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Add Metabase performance graph SQL sources
Version-control the SQL queries backing the Metabase performance dashboards, with a README documenting the data model, the {{product_release}} / {{scenario_name}} template variables, and what each query produces. Each .sql file also carries a short header comment. Covers filter queries (product_releases, scenario_names), CPU/memory/runtime history graphs (backend + UI variants), the per-release drilldowns with fixed-release baselines, and the per-scenario snapshots. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Change-Id: I5365bc9bd8e4053bd9a24e734d6045c96b3b580e
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‎tests/performance/database/graphs/README.md‎

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# Metabase performance graph queries
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The `.sql` files in this folder are the **source queries for the Metabase
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performance dashboards**. Each query is pasted into a Metabase question that
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renders a graph (or, for a couple of them, populates a dashboard filter). The
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files are kept here so the queries are version-controlled and reviewable
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alongside the rest of the performance test suite; Metabase itself remains the
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place where they are executed and visualised.
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## Data model
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The queries read from the performance results database (see the parent
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[`README.md`](../README.md) for how it is created):
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| Table | Purpose |
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| ------------ | --------------------------------------------------------------------------------------------------------------------------- |
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| `jobs` | One row per CI performance run. `job_name` is prefixed with the release (`3.0.0-…`); `start_timestamp` records when it ran. |
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| `tests` | Individual tests belonging to a job. |
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| `scenarios` | The performance scenario a test belongs to (the `test_*` function name). |
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| `metrics` | Sampled system-resource values per test, e.g. `cpu_info.cpu_percent`, `memory_info.virtual_memory_percent`. |
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| `benchmarks` | Timing measurements per test; `metric_name = 'mean'` is the mean runtime in seconds. |
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## Metabase template variables
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Some queries use Metabase's `{{ … }}` template syntax:
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- `{{product_release}}` — text variable holding a release prefix (e.g. `3.0.0`),
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matched against `job_name` with `LIKE CONCAT({{product_release}}, '-%')`.
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- `{{scenario_name}}` — a field filter that Metabase expands into a boolean
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condition selecting one scenario (used by the drilldown queries).
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## The queries
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**Filter queries** (populate dashboard dropdowns):
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- `product_releases.sql` — distinct release prefixes, newest first → `{{product_release}}`.
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- `scenario_names.sql` — the selectable performance scenarios → `{{scenario_name}}`.
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**History graphs** — trend over the last 6 months for the selected release,
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split into backend and UI (`test_performance_ui_*`) variants:
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- `cpu_history.sql` / `cpu_history_ui.sql` — average CPU usage.
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- `memory_history.sql` / `memory_history_ui.sql` — average memory usage.
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- `runtime_history.sql` / `runtime_history_ui.sql` — average test runtime.
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**Drilldown graphs** — a single release and scenario, overlaid with fixed
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reference baselines for releases `3.0.0` / `2.5.0` / `2.4.0` / `2.3.0`:
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- `cpu_history_drilldown.sql`, `memory_history_drilldown.sql`,
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`runtime_history_drilldown.sql`.
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**Per-scenario snapshots** — the 3 most recent jobs of the selected release,
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broken down by scenario:
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- `scenario_cpu_usage.sql`, `scenario_memory_usage.sql`,
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`scenario_mean_runtime.sql`.
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Each file also carries a short header comment describing what it produces.

‎tests/performance/database/graphs/cpu_history.sql‎

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-- Backend CPU history graph: average CPU usage per scenario across all jobs of
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-- the selected {{product_release}} in the last 6 months. Backend scenarios only
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-- (test_*, excluding UI). Divided by 100 for Metabase's percent
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-- formatting.
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SELECT
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j.job_name AS "Job Name",
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s.scenario_name AS "Scenario Name",
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AVG(m.measured_value) / 100 AS "Average CPU usage (%)"
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FROM
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jobs j
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JOIN tests t ON j.job_id = t.job_id
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JOIN metrics m ON t.test_id = m.test_id
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JOIN scenarios s ON t.scenario_id = s.scenario_id
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WHERE
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j.job_name LIKE CONCAT({{product_release}}, '-%')
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AND j.start_timestamp >= now() - INTERVAL '6 months'
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AND m.metric_name = 'cpu_info.cpu_percent'
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AND s.scenario_name LIKE 'test_%'
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AND s.scenario_name NOT LIKE 'test_performance_ui_%'
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GROUP BY
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j.job_name,
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s.scenario_name
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ORDER BY
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j.job_name ASC;

‎tests/performance/database/graphs/cpu_history_drilldown.sql‎

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-- CPU drilldown graph: for the selected {{product_release}} and single
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-- {{scenario_name}}, plots average CPU usage per job and overlays fixed reference
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-- baselines for releases 3.0.0/2.5.0/2.4.0/2.3.0 as extra columns. Each baseline
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-- is the average of that release's 100 most recent measurements, skipping the
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-- single most recent measurement (OFFSET 1) to avoid an in-progress or outlier build. The
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-- per-job value and all baselines are divided by 100 for Metabase's percent
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-- formatting, consistent with cpu_history.sql.
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WITH
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baseline300 AS (
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SELECT
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AVG(measured_value) AS baseline_cpu_usage
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FROM
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(
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SELECT
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m.measured_value
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FROM
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jobs j
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JOIN tests t ON j.job_id = t.job_id
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JOIN metrics m ON t.test_id = m.test_id
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JOIN scenarios s ON t.scenario_id = s.scenario_id
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WHERE
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j.job_name LIKE '3.0.0-%'
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AND m.metric_name = 'cpu_info.cpu_percent'
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AND {{scenario_name}}
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ORDER BY
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j.start_timestamp DESC
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OFFSET
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1
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LIMIT
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100
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)
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),
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baseline250 AS (
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SELECT
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AVG(measured_value) AS baseline_cpu_usage
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FROM
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(
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SELECT
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m.measured_value
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FROM
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jobs j
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JOIN tests t ON j.job_id = t.job_id
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JOIN metrics m ON t.test_id = m.test_id
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JOIN scenarios s ON t.scenario_id = s.scenario_id
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WHERE
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j.job_name LIKE '2.5.0-%'
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AND m.metric_name = 'cpu_info.cpu_percent'
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AND {{scenario_name}}
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ORDER BY
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j.start_timestamp DESC
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OFFSET
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1
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LIMIT
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100
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)
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),
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baseline240 AS (
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SELECT
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AVG(measured_value) AS baseline_cpu_usage
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FROM
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(
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SELECT
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m.measured_value
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FROM
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jobs j
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JOIN tests t ON j.job_id = t.job_id
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JOIN metrics m ON t.test_id = m.test_id
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JOIN scenarios s ON t.scenario_id = s.scenario_id
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WHERE
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j.job_name LIKE '2.4.0-%'
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AND m.metric_name = 'cpu_info.cpu_percent'
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AND {{scenario_name}}
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ORDER BY
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j.start_timestamp DESC
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OFFSET
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1
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LIMIT
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100
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)
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),
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baseline230 AS (
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SELECT
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AVG(measured_value) AS baseline_cpu_usage
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FROM
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(
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SELECT
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m.measured_value
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FROM
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jobs j
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JOIN tests t ON j.job_id = t.job_id
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JOIN metrics m ON t.test_id = m.test_id
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JOIN scenarios s ON t.scenario_id = s.scenario_id
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WHERE
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j.job_name LIKE '2.3.0-%'
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AND m.metric_name = 'cpu_info.cpu_percent'
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AND {{scenario_name}}
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ORDER BY
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j.start_timestamp DESC
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OFFSET
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1
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LIMIT
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100
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)
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)
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SELECT
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j.job_name AS "Job Name",
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s.scenario_name AS "Scenario Name",
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AVG(m.measured_value) / 100 AS "average CPU usage (%)",
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b300.baseline_cpu_usage / 100 AS "3.0.0 baseline CPU usage (%)",
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b250.baseline_cpu_usage / 100 AS "2.5.0 baseline CPU usage (%)",
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b240.baseline_cpu_usage / 100 AS "2.4.0 baseline CPU usage (%)",
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b230.baseline_cpu_usage / 100 AS "2.3.0 baseline CPU usage (%)"
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FROM
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jobs j
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JOIN tests t ON j.job_id = t.job_id
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JOIN metrics m ON t.test_id = m.test_id
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JOIN scenarios s ON t.scenario_id = s.scenario_id
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CROSS JOIN baseline300 b300
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CROSS JOIN baseline250 b250
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CROSS JOIN baseline240 b240
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CROSS JOIN baseline230 b230
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WHERE
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j.job_name LIKE CONCAT({{product_release}}, '-%')
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AND j.start_timestamp >= now() - INTERVAL '6 months'
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AND m.metric_name = 'cpu_info.cpu_percent'
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AND {{scenario_name}}
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GROUP BY
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j.job_name,
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s.scenario_name,
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b300.baseline_cpu_usage,
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b250.baseline_cpu_usage,
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b240.baseline_cpu_usage,
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b230.baseline_cpu_usage
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ORDER BY
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j.job_name ASC;

‎tests/performance/database/graphs/cpu_history_ui.sql‎

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-- UI CPU history graph: like cpu_history.sql but for the GUI/UI scenarios
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-- (test_performance_ui_*). Same 6-month window and {{product_release}} filter.
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SELECT
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j.job_name AS "Job Name",
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s.scenario_name AS "Scenario Name",
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AVG(m.measured_value) / 100 AS "Average CPU usage (%)"
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FROM
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jobs j
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JOIN tests t ON j.job_id = t.job_id
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JOIN metrics m ON t.test_id = m.test_id
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JOIN scenarios s ON t.scenario_id = s.scenario_id
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WHERE
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j.job_name LIKE CONCAT({{product_release}}, '-%')
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AND j.start_timestamp >= now() - INTERVAL '6 months'
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AND m.metric_name = 'cpu_info.cpu_percent'
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AND s.scenario_name LIKE 'test_performance_ui_%'
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GROUP BY
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j.job_name,
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s.scenario_name
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ORDER BY
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j.job_name ASC;

‎tests/performance/database/graphs/memory_history.sql‎

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-- Backend memory history graph: average virtual-memory usage per scenario across
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-- all jobs of the selected {{product_release}} in the last 6 months. Backend
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-- scenarios only. Divided by 100 for Metabase's percent formatting.
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SELECT
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j.job_name AS "Job Name",
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s.scenario_name AS "Scenario Name",
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AVG(m.measured_value) / 100 AS "Average memory usage (%)"
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FROM
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jobs j
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JOIN tests t ON j.job_id = t.job_id
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JOIN metrics m ON t.test_id = m.test_id
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JOIN scenarios s ON t.scenario_id = s.scenario_id
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WHERE
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j.job_name LIKE CONCAT({{product_release}}, '-%')
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AND j.start_timestamp >= now() - INTERVAL '6 months'
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AND m.metric_name = 'memory_info.virtual_memory_percent'
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AND s.scenario_name LIKE 'test_%'
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AND s.scenario_name NOT LIKE 'test_performance_ui_%'
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GROUP BY
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j.job_name,
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s.scenario_name
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ORDER BY
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j.job_name ASC;

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