113217743918, + "query_count": 4, + "cpu_ms_per_query": 93.54299999999999, + "average_cores_per_query": 6.929111111111111, + "rows_read_per_query": 1005826.75, + "query_duration_ms": 13.5 + } + }, + "accepted_panels": [ + "Data processing throughput", + "Data throughput per CPU core", + "Query latency", + "Effective aggregation throughput" + ], + "family_rate_formula": "sum(read_bytes) / sum(query_duration_ms / 1000) per scheduled iteration", + "per_core_rate_formula": "sum(read_bytes) / sum((user_cpu_us + system_cpu_us) / 1000000) per scheduled iteration", + "per_core_unit": "Bytes per CPU-second; equivalent to bytes/s divided by time-weighted average busy cores. Not divided by 16 provisioned cores.", + "effective_aggregation_formula": "2 * runner.raw_rows / ((A3.query_duration_ms + A4.query_duration_ms) / 1000)", + "effective_aggregation_scope": "A3 and A4 full-table aggregations only; raw quotes represented by current pre-aggregates. Logical answer coverage, not raw rows scanned or sustained query capacity.", + "latency_display": { + "source": "runner result[query_number][0], seconds", + "family_mean": "Equal mean of independently smoothed query latencies", + "median_windows": { + "drill": 5, + "aggregate": 7 + }, + "horizon": "Through 100B rows, median windows use observations in that horizon; beyond 100B, use the full positive-row active window through first complete dataset.", + "sampling": "Drill: every observation. Aggregate: every third observation through 100B, always include the last; every observation beyond 100B.", + "boundary": "Centered windows shrink at either endpoint.", + "outlier_exclusions": [] + }, + "sanitization": "Removed query IDs, hostnames and repeated query text; measurements, hashes and UTC timestamps retained.", + "profile_validation": { + "path": "full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/query-log-profile-stats.csv", + "sha256": "69cc86955efb5874e980c19cc4c435c304bbaf89669ecfb6e312e1cec3703fdf", + "records": 1241, + "matched_counter_values_equal": true, + "selected_rows_equals_read_rows": true, + "selected_bytes_equals_read_bytes": true, + "active_max_threads": [ + 16 + ] + }, + "sql_sources": [ + { + "path": "full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/queries/00-query-log-fields.sql", + "sha256": "2ebb447fb5825aa56894b0a82888edffd3efe9172580a2233ceadcf6dac60d6f" + }, + { + "path": "full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/queries/01-discover-benchmark-queries.sql", + "sha256": "927613dba14f187142a082486ed4165f98d39244ac994f8ceb138fd04e347fb5" + }, + { + "path": "full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/queries/02-export-query-log.sql", + "sha256": "ca91b27dbd7a981d8d275166bceaf3b599f9584d2a1a68557c4fb911b80114bc" + }, + { + "path": "full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/queries/03-export-profile-stats.sql", + "sha256": "120742c85f4eb1a81bc0f02d069cd3687136199d9b272a3268bbb52d6bd9e00e" + }, + { + "path": "full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/queries/benchmark-aggregations.sql", + "sha256": "e31042b3aec1882f293f57ec103eda7953d947fdb47607ee11a6fb6f31a4d108" + }, + { + "path": "full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/queries/benchmark-drill-downs.sql", + "sha256": "44f8199cc3b18ff091324789918535a3d1c5f8f5ba99939bf02df7433d5ad29b" + } + ] +} diff --git a/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/queries/00-query-log-fields.sql b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/queries/00-query-log-fields.sql new file mode 100644 index 0000000..e987ec7 --- /dev/null +++ b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/queries/00-query-log-fields.sql @@ -0,0 +1,13 @@ +SELECT name, type, comment +FROM system.columns +WHERE database = 'system' + AND table = 'query_log' + AND name IN ('event_date', 'event_time', 'query_start_time', + 'query_start_time_microseconds', 'query_duration_ms', + 'read_rows', 'read_bytes', 'result_rows', 'query', + 'normalized_query_hash', 'is_initial_query', 'current_database', + 'ProfileEvents', 'query_id', 'initial_query_id', 'hostname', + 'type', 'query_kind', 'tables') +ORDER BY position +LIMIT 30 +SETTINGS max_execution_time = 10, max_rows_to_read = 100000; diff --git a/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/queries/01-discover-benchmark-queries.sql b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/queries/01-discover-benchmark-queries.sql new file mode 100644 index 0000000..dba6376 --- /dev/null +++ b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/queries/01-discover-benchmark-queries.sql @@ -0,0 +1,24 @@ +SELECT + toString(normalized_query_hash) AS query_hash, + count() AS executions, + countIf(mapContains(ProfileEvents, 'UserTimeMicroseconds')) AS with_user_cpu, + countIf(mapContains(ProfileEvents, 'SystemTimeMicroseconds')) AS with_system_cpu, + round(avg(ProfileEvents['UserTimeMicroseconds'] + + ProfileEvents['SystemTimeMicroseconds']) / 1000, 3) AS cpu_ms_per_query, + round(avg(query_duration_ms), 3) AS duration_ms, + round(avg(read_rows)) AS rows_read_per_query, + any(query) AS example_query +FROM clusterAllReplicas(default, merge('system', '^query_log')) +WHERE event_date BETWEEN '2026-08-08' AND '2026-08-09' + AND query_start_time >= toDateTime('2026-08-08 06:50:00', 'UTC') + AND query_start_time < toDateTime('2026-08-09 20:00:00', 'UTC') + AND type = 'QueryFinish' + AND is_initial_query = 1 + AND query_kind = 'Select' + AND current_database = 'quotes_async_t4' +GROUP BY normalized_query_hash +ORDER BY executions DESC +LIMIT 20 +SETTINGS skip_unavailable_shards = 1, + max_execution_time = 30, + max_rows_to_read = 10000000; diff --git a/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/queries/02-export-query-log.sql b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/queries/02-export-query-log.sql new file mode 100644 index 0000000..a95b4c3 --- /dev/null +++ b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/queries/02-export-query-log.sql @@ -0,0 +1,40 @@ +SELECT + multiIf( + normalized_query_hash = 4268017077458496684, 'A1', + normalized_query_hash = 13116456435110875434, 'A2', + normalized_query_hash = 16441976537628221706, 'A3', + normalized_query_hash = 16076059573740575684, 'A4', + normalized_query_hash = 14900422428945064879, 'D1', 'D2' + ) AS benchmark_query, + toString(toTimeZone(query_start_time_microseconds, 'UTC')) AS started_at_utc, + toString(toTimeZone(event_time, 'UTC')) AS finished_at_utc, + query_id, + hostname, + toString(normalized_query_hash) AS query_hash, + query_duration_ms, + ProfileEvents['UserTimeMicroseconds'] AS user_cpu_us, + ProfileEvents['SystemTimeMicroseconds'] AS system_cpu_us, + mapContains(ProfileEvents, 'UserTimeMicroseconds') AS has_user_cpu, + mapContains(ProfileEvents, 'SystemTimeMicroseconds') AS has_system_cpu, + read_rows, + read_bytes, + ProfileEvents['QueryCacheHits'] AS query_cache_hits, + query +FROM clusterAllReplicas(default, merge('system', '^query_log')) +WHERE event_date BETWEEN '2026-08-08' AND '2026-08-10' + AND query_start_time >= toDateTime('2026-08-08 06:50:00', 'UTC') + AND query_start_time < toDateTime('2026-08-10 06:30:00', 'UTC') + AND type = 'QueryFinish' + AND is_initial_query = 1 + AND query_kind = 'Select' + AND current_database = 'quotes_async_t4' + AND normalized_query_hash IN ( + 4268017077458496684, 13116456435110875434, + 16441976537628221706, 16076059573740575684, + 14900422428945064879, 4120463799277501782 + ) +ORDER BY query_start_time_microseconds, benchmark_query +LIMIT 3000 +SETTINGS skip_unavailable_shards = 1, + max_execution_time = 30, + max_rows_to_read = 10000000; diff --git a/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/queries/03-export-profile-stats.sql b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/queries/03-export-profile-stats.sql new file mode 100644 index 0000000..9d21e9a --- /dev/null +++ b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/queries/03-export-profile-stats.sql @@ -0,0 +1,41 @@ +SELECT + multiIf( + normalized_query_hash = 4268017077458496684, 'A1', + normalized_query_hash = 13116456435110875434, 'A2', + normalized_query_hash = 16441976537628221706, 'A3', + normalized_query_hash = 16076059573740575684, 'A4', + normalized_query_hash = 14900422428945064879, 'D1', 'D2' + ) AS benchmark_query, + toString(toTimeZone(query_start_time_microseconds, 'UTC')) AS started_at_utc, + query_id, + query_duration_ms, + read_rows, + read_bytes, + peak_threads_usage, + length(thread_ids) AS total_distinct_threads, + ProfileEvents['UserTimeMicroseconds'] AS user_cpu_us, + ProfileEvents['SystemTimeMicroseconds'] AS system_cpu_us, + ProfileEvents['OSCPUVirtualTimeMicroseconds'] AS os_cpu_us, + ProfileEvents['RealTimeMicroseconds'] AS thread_wall_us, + ProfileEvents['SelectedRows'] AS selected_rows, + ProfileEvents['SelectedBytes'] AS selected_bytes, + ProfileEvents['QueryTimeMicroseconds'] AS query_time_us, + ProfileEvents['SelectQueryTimeMicroseconds'] AS select_query_time_us, + ProfileEvents['OSCPUWaitMicroseconds'] AS cpu_wait_us, + ProfileEvents['OSIOWaitMicroseconds'] AS io_wait_us, + mapContains(ProfileEvents, 'QueryTimeMicroseconds') AS has_query_time, + mapContains(ProfileEvents, 'SelectQueryTimeMicroseconds') AS has_select_query_time, + mapContains(Settings, 'max_threads') AS has_max_threads_setting, + Settings['max_threads'] AS max_threads_setting +FROM clusterAllReplicas(default, merge('system', '^query_log')) +WHERE event_date BETWEEN '2026-08-08' AND '2026-08-10' + AND query_start_time >= toDateTime('2026-08-08 06:50:00', 'UTC') + AND query_start_time < toDateTime('2026-08-10 06:30:00', 'UTC') + AND type = 'QueryFinish' + AND is_initial_query = 1 + AND query_kind = 'Select' + AND current_database = 'quotes_async_t4' + AND normalized_query_hash IN (4268017077458496684, 13116456435110875434, 16441976537628221706, 16076059573740575684, 14900422428945064879, 4120463799277501782) +ORDER BY query_start_time_microseconds, benchmark_query +LIMIT 3000 +SETTINGS skip_unavailable_shards = 1, max_execution_time = 30, max_rows_to_read = 10000000, timeout_before_checking_execution_speed = 0; diff --git a/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/queries/benchmark-aggregations.sql b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/queries/benchmark-aggregations.sql new file mode 100644 index 0000000..a5dd957 --- /dev/null +++ b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/queries/benchmark-aggregations.sql @@ -0,0 +1,67 @@ +-- ============================================================================= +-- Dashboard queries — run every ~10 minutes against the MV. +-- All queries filter by sym only or not at all; never by day. Cost scales +-- with the total data volume, so the benchmark answer changes as the dataset +-- grows. (sym, day) sort key lets sym-filtered queries do a prefix scan. +-- ============================================================================= + +-- ----------------------------------------------------------------------------- +-- 1. SINGLE-SYMBOL ALL-TIME SUMMARY +-- Filter by one sym. Uses (sym, day) sort as a single-sym prefix scan. +-- Cost grows with how much historical data we have for that symbol. +-- ----------------------------------------------------------------------------- +SELECT + count() AS days_traded, + sum(n_quotes) AS total_quotes, + min(bp_min) AS lowest_bid, + max(bp_max) AS highest_bid, + min(ap_min) AS lowest_ask, + max(ap_max) AS highest_ask, + sum(spread_sum) / sum(n_quotes) AS