# Time-series with Arcadic

## Setup

`Arcadic.TimeSeries` is a tenant-blind client for ArcadeDB's time-series surface: the
`TIMESERIES` DDL, InfluxDB line-protocol writes, JSON query/latest reads, PromQL reads
(instant, range, labels, series), continuous aggregates, and downsampling policies. This
notebook walks all of it against a throwaway `sensor` type.

This notebook needs a running **ArcadeDB >= 26.7.2** — the `/api/v1/ts` routes don't
exist on older servers (they answer a plain 404). The quickest way is Docker:

```
docker run -d --name arcadic-timeseries \
  -p 2480:2480 \
  -e JAVA_OPTS="-Darcadedb.server.rootPassword=playwithdata" \
  arcadedata/arcadedb:latest
```

Only the HTTP port (**2480**) is needed — every operation below, including PromQL reads,
rides the same HTTP endpoint; none of it needs Bolt (see
[`getting_started.livemd`](getting_started.livemd) for the Bolt transport).

Every connection value can be overridden with an environment variable set before you
launch Livebook (`ARCADIC_HTTP_URL`, `ARCADIC_PASSWORD`); otherwise the defaults match
the `docker run` above.

> **Re-running cells.** The continuous-aggregate and downsampling cells create and drop
> within the same cell, so they re-run cleanly. The **sensor type** cell is the one
> exception: `CREATE TIMESERIES TYPE` has no `IF NOT EXISTS` on 26.7.2 (dropping a type
> that doesn't exist yet is a server error too), so that cell (under **Define the
> type**) issues an explicit,
> discarded `drop_type` immediately before `create_type!` — safe to re-run in isolation.
> **Writing points is append-only by design** (see the callout below) — re-running that
> section adds more points, it never errors, but the row counts you see will grow with
> every re-run. Run **Cleanup** at the bottom, then top to bottom, for a clean slate.

## Install

> **Requires an unreleased arcadic build.** `Arcadic.TimeSeries` is not in any published
> release yet. Concretely, as of this writing: Hex hosts only `0.4.0`, so the `~> 0.6`
> requirement below doesn't resolve at all (`Mix.install` fails immediately with
> `version solving failed`, not a silent downgrade); the module also isn't yet on the
> `main` branch on GitHub, so `{:arcadic, github: "baselabs/arcadic"}` won't have it
> either until that catches up. The only way to run this notebook today is a local path
> dependency against a checkout that has the module, e.g.
> `{:arcadic, path: "/path/to/your/arcadic/checkout"}` in place of the pin below. Once a
> release carrying it is published (and pushed), the `~> 0.6` pin resolves normally and
> this note no longer applies.

```elixir
Mix.install([
  {:arcadic, "~> 0.7"},
  {:kino, "~> 0.14"}
])
```

## Connect

We create a throwaway `arcadic_timeseries` database to play in (only if it does not
already exist, so this cell is safe to re-run).

```elixir
http_url = System.get_env("ARCADIC_HTTP_URL", "http://localhost:2480")
password = System.get_env("ARCADIC_PASSWORD", "playwithdata")
database = "arcadic_timeseries"

admin = Arcadic.connect(http_url, database, auth: {"root", password})
{:ok, true} = Arcadic.Server.ready?(admin)

unless match?({:ok, true}, Arcadic.Server.database_exists?(admin, database)) do
  Arcadic.Server.create_database!(admin, database)
end

conn = Arcadic.connect(http_url, database, auth: {"root", password})
```

## Define the type

`Arcadic.TimeSeries.create_type!/4` emits `CREATE TIMESERIES TYPE` — a `sensor` type
tagged by `sensor_id`/`location`, carrying `temperature`/`humidity` fields, millisecond
precision, and a 90-day retention window.

```elixir
# No IF NOT EXISTS on 26.7.2 -- the discarded drop makes this cell safe to re-run
# in isolation (dropping a not-yet-existing type errors too; `_ =` discards either way).
_ = Arcadic.TimeSeries.drop_type(conn, "sensor")

:ok =
  Arcadic.TimeSeries.create_type!(conn, "sensor", "ts",
    fields: [temperature: "DOUBLE", humidity: "DOUBLE"],
    tags: [sensor_id: "STRING", location: "STRING"],
    precision: :millisecond,
    retention: {90, :days}
  )
```

## Writing points

`Arcadic.TimeSeries.write/3` builds InfluxDB line protocol from structured point maps —
typed fields, string tags, and an explicit timestamp. Note there are two precision
grammars: the DDL takes `:millisecond`-style tokens (as in `create_type!` above), while
the write path takes wire tokens (`:ns | :us | :ms | :s`) — each rejects the other's.
Wire `:precision` declares the unit of the timestamps you put in the body, independent
of the type's declared storage `PRECISION`: the timestamps below are epoch-milliseconds,
hence `precision: :ms`. Omitting it means `:ns` — millisecond timestamps read as
nanoseconds land every point in January 1970.

```elixir
now_ms = System.system_time(:millisecond)

:ok =
  Arcadic.TimeSeries.write(
    conn,
    [
      %{
        type: "sensor",
        tags: %{"sensor_id" => "s1", "location" => "lab-a"},
        fields: %{"temperature" => 21.5, "humidity" => 45.0},
        timestamp: now_ms - 60_000
      },
      %{
        type: "sensor",
        tags: %{"sensor_id" => "s1", "location" => "lab-a"},
        fields: %{"temperature" => 22.0, "humidity" => 44.0},
        timestamp: now_ms
      }
    ],
    precision: :ms
  )
```

`Arcadic.TimeSeries.write_lines/3` is the raw passthrough — useful for relaying an
already-built batch (e.g. forwarding a Telegraf line) without going through the point-map
builder.

```elixir
:ok =
  Arcadic.TimeSeries.write_lines(
    conn,
    "sensor,sensor_id=s2,location=lab-b temperature=19.0,humidity=50.0 #{now_ms}",
    precision: :ms
  )
```

> **Operational contract** (from the `Arcadic.TimeSeries` moduledoc, live-probed on
> 26.7.2 — read this before relying on retries or mixed-type batