Altinity · BorisTyshkevich · Jul 22, 2026 · Jul 22, 2026
@@ -9,6 +9,14 @@ auto-generated per-PR notes; this file is the curated, human-readable history.
 
 ## [Unreleased]
 
+### Changed
+- Consolidated the non-Iceberg examples into three responsive flagship
+  dashboards: On-time flights, Shop analytics, and ClickHouse Operations.
+  Each uses an authored `grafana-grid@1` layout with a complete `flow@1`
+  fallback, shared filters, and focused visible tiles; useful secondary
+  analyses remain untiled Library entries. Removed the superseded KPI, logs,
+  query-log, System Explorer, and earlier Grafana-port fixtures and generator.
+
 ### Added
 - **Cross-tab workspace consistency: refresh before write and stale-tab
   invalidation** (#343). Workbench and editable-Dashboard tabs editing the same

@@ -23,15 +23,20 @@ held at **100% test coverage**.
 
 See the [**feature tour, deployment guide and screenshots**](https://docs.altinity.com/altinity-sql-browser/)
 on the project site. Try it live on the Antalya demo cluster: **https://antalya.demo.altinity.cloud/sql**.
-The [**ontime chart demo**](docs/ONTIME-CHART-DEMO.md) is a ready-made library of 10
-queries (load [`examples/ontime-charts.json`](examples/ontime-charts.json) via
-**File ▾ → Import queries**) that walks through every chart type and feature against the public
-`ontime` flight dataset. The [**system explorer demo**](docs/SYSTEM-EXPLORER-DEMO.md)
-is a 14-query library (load [`examples/system-explorer-charts.json`](examples/system-explorer-charts.json)
-via **File ▾ → Import queries**) that introspects ClickHouse's own `system` database —
-running queries, merges/replication health, and historical query/part/error
-activity — with a shared From/To filter driving every time-ranged Dashboard tile
-at once.
+Three flagship bundles cover the main workflows without a pile of one-feature
+fixtures:
+
+- [**On-time flights**](docs/ONTIME-CHART-DEMO.md) — seven analytical tiles,
+  a KPI band, a shared 2023 date range, and carrier/airport multiselects over
+  the public `ontime` dataset.
+- [**Shop analytics**](docs/SHOP-ANALYTICS-DEMO.md) — seven business tiles over
+  the schema, sample data, materialized views, and dictionary created by
+  [`examples/shop-demo.sql`](examples/shop-demo.sql).
+- [**ClickHouse Operations**](docs/CLICKHOUSE-OPERATIONS-DEMO.md) — sixteen
+  operator-first tiles for live health, resources, background work, and
+  investigation, with the remaining operational queries kept in the Library.
+
+Load the corresponding portable bundle from `examples/` with **File ▾ → Open…**.
 The [**Iceberg catalog explorer**](docs/ICEBERG-CATALOG-EXPLORER-DEMO.md) is a
 distributable installer + two dashboards for Iceberg data-lake catalogs:
 [`examples/iceberg-install.json`](examples/iceberg-install.json) generates the
@@ -92,9 +97,9 @@ ordinary `.kpi-panel` grid, while a **favorited, explicitly-KPI-typed** Dashboar
 query instead joins a full-width **KPI band** — a flat, wrapping card stream
 with no per-favorite name, description, or statistics footer, spanning every
 flow Dashboard layout (Report/2/3 columns). Consecutive explicit KPI
-favorites merge into one shared band. The complete
-[`kpi-panel.json`](examples/kpi-panel.json) Library example can be opened from
-**File ▾ → Import queries** to see both.
+favorites merge into one shared band. The On-time, Shop, and Operations
+flagship dashboards all include a production
+KPI band alongside charts, tables, and logs.
 When constructing a named tuple from expressions, either enable alias-derived
 member names for the query:
 
@@ -492,14 +497,10 @@ nested option values, limits each helper to 1,000 options, and falls back to the
 ordinary parameter field when a source, consumer type, or provider conflicts.
 Filter sources run and reconcile saved values before any Panel query starts.
 
-The complete [`query-log-explorer.json`](examples/query-log-explorer.json)
-Library example (load via **File ▾ → Import queries**) demonstrates every filter
-variant against `system.query_log` on any cluster: three Filter sources, one
-per option shape (`Array(Tuple(value, label))`, `Map(String, String)`, plain
-`Array(T)`), alongside plain auto-detected numeric/text fields — a KPI panel,
-four analytical Panels adapted from the Altinity KB's ["Handy queries for
-system.query_log"](https://kb.altinity.com/altinity-kb-useful-queries/query_log/),
-a Logs panel, and a Text panel explaining the demo.
+The flagship bundles demonstrate the same contracts in context: readable
+`Array(Tuple(value, label))` airport options in On-time, targeted country and
+category filters in Shop, and inferred `Array(T)` multiselects for operational
+query-log dimensions in ClickHouse Operations.
 
 ```sql
 SELECT

@@ -0,0 +1,27 @@
+# ClickHouse Operations dashboard
+
+[`examples/clickhouse-operations.json`](../examples/clickhouse-operations.json)
+is an operator-first dashboard imported and curated from the ClickHouse
+Operations bundle. Open it with **File ▾ → Open…** against a cluster where the
+signed-in user can inspect the relevant `system` tables.
+
+Its sixteen visible tiles follow an investigation path:
+
+- overview: live KPIs, running queries, query rate, active connections;
+- resources: CPU, memory, I/O utilization, network traffic;
+- background work: merges, mutations, replication checks;
+- investigation: errors, largest tables, query-hash metric, query details, and
+  recent server logs.
+
+The active time range defaults to `-1h` through `now`. `user`, `query_kind`,
+`exception_code`, and `query_hash` are inferred searchable multiselects; their
+consumers consistently use `Array(T)` parameters with `has(...)`. `metric` and
+`is_initial_query` remain single-select controls, while time and log search are
+scalar. The other downloaded operational queries remain untiled in the Library.
+
+Typical grants include `SELECT` on `system.metric_log`,
+`system.asynchronous_metric_log`, `system.query_log`, `system.part_log`,
+`system.text_log`, `system.parts`, `system.merges`, `system.mutations`, and
+replication-related system tables. Exact availability depends on server
+version and deployment policy; missing grants fail individual tiles without
+hiding the rest of the dashboard.
@@ -1,65 +1,27 @@
-# Chart demo — the `ontime` flight dataset
+# On-time flights dashboard
 
-A ready-made **Library** of 10 analytical queries that show off every chart type and
-feature in the Altinity® SQL Browser, running against the public US flight-history
-dataset (`ontime`, ~230M rows, 1987–2025) on the Antalya demo cluster.
+[`examples/ontime-charts.json`](../examples/ontime-charts.json) is the flagship
+analytical dashboard for the public `ontime` flight dataset. Open it on the
+[Antalya demo](https://antalya.demo.altinity.cloud/sql) with **File ▾ → Open…**.
 
-- **Live demo:** **https://antalya.demo.altinity.cloud/sql**
-- **The library file:** [`examples/ontime-charts.json`](../examples/ontime-charts.json)
-  ([raw download](https://raw.githubusercontent.com/Altinity/altinity-sql-browser/main/examples/ontime-charts.json))
-- **Reproduce it:** [`examples/mjs/build-ontime-charts.mjs`](../examples/mjs/build-ontime-charts.mjs)
-  regenerates the JSON (it derives each chart's schema key live with
-  `clickhouse-client --connection antalya`).
+The authored grid contains seven visible tiles: Flight KPIs, Daily flights,
+On-time rate, Busiest origins, Monthly carrier volume, Delay causes by carrier,
+and Cancellation reasons. Additional chart analyses remain available as
+untiled Library entries.
 
-## Load it (≈30 seconds)
+The active time range defaults to `2023-01-01` through `2023-12-31`. Carrier
+and Origin airport start inactive and become searchable multiselects because
+every targeted query declares `Array(String)` and uses `has(...)`. Airport
+codes are the bound values; readable airport names are the labels.
 
-1. Open **https://antalya.demo.altinity.cloud/sql** and sign in (**Continue with Google**,
-   or use the credentials box).
-2. Download [`ontime-charts.json`](https://raw.githubusercontent.com/Altinity/altinity-sql-browser/main/examples/ontime-charts.json)
-   (right-click → Save link as…).
-3. In the header, click **File ▾ → Open…** and pick the file. The library is renamed
-   **ontime-charts** and fills with 10 saved queries (confirm the replace if you already
-   had queries saved).
-4. Click any query in the **Queries** panel — it runs and opens straight into its chart.
-   Switch **Table / JSON / Chart** at the top of the results, or change the **Type / X / Y /
-   Series** dropdowns to re-encode any chart live.