avg_spread, + sum(bs_sum) AS total_bid_volume, + sum(as_sum) AS total_ask_volume +FROM quotes_daily +WHERE sym = 'AAPL'; + +-- ----------------------------------------------------------------------------- +-- 2. WATCHLIST ALL-TIME SUMMARY +-- Small set of symbols, no day filter. Each sym is a prefix scan in +-- (sym, day) order. Cost scales with total data across those symbols. +-- ----------------------------------------------------------------------------- +SELECT + sym, + count() AS days_traded, + sum(n_quotes) AS total_quotes, + min(bp_min) AS lowest_bid, + max(bp_max) AS highest_bid, + sum(spread_sum) / sum(n_quotes) AS avg_spread +FROM quotes_daily +WHERE sym IN ('AAPL', 'MSFT', 'GOOGL', 'AMZN', 'TSLA', 'META', 'NVDA', 'NFLX') +GROUP BY sym +ORDER BY total_quotes DESC; + +-- ----------------------------------------------------------------------------- +-- 3. TOP MOVERS HISTORICALLY — no filter, full MV scan +-- Per-symbol historical price range across the entire data window. +-- Cost scales with the full MV size. +-- ----------------------------------------------------------------------------- +SELECT + sym, + (max(bp_max) - min(bp_min)) / min(bp_min) * 100 AS pct_range +FROM quotes_daily +GROUP BY sym +ORDER BY abs(pct_range) DESC +LIMIT 20; + +-- ----------------------------------------------------------------------------- +-- 4. DAILY MARKET ACTIVITY TIME SERIES — no filter, full MV scan +-- Market-wide totals per day. Cost scales with the full MV size. +-- ----------------------------------------------------------------------------- +SELECT + day, + sum(n_quotes) AS total_quotes, + sum(bs_sum) + sum(as_sum) AS total_volume, + sum(spread_sum) / sum(n_quotes) AS avg_spread +FROM quotes_daily +GROUP BY day +ORDER BY day; diff --git a/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/queries/benchmark-drill-downs.sql b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/queries/benchmark-drill-downs.sql new file mode 100644 index 0000000..7b91ab3 --- /dev/null +++ b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/queries/benchmark-drill-downs.sql @@ -0,0 +1,56 @@ +-- ============================================================================= +-- DRILLDOWN — TWO queries, run ~hourly against the raw quotes table. +-- Both are single-symbol (sym only, no time filter) drilldowns; cost scales with +-- that symbol's data volume. Exercises the (sym, t) sort key. +-- +-- Q1 = HOURLY OHLCV BARS — the canonical "show me this symbol's chart" query: +-- per-hour OHLC + VWAP + volume + volatility + spread. High-cardinality +-- GROUP BY (where ClickHouse's hash aggregation wins). +-- Q2 = RISK & LIQUIDITY PROFILE (a.k.a. "B7") — a single-row microstructure +-- stats panel: realized volatility, spread distribution + tail risk +-- (skew/kurtosis/p95/p99), order-book imbalance, spread-vs-depth corr. +-- Single-pass aggregation (where ClickHouse stays I/O-bound while the +-- per-aggregate overhead accumulates on the other engine). +-- +-- The runner times each query separately -> result: [[q1_secs],[q2_secs]]. +-- v1 single-query drilldown is preserved in queries_raw_v1.sql. +-- (A daily-bars variant of Q1 lives in the project history if a coarser grain +-- is wanted.) +-- ============================================================================= + +-- ----------------------------------------------------------------------------- +-- Q1. HOURLY OHLCV BARS +-- ----------------------------------------------------------------------------- +SELECT + toStartOfHour(fromUnixTimestamp64Milli(t)) AS hour, + argMin(bp, t) AS open, + max(bp) AS high, + min(bp) AS low, + argMax(bp, t) AS close, + sum(bs) AS volume, + sum(bp * bs) / sum(bs) AS vwap, + stddevPop(bp) AS volatility, + avg(ap - bp) AS avg_spread, + count() AS ticks +FROM quotes +WHERE sym = 'AAPL' +GROUP BY hour +ORDER BY hour; + +-- ----------------------------------------------------------------------------- +-- Q2. RISK & LIQUIDITY PROFILE ("B7") +-- ----------------------------------------------------------------------------- +SELECT + count() AS ticks, + avg((bp + ap) / 2) AS avg_mid, + stddevPop((bp + ap) / 2) AS mid_volatility, + avg(ap - bp) AS avg_spread, + stddevPop(ap - bp) AS spread_volatility, + skewPop(ap - bp) AS spread_skew, + kurtPop(ap - bp) AS spread_kurtosis, + max(ap - bp) AS max_spread, + corr(ap - bp, bs + `as`) AS corr_spread_depth, + avg((toFloat64(bs) - toFloat64(`as`)) / nullIf(bs + `as`, 0)) AS avg_book_imbalance, + quantilesTDigest(0.95, 0.99)(ap - bp) AS spread_p95_p99 +FROM quotes +WHERE sym = 'AAPL'; \ No newline at end of file diff --git a/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/query-latency-per-query.csv b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/query-latency-per-query.csv new file mode 100644 index 0000000..273fc9f --- /dev/null +++ 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06:15:59,16076059573740575684,16,145626,8866,1,1,1887532,64176088,0 +A1,2026-08-10 06:26:00.054950,2026-08-10 06:26:00,4268017077458496684,6,11068,858,1,1,32768,2322567,0 +A2,2026-08-10 06:26:00.129488,2026-08-10 06:26:00,13116456435110875434,12,12185,17044,1,1,212199,8238658,0 +A3,2026-08-10 06:26:00.210284,2026-08-10 06:26:00,16441976537628221706,17,132641,31026,1,1,1887532,42981043,0 +A4,2026-08-10 06:26:00.299621,2026-08-10 06:26:00,16076059573740575684,15,126863,31091,1,1,1887532,64176088,0 From 76d3f01aad343e186bef5b2a8617d0f37bbf23ad Mon Sep 17 00:00:00 2001 From: Tom Schreiber Date: Sun, 11 Oct 2026 12:29:20 +0100 Subject: [PATCH 2/3] Add reader query resources and reproducible display data --- .../results_t2/utilization/reader/README.md | 2 +- .../reader/query-metrics/README.md | 10 +- .../query-metrics/query-resources/.gitignore | 2 + .../query-resources/FILES.sha256 | 39 + .../query-metrics/query-resources/README.md | 37 + .../query-resources/checksums.py | 14 + 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full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/query-resources/source-manifest.json create mode 100644 full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/query-resources/source-provenance.json diff --git a/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/README.md b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/README.md index 0873f9f..e521b71 100644 --- a/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/README.md +++ b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/README.md @@ -1,7 +1,7 @@ # ClickHouse Cloud reader utilization (async-insert run) For measurements during individual query executions, see -[Query throughput, CPU efficiency and latency](query-metrics/). That directory contains the SQL, +[Query throughput, CPU efficiency and latency](query-metrics/), including the current [query-execution CPU/headroom and per-query peak memory data](query-metrics/query-resources/). That directory contains the SQL, recorded result CSVs, metric definitions, and a reproducible data adapter for the August run. Service-wide averages below include the gaps between scheduled queries and should not be interpreted as cores used while a query is executing. diff --git a/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/README.md b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/README.md index 86cb059..7ab5a00 100644 --- a/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/README.md +++ b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/README.md @@ -1,6 +1,14 @@ # Reader query metrics -Measurements behind Blog 6 visual 11a, **Data processing throughput and CPU efficiency**. The four panels use the August 8–9, 2026 ClickHouse run while the raw dataset grows to **113,217,743,918 quotes**. The reader service had one node with 16 CPUs and 64 GiB; the benchmark database was `quotes_async_t4` (the historical results directory remains `results_t2`). +Original numeric extraction behind Blog 6 reader visuals **11a and 11b**. The measurements use the August 8–9, 2026 ClickHouse run while the raw dataset grows to **113,217,743,918 quotes**. The reader service had one node with 16 CPUs and 64 GiB; the benchmark database was `quotes_async_t4` (the historical results directory remains `results_t2`). + +## Current blog values and resource band + +Use [query-resources/](query-resources/README.md) for the current two-panel layouts and their **Resource utilization during query execution** bands. It includes extraction SQL/results, all 958 matched per-query memory peaks, CPU during execution with headroom, shared Gaussian display smoothing, exact 11a/11b payloads and a dependency-free reproducer. These calculations exclude the idle gaps in the query schedule and preserve the original 16-vCPU / 64-GiB setup. + +The tables and adapters below retain the original four-panel extraction as frozen evidence. Their byte-rate and CPU-rate CSVs are inputs to the current display adapter; the older median-smoothed latency payload is preserved for traceability, rather than used as the current blog curve. + +## Frozen original extraction | Position | Panel | Download | Calculation for one scheduled iteration | | --- | --- | --- | --- | diff --git a/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/query-resources/.gitignore b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/query-resources/.gitignore new file mode 100644 index 0000000..7a60b85 --- /dev/null +++ b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/query-resources/.gitignore @@ -0,0 +1,2 @@ +__pycache__/ +*.pyc diff --git a/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/query-resources/FILES.sha256 b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/query-resources/FILES.sha256 new file mode 100644 index 0000000..92de3a7 --- /dev/null +++ b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/query-resources/FILES.sha256 @@ -0,0 +1,39 @@ +862263fa1f46c20f0d1e4dac5ffcc75abd55c08211b2c3864c5f8764b9d87793 .gitignore +9fba9a0689eb3c493ef6438341cf9ca49555a4ef74f1ec1341f122ba01e0644a README.md +89b6267012fbc2e9550ddd5815f5c26902328208d520c0fc9c853d003c23f159 checksums.py +18aa685c0f59669414df754d750e7c35bafcc2bb1b21e17a21bc0776eabda0c5 config.json +60810f26906011e547646297b811033999026e0b93c6519f7bc4ef56f1fac163 derive.py +1d39ac9181affb70cc673fab2a32f58c64485159684bd0553a01a1c3d999a822 display-metrics.csv +34581b8ab5b6e2b542b8ae041d6dcb7a29647c281aa0becf13c2b695ee9ad66f evidence/01-schema.csv +5dcfee38214afaf23f32741768f2908947a2b776fd78959a03b607a80079ca1b evidence/02-log-coverage.csv +64da399fdc9ff62df351be7c3e54dbef961523775b86f3b69ba21b06c8e44008 evidence/03-resource-series.csv +7033d6651a860fe25663bf6f2f16e5b9329b5e6c0fcb0c5cc569f6a3bcaa94ce evidence/04-capacity.csv +515e1d4641b57ce7042f86a515d723b9618bee428f2c703caa64d685d22750ee evidence/07-memory-metric-descriptions.csv +8795576d9b7422def351bfdb8cf784a7e9b867ab386709259fb11d8905eff536 evidence/08-memory-cache-check.csv +82bb6d9ccc449df66843ec93626c0c91e0fced5e46b66aec65fa23c40ea3171b evidence/09-query-memory-schema.csv +d783fb8c95cefa104f645f103ad302d63910d776b056e012695aad07759c113f evidence/10-query-peak-memory.csv +1f7aea591df5d849e8eda97ba9eb841181e98a54945d6bd5d9e1007e53ac1775 evidence/active-newpart-series.csv +0fbfd6c089fc9e5ef4af88199db2bc08acc6f538a56d2be50a55a06d5765e960 evidence/dashboard_20260808T065559Z.jsonl +0c69764e38967b6abc54f60acc47bf76568891c3b3c6e3e7592cd9b20b1a86cd evidence/data-processing-throughput.csv +2b9a53886fde0a8d5ad631346cb87f1af244d74fae2fbfe4a2842aa25a3e8749 evidence/data-throughput-per-cpu-core.csv +fa4033841b2d0596c227b0baacfc666086d41bdcceb9173da9e3c9e699f1f378 evidence/drilldown_20260808T065602Z.jsonl +02374eee080f0f9532a530f85f4b976f6cd3a2da1ab215b9070e9e5b4d81f140 evidence/effective-aggregation-throughput.csv +4280337315e9bd4e9c6ba52fd084edfdcec6d016b2d1891e24f345cd76778c49 evidence/metrics-per-query.csv +aea72e66f238109360b036992e1ac5f98194df90534486b55988e1980be0f747 evidence/prior-chart-data.json +e7a2aadb950ba8563dd616c6619d565714e92b95769bf613d82565f22f65d9f8 evidence/queries/01-schema.sql +e609e2228b46f736b025e83e58e6b3c28d32d49d1a517fd8fc3546f16589d4a7 evidence/queries/02-log-coverage.sql +cde680516de4c76ffb3655abfce9fdfbdb052cce11f702f71fdb27dd7d5a0eb2 evidence/queries/03-resource-series.sql +cd955cb1f13c06d71cee020a8c69b8744d0d5600678ed93dcadda22986e52472 evidence/queries/04-capacity.sql +9ca68ce60d0cf1f9c1a763e7ae67467956e6a20f7609d8c56561ff83d040c5c2 evidence/queries/05-memory-definition.sql +c36e638891c8eabfbc86b06857b73ebcdf1a7afd52a42f2fd1b363f316ddf8dd evidence/queries/06-historical-memory-metrics.sql +73bf6063ac170f07df71552cb15f92878d27c59f40f0ab8d94a23a250df3efab evidence/queries/07-memory-metric-descriptions.sql +0133aa7051bc7619f2908a71e3a25689c6ad9025cb79fd8e2db857b8331fcb1e evidence/queries/08-memory-cache-check.sql +4b6e5a004785f50758280b04e0ef92393324f4f65fd8beefd9e2f4ed8d8b58bd evidence/queries/09-query-memory-schema.sql +5bde6168370105860fd1f233efbf937400ff397df76769a403070e11e5647a19 evidence/queries/10-query-peak-memory.sql +d84358b7fd9ebb53ef9435675e7815ae8a33491f70a9cd38c03525e9aeed158d latency/chart-data.json +2b9a126466c535f16259df9913bc22e36b6247e8cb96d48a8ed6b4433cb7aed0 matched-query-memory.csv +de918e3f4d9bc2eac4da338459410fa8b26d87d98a3421bff37e77ccf1027e32 processing/chart-data.json +cda1908a71e5b4271edcd5d674af7fb41625085abb80d85ea69171c7dae476f1 query-memory-display.csv +4d170d9557d7315551d7796aa2f53483396900fbe3e8ddd4221f76bbab68bccd resource-display.csv +d3a70969388012773531530bd7d815bfd30b1dab7856cff994c5092fc243e7ec source-manifest.json +340abf4cc5e9141d56eebf1b965c906df0b72d16c2ce40094baa1ae40a638bcf source-provenance.json diff --git a/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/query-resources/README.md b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/query-resources/README.md new file mode 100644 index 0000000..9ba30cf --- /dev/null +++ b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/query-resources/README.md @@ -0,0 +1,37 @@ +# Reader query resources and current 11a/11b display data + +This package reproduces the current two reader visuals from the original Run 2 evidence. **11a** shows data processing throughput and throughput per consumed CPU core; **11b** shows query latency and effective aggregation throughput. Both use the same **Resource utilization during query execution** band. + +The active window is **2026-08-08 06:55:56–2026-08-09 19:40:58 UTC**, during continuous ingestion of **113,217,743,918 quotes**. The read service was one **16-vCPU / 64-GiB** node. All **958** active executions are retained: **74 drill-downs** and **884 interactive aggregates**. No new exclusions are applied. + +## Query-execution CPU and headroom + +CPU utilization uses summed `UserTimeMicroseconds + SystemTimeMicroseconds`, divided by summed execution time and **16 vCPUs**. Execution time supplies the query weights. The hourly drill-down and ten-minute aggregate scheduling gaps do not enter this denominator. CPU headroom is the complement of this share; it does not quantify additional concurrent queries. + +The resource curve has 442 five-minute row-progress positions joined to cumulative raw-table NewPart rows. At each timestamp it uses the same centered Gaussian display kernel as the charts. [Resource CSV](resource-display.csv) retains busy-core counts and percentages. Historical whole-service memory columns remain evidence and are not presented as query-memory utilization. + +## Per-query peak memory + +The extraction is [10-query-peak-memory.sql](evidence/queries/10-query-peak-memory.sql), with its [result CSV](evidence/10-query-peak-memory.csv). The `QueryFinish` memory field is the query peak. Each selected row joins uniquely to the existing query evidence using exact start time and normalized query hash; duration, rows and bytes must also match. [All 958 matched peaks](matched-query-memory.csv) preserve query name, family, iteration, raw row count and bytes. + +The band shows separate arithmetic means for **Drill-downs · peak memory** and **Interactive aggs · peak memory**, with equal query weights within each iteration and Gaussian weights between iterations. The 64-GiB label is provisioned RAM. These query peaks are separate from the service's in-memory cache footprint, and no memory-utilization or memory-headroom percentage is inferred from them. + +## Shared display kernel + +Every current chart line uses a centered Gaussian in actual UTC time, with **sigma one hour** and **radius three hours**. End windows renormalize the available observations. Rates smooth their numerator and denominator before dividing; latency starts from original runner durations with no prior median smoothing or decimation. [Display CSV](display-metrics.csv), [memory display CSV](query-memory-display.csv), and exact [11a](processing/chart-data.json)/[11b](latency/chart-data.json) payloads are included. [Provenance](source-provenance.json) and [source hashes](source-manifest.json) document the join and formulas. + +The unsmoothed byte/CPU rates and older latency display extraction remain unchanged in the parent directory. Use this package for the current blog display values, including the smoothed **3.25 GB/s** drill-down endpoint. Effective aggregation throughput is logical quotes represented by the A3/A4 answer, not physical raw scanning. + +## Reproduce offline + +Python 3.9+, standard library only, from the repository root: + +```sh +python3 full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/query-resources/derive.py +python3 full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/query-resources/derive.py --check +python3 full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/query-resources/checksums.py --check +``` + +The first regenerates the two JSON payloads, display/resource CSVs, memory matches and provenance. The second verifies byte-identical reproduction without modifying them; source hashes are checked first. Evidence is frozen beside the adapter so historical log retention does not prevent offline reproduction. Live queries are unnecessary. Credentials are excluded. + +The newer fixed-data Hot/Cold experiment for **11c** lives separately under [reader-thread-scaling in PR #46](https://github.com/ClickHouse/CostBench/pull/46). It uses another service configuration and version and must not be mixed into Run 2's ingestion-progress curves. diff --git a/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/query-resources/checksums.py b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/query-resources/checksums.py new file mode 100644 index 0000000..86ae726 --- /dev/null +++ b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/query-resources/checksums.py @@ -0,0 +1,14 @@ +#!/usr/bin/env python3 +"""Create or verify the experiment's file hashes; never include ignored caches.""" +import argparse, hashlib, pathlib +ROOT=pathlib.Path(__file__).resolve().parent +def digest(p):return hashlib.sha256(p.read_bytes()).hexdigest() +def main(): + parser=argparse.ArgumentParser();parser.add_argument('--check',action='store_true');args=parser.parse_args();target=ROOT/'FILES.sha256' + if args.check: + rows=[line.split(' ',1)for line in target.read_text().splitlines()] + for h,name in rows:assert digest(ROOT/name)==h,name + print('Verified',len(rows),'files.');return + files=sorted(p for p in ROOT.rglob('*')if p.is_file() and p.name!='FILES.sha256' and '__pycache__'not in p.parts and p.suffix!='.pyc') + target.write_text(''.join(digest(p)+' '+str(p.relative_to(ROOT))+'\n'for p in files));print('Hashed',len(files),'files.') +if __name__=='__main__':main() diff --git a/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/query-resources/config.json b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/query-resources/config.json new file mode 100644 index 0000000..9dd2f53 --- /dev/null +++ b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/query-resources/config.json @@ -0,0 +1,24 @@ +[ + { + "id": "11a", + "view": "processing", + "stem": "11a_read-service-metrics", + "title": "ClickHouse processes gigabytes per second on a single query node", + "metricTitles": { + "throughput": "Data processing throughput", + "efficiency": "Data throughput per CPU core" + }, + "contextCaption": "Where we measure: query compute" + }, + { + "id": "11b", + "view": "latency", + "stem": "11b_query-latency-throughput", + "title": "Fast answers over 113 billion quotes with CPU headroom", + "metricTitles": { + "latency": "Query latency", + "coverage": "Effective aggregation throughput" + }, + "contextCaption": "Where we measure: query compute" + } +] diff --git a/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/query-resources/derive.py b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/query-resources/derive.py new file mode 100644 index 0000000..122d22e --- /dev/null +++ b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/query-resources/derive.py @@ -0,0 +1,128 @@ +#!/usr/bin/env python3 +"""Reproduce the two reader visuals from pinned numeric evidence (stdlib only).""" +from pathlib import Path +from datetime import datetime,timezone +from collections import defaultdict +import csv,json,math,hashlib,argparse,tempfile +HERE=Path(__file__).resolve().parent +FULL=113217743918 +START=int(datetime(2026,8,8,6,55,56,tzinfo=timezone.utc).timestamp()) +END=int(datetime(2026,8,9,19,40,58,tzinfo=timezone.utc).timestamp()) +SIGMA=3600; RADIUS=10800 + +def epoch(s): + return datetime.fromisoformat(s.replace('Z','+00:00')).replace(tzinfo=timezone.utc).timestamp() +def read(name): + return list(csv.DictReader((HERE/'evidence'/name).open())) +def weight(t,u): + return math.exp(-.5*((t-u)/SIGMA)**2) if abs(t-u)<=RADIUS else 0 + +def derive(out): + for source in json.loads((HERE/'source-manifest.json').read_text()): + assert hashlib.sha256((HERE/source['path']).read_bytes()).hexdigest()==source['sha256'],source['path'] + configs=json.loads((HERE/'config.json').read_text()) + old=json.loads((HERE/'evidence/prior-chart-data.json').read_text()) + panels={p['id']:p for p in old['panels']} + query_rows=read('metrics-per-query.csv') + groups=defaultdict(list) + for q in query_rows:groups[(q['family'],int(q['iteration']))].append(q) + runners={} + for family,file in [('drill','drilldown_20260808T065602Z.jsonl'),('aggregate','dashboard_20260808T065559Z.jsonl')]: + for line in (HERE/'evidence'/file).read_text().splitlines(): + r=json.loads(line);runners[(family,r['iteration'])]=r + rates={} + for metric,file,num,den in [('throughput','data-processing-throughput.csv','total_read_bytes','total_elapsed_seconds'),('efficiency','data-throughput-per-cpu-core.csv','total_read_bytes','total_cpu_seconds'),('coverage','effective-aggregation-throughput.csv','raw_quotes_represented','total_elapsed_seconds')]: + rates[metric]=defaultdict(list) + for row in read(file): + family=row.get('family','aggregate');r=runners[(family,int(row['iteration']))] + rates[metric][family].append({'progress':int(row['rows_ingested'])/FULL,'time':epoch(r['iteration_started_at']),'num':float(row[num]),'den':float(row[den])}) + latency=defaultdict(list); active_queries=[]; query_memory=defaultdict(list) + memory_lookup={(r['started_at_utc'],r['query_hash']):r