+The dashboard reads `ontime.fact_ontime` and joins
+`ontime.dim_airports` for origin names. To refresh panel schema keys against
+the configured connection, run:
 
-## What each query demonstrates
+```bash
+node examples/mjs/build-ontime-charts.mjs
+```
 
-| # | Query | Chart | Feature |
-|---|-------|-------|---------|
-| 1 | Busiest origin airports — 2023 | Bar (horizontal) | categorical axis; joined to `dim_airports` for readable names; hover any bar (long or short) for its exact value |
-| 2 | Flights by month — 2023 | Column | numeric `month` auto-detected as an ordinal axis; K/M-humanised value ticks |
-| 3 | Daily flights — 2023 | Line | `Date` axis auto-detected as a time series (~365 points) |
-| 4 | Daily on-time rate — 2023 | Area | filled time series (a percentage measure) |
-| 5 | Cancellation reasons — 2023 | Pie | share of a small category set, with a legend |
-| 6 | Monthly flights by carrier — 2023 | Grouped bars | a **Series** column (carrier) splits each month into per-carrier bars |
-| 7 | Average delay breakdown by carrier — 2023 | Multi-measure columns | four measures plotted together (“All measures”) |
-| 8 | Daily flights since 2022 | Line | result exceeds the chart cap → a **“first 500 of 1.5K rows”** note (the table keeps them all) |
-| 9 | Flights by day of week — 2023 | Column | ordinal `dayofweek` axis |
-| 10 | Worst average departure delay by airport — 2023 | Bar (horizontal) | a non-count measure (avg minutes), joined for names |
-
-Each saved query stores its panel configuration in the complete query Spec, so it reopens exactly as designed. (Charts
-plot the first 500 rows; the full result is always available in the Table view.)
-
-## Direct links
-
-Every query is also reachable as a single shareable link — open one and the SQL **and** its
-chart configuration are pre-loaded; press **Run**, then the **Chart** tab. (Inside the app,
-the **Share** button copies the same kind of link for whatever you're looking at.)
-
-- **Bar** — [Busiest origin airports — 2023](https://antalya.demo.altinity.cloud/sql#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)
-- **Column** — [Flights by month — 2023](https://antalya.demo.altinity.cloud/sql#eyJfX2FzYiI6MSwic3FsIjoiU0VMRUNUIE1vbnRoIEFTIG1vbnRoLCBjb3VudCgpIEFTIGZsaWdodHNcbkZST00gb250aW1lLmZhY3Rfb250aW1lXG5XSEVSRSBZZWFyID0gMjAyM1xuR1JPVVAgQlkgbW9udGhcbk9SREVSIEJZIG1vbnRoIiwiY2hhcnQiOnsiY2ZnIjp7InR5cGUiOiJiYXIiLCJ4IjowLCJ5IjpbMV0sInNlcmllcyI6bnVsbH0sImtleSI6Im1vbnRoOlVJbnQ4fGZsaWdodHM6VUludDY0In19)
-- **Line** — [Daily flights — 2023](https://antalya.demo.altinity.cloud/sql#eyJfX2FzYiI6MSwic3FsIjoiU0VMRUNUIEZsaWdodERhdGUgQVMgZGF0ZSwgY291bnQoKSBBUyBmbGlnaHRzXG5GUk9NIG9udGltZS5mYWN0X29udGltZVxuV0hFUkUgWWVhciA9IDIwMjNcbkdST1VQIEJZIGRhdGVcbk9SREVSIEJZIGRhdGUiLCJjaGFydCI6eyJjZmciOnsidHlwZSI6ImxpbmUiLCJ4IjowLCJ5IjpbMV0sInNlcmllcyI6bnVsbH0sImtleSI6ImRhdGU6RGF0ZXxmbGlnaHRzOlVJbnQ2NCJ9fQ==)
-- **Area** — [Daily on-time rate — 2023](https://antalya.demo.altinity.cloud/sql#eyJfX2FzYiI6MSwic3FsIjoiU0VMRUNUXG4gICAgRmxpZ2h0RGF0ZSBBUyBkYXRlLFxuICAgIHJvdW5kKDEwMCAqIGNvdW50SWYoQXJyRGVsMTUgPSAwKSAvIGNvdW50KCksIDEpIEFTIG9uX3RpbWVfcGN0XG5GUk9NIG9udGltZS5mYWN0X29udGltZVxuV0hFUkUgWWVhciA9IDIwMjNcbkdST1VQIEJZIGRhdGVcbk9SREVSIEJZIGRhdGUiLCJjaGFydCI6eyJjZmciOnsidHlwZSI6ImFyZWEiLCJ4IjowLCJ5IjpbMV0sInNlcmllcyI6bnVsbH0sImtleSI6ImRhdGU6RGF0ZXxvbl90aW1lX3BjdDpGbG9hdDY0In19)
-- **Pie** — [Cancellation reasons — 2023](https://antalya.demo.altinity.cloud/sql#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)