for r in read('10-query-peak-memory.csv')} + hashes={'A1':'4268017077458496684','A2':'13116456435110875434','A3':'16441976537628221706','A4':'16076059573740575684','D1':'14900422428945064879','D2':'4120463799277501782'} + matched_memory=[] + for (family,iteration),queries in groups.items(): + r=runners[(family,iteration)];p=int(r['raw_rows'])/FULL;assert 0=toDateTime('2026-08-08 06:55:56','UTC') AND event_time=toDateTime('2026-08-08 06:55:56','UTC') AND event_time=toDateTime('2026-08-08 06:55:56','UTC') AND event_time=toDateTime('2026-08-09 19:40:00','UTC') AND event_time0 +GROUP BY metric ORDER BY metric LIMIT 100 SETTINGS max_threads=2,max_execution_time=20,timeout_before_checking_execution_speed=0,max_rows_to_read=100000,skip_unavailable_shards=0 FORMAT CSVWithNames diff --git a/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/query-resources/evidence/queries/07-memory-metric-descriptions.sql b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/query-resources/evidence/queries/07-memory-metric-descriptions.sql new file mode 100644 index 0000000..999f689 --- /dev/null +++ b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/query-resources/evidence/queries/07-memory-metric-descriptions.sql @@ -0,0 +1,2 @@ +SELECT metric,value,description FROM system.asynchronous_metrics WHERE positionCaseInsensitive(metric,'memory')>0 +ORDER BY metric LIMIT 100 SETTINGS max_threads=2,max_execution_time=15,timeout_before_checking_execution_speed=0,max_rows_to_read=100000 FORMAT CSVWithNames diff --git a/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/query-resources/evidence/queries/08-memory-cache-check.sql b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/query-resources/evidence/queries/08-memory-cache-check.sql new file mode 100644 index 0000000..7ffb5ce --- /dev/null +++ b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/query-resources/evidence/queries/08-memory-cache-check.sql @@ -0,0 +1,4 @@ +SELECT metric,count() AS samples,min(value) AS minimum,max(value) AS maximum,avg(value) AS average FROM clusterAllReplicas(default,merge('system','^asynchronous_metric_log')) +WHERE event_date='2026-08-09' AND event_time>=toDateTime('2026-08-09 19:35:00','UTC') AND event_time0 OR name IN ('query_start_time_microseconds','event_time_microseconds','normalized_query_hash','databases','type','is_initial_query','query_kind','ProfileEvents')) +ORDER BY name LIMIT 50 SETTINGS max_threads=2,max_execution_time=15,timeout_before_checking_execution_speed=0,max_rows_to_read=100000 FORMAT CSVWithNames diff --git a/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/query-resources/evidence/queries/10-query-peak-memory.sql b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/query-resources/evidence/queries/10-query-peak-memory.sql new file mode 100644 index 0000000..1cbf22b --- /dev/null +++ b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/query-resources/evidence/queries/10-query-peak-memory.sql @@ -0,0 +1,7 @@ +SELECT toString(query_start_time_microseconds) AS started_at_utc,toString(normalized_query_hash) AS query_hash,memory_usage AS peak_memory_bytes,query_duration_ms,read_rows,read_bytes +FROM clusterAllReplicas(default,merge('system','^query_log')) +WHERE event_date BETWEEN '2026-08-08' AND '2026-08-09' +AND query_start_time>=toDateTime('2026-08-08 06:54:00','UTC') AND query_start_time Date: Mon, 12 Oct 2026 13:33:44 +0100 Subject: [PATCH 3/3] Align reader documentation with Part 6 visual numbering --- .../utilization/reader/query-metrics/README.md | 6 ++++-- .../reader/query-metrics/query-resources/FILES.sha256 | 2 +- .../reader/query-metrics/query-resources/README.md | 10 ++++++---- 3 files changed, 11 insertions(+), 7 deletions(-) diff --git a/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/README.md b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/README.md index 7ab5a00..17ece69 100644 --- a/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/README.md +++ b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/README.md @@ -1,10 +1,12 @@ # Reader query metrics -Original numeric extraction behind Blog 6 reader visuals **11a and 11b**. The measurements use the August 8–9, 2026 ClickHouse run while the raw dataset grows to **113,217,743,918 quotes**. The reader service had one node with 16 CPUs and 64 GiB; the benchmark database was `quotes_async_t4` (the historical results directory remains `results_t2`). +Visual numbers follow the current Part 6 article. Existing filenames retain their earlier identifiers so reproduction commands and links stay compatible. + +Original numeric extraction behind Blog 6 reader visuals **16 and 17**. The measurements use the August 8–9, 2026 ClickHouse run while the raw dataset grows to **113,217,743,918 quotes**. The reader service had one node with 16 CPUs and 64 GiB; the benchmark database was `quotes_async_t4` (the historical results directory remains `results_t2`). ## Current blog values and resource band -Use [query-resources/](query-resources/README.md) for the current two-panel layouts and their **Resource utilization during query execution** bands. It includes extraction SQL/results, all 958 matched per-query memory peaks, CPU during execution with headroom, shared Gaussian display smoothing, exact 11a/11b payloads and a dependency-free reproducer. These calculations exclude the idle gaps in the query schedule and preserve the original 16-vCPU / 64-GiB setup. +Use [query-resources/](query-resources/README.md) for the current two-panel layouts and their **Resource utilization during query execution** bands. It includes extraction SQL/results, all 958 matched per-query memory peaks, CPU during execution with headroom, shared Gaussian display smoothing, exact 16/17 payloads and a dependency-free reproducer. These calculations exclude the idle gaps in the query schedule and preserve the original 16-vCPU / 64-GiB setup. The tables and adapters below retain the original four-panel extraction as frozen evidence. Their byte-rate and CPU-rate CSVs are inputs to the current display adapter; the older median-smoothed latency payload is preserved for traceability, rather than used as the current blog curve. diff --git a/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/query-resources/FILES.sha256 b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/query-resources/FILES.sha256 index 92de3a7..0159c75 100644 --- a/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/query-resources/FILES.sha256 +++ b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/query-resources/FILES.sha256 @@ -1,5 +1,5 @@ 862263fa1f46c20f0d1e4dac5ffcc75abd55c08211b2c3864c5f8764b9d87793 .gitignore -9fba9a0689eb3c493ef6438341cf9ca49555a4ef74f1ec1341f122ba01e0644a README.md +a315b264dccf41e050112d0198923d44b4af700295c8527ef284ad2d15a77ea1 README.md 89b6267012fbc2e9550ddd5815f5c26902328208d520c0fc9c853d003c23f159 checksums.py 18aa685c0f59669414df754d750e7c35bafcc2bb1b21e17a21bc0776eabda0c5 config.json 60810f26906011e547646297b811033999026e0b93c6519f7bc4ef56f1fac163 derive.py diff --git a/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/query-resources/README.md b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/query-resources/README.md index 9ba30cf..6be6a6d 100644 --- a/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/query-resources/README.md +++ b/full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader/query-metrics/query-resources/README.md @@ -1,6 +1,8 @@ -# Reader query resources and current 11a/11b display data +# Reader query resources and current 16/17 display data -This package reproduces the current two reader visuals from the original Run 2 evidence. **11a** shows data processing throughput and throughput per consumed CPU core; **11b** shows query latency and effective aggregation throughput. Both use the same **Resource utilization during query execution** band. +Visual numbers follow the current Part 6 article. Existing filenames retain their earlier identifiers so reproduction commands and links stay compatible. + +This package reproduces the current two reader visuals from the original Run 2 evidence. **16** shows data processing throughput and throughput per consumed CPU core; **17** shows query latency and effective aggregation throughput. Both use the same **Resource utilization during query execution** band. The active window is **2026-08-08 06:55:56–2026-08-09 19:40:58 UTC**, during continuous ingestion of **113,217,743,918 quotes**. The read service was one **16-vCPU / 64-GiB** node. All **958** active executions are retained: **74 drill-downs** and **884 interactive aggregates**. No new exclusions are applied. @@ -18,7 +20,7 @@ The band shows separate arithmetic means for **Drill-downs · peak memory** and ## Shared display kernel -Every current chart line uses a centered Gaussian in actual UTC time, with **sigma one hour** and **radius three hours**. End windows renormalize the available observations. Rates smooth their numerator and denominator before dividing; latency starts from original runner durations with no prior median smoothing or decimation. [Display CSV](display-metrics.csv), [memory display CSV](query-memory-display.csv), and exact [11a](processing/chart-data.json)/[11b](latency/chart-data.json) payloads are included. [Provenance](source-provenance.json) and [source hashes](source-manifest.json) document the join and formulas. +Every current chart line uses a centered Gaussian in actual UTC time, with **sigma one hour** and **radius three hours**. End windows renormalize the available observations. Rates smooth their numerator and denominator before dividing; latency starts from original runner durations with no prior median smoothing or decimation. [Display CSV](display-metrics.csv), [memory display CSV](query-memory-display.csv), and exact [16](processing/chart-data.json)/[17](latency/chart-data.json) payloads are included. [Provenance](source-provenance.json) and [source hashes](source-manifest.json) document the join and formulas. The unsmoothed byte/CPU rates and older latency display extraction remain unchanged in the parent directory. Use this package for the current blog display values, including the smoothed **3.25 GB/s** drill-down endpoint. Effective aggregation throughput is logical quotes represented by the A3/A4 answer, not physical raw scanning. @@ -34,4 +36,4 @@ python3 full-path-realtime/quotes/clickhouse-cloud/results_t2/utilization/reader The first regenerates the two JSON payloads, display/resource CSVs, memory matches and provenance. The second verifies byte-identical reproduction without modifying them; source hashes are checked first. Evidence is frozen beside the adapter so historical log retention does not prevent offline reproduction. Live queries are unnecessary. Credentials are excluded. -The newer fixed-data Hot/Cold experiment for **11c** lives separately under [reader-thread-scaling in PR #46](https://github.com/ClickHouse/CostBench/pull/46). It uses another service configuration and version and must not be mixed into Run 2's ingestion-progress curves. +The newer fixed-data Hot/Cold experiment for **18** lives separately under [reader-thread-scaling in PR #46](https://github.com/ClickHouse/CostBench/pull/46). It uses another service configuration and version and must not be mixed into Run 2's ingestion-progress curves.