-- **Grouped columns** — [Monthly flights by carrier — 2023](https://antalya.demo.altinity.cloud/sql#eyJfX2FzYiI6MSwic3FsIjoiU0VMRUNUXG4gICAgTW9udGggQVMgbW9udGgsXG4gICAgQ2FycmllciBBUyBjYXJyaWVyLFxuICAgIGNvdW50KCkgQVMgZmxpZ2h0c1xuRlJPTSBvbnRpbWUuZmFjdF9vbnRpbWVcbldIRVJFIFllYXIgPSAyMDIzIEFORCBDYXJyaWVyIElOICgnV04nLCAnQUEnLCAnREwnLCAnVUEnKVxuR1JPVVAgQlkgbW9udGgsIGNhcnJpZXJcbk9SREVSIEJZIG1vbnRoLCBjYXJyaWVyIiwiY2hhcnQiOnsiY2ZnIjp7InR5cGUiOiJiYXIiLCJ4IjowLCJ5IjpbMl0sInNlcmllcyI6MX0sImtleSI6Im1vbnRoOlVJbnQ4fGNhcnJpZXI6TG93Q2FyZGluYWxpdHkoU3RyaW5nKXxmbGlnaHRzOlVJbnQ2NCJ9fQ==)
-- **Multi-measure columns** — [Average delay breakdown by carrier — 2023](https://antalya.demo.altinity.cloud/sql#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)
-- **Line (capped)** — [Daily flights since 2022](https://antalya.demo.altinity.cloud/sql#eyJfX2FzYiI6MSwic3FsIjoiU0VMRUNUIEZsaWdodERhdGUgQVMgZGF0ZSwgY291bnQoKSBBUyBmbGlnaHRzXG5GUk9NIG9udGltZS5mYWN0X29udGltZVxuV0hFUkUgRmxpZ2h0RGF0ZSA+PSAnMjAyMi0wMS0wMSdcbkdST1VQIEJZIGRhdGVcbk9SREVSIEJZIGRhdGUiLCJjaGFydCI6eyJjZmciOnsidHlwZSI6ImxpbmUiLCJ4IjowLCJ5IjpbMV0sInNlcmllcyI6bnVsbH0sImtleSI6ImRhdGU6RGF0ZXxmbGlnaHRzOlVJbnQ2NCJ9fQ==)
-- **Column** — [Flights by day of week — 2023](https://antalya.demo.altinity.cloud/sql#eyJfX2FzYiI6MSwic3FsIjoiU0VMRUNUIERheU9mV2VlayBBUyBkYXlvZndlZWssIGNvdW50KCkgQVMgZmxpZ2h0c1xuRlJPTSBvbnRpbWUuZmFjdF9vbnRpbWVcbldIRVJFIFllYXIgPSAyMDIzXG5HUk9VUCBCWSBkYXlvZndlZWtcbk9SREVSIEJZIGRheW9md2VlayIsImNoYXJ0Ijp7ImNmZyI6eyJ0eXBlIjoiYmFyIiwieCI6MCwieSI6WzFdLCJzZXJpZXMiOm51bGx9LCJrZXkiOiJkYXlvZndlZWs6VUludDh8ZmxpZ2h0czpVSW50NjQifX0=)
-- **Bar** — [Worst average departure delay by airport — 2023](https://antalya.demo.altinity.cloud/sql#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)
-
-## Tables used
-
-- `ontime.fact_ontime` — one row per US domestic flight (dates, carrier, origin/dest, delays, cancellations, …).
-- `ontime.dim_airports` — airport reference data; joined on `AirportCode = OriginCode AND IsLatest = 1` for human-readable airport names.
+The generator preserves the authored tile order and sizes, filters and
+defaults, KPI field configuration, semantic dashboard identity, and complete
+`flow@1` fallback.
@@ -0,0 +1,23 @@
+# Shop analytics dashboard
+
+The Shop example has two deliberately separate artifacts:
+
+- [`examples/shop-demo.sql`](../examples/shop-demo.sql) creates the `shop`
+  schema, sample events/products, dictionary, materialized views, aggregate
+  tables, and lineage relationships.
+- [`examples/shop-charts.json`](../examples/shop-charts.json) contains the
+  reusable queries and authored dashboard, without duplicating setup SQL.
+
+Load the SQL once with a suitably privileged ClickHouse client, then open the
+bundle with **File ▾ → Open…**. The dashboard shows Sales KPIs, Daily revenue,
+Revenue by country, Revenue by category, Top products, Daily active users, and
+Traffic by hour. Country revenue trends remain as an untiled Library analysis.
+
+The active range defaults to `-90d` through `now`. Country and Category are
+inactive searchable multiselects. Their target lists are explicit because the
+aggregate tables intentionally do not all carry both dimensions.
+
+The setup user needs create/insert privileges for `shop.*`. Dashboard users
+need `SELECT ON shop.*`; `SELECT ON system.dictionaries` is also required to
+show dictionary lineage. The dictionary's ClickHouse source user must be able
+to read `shop.products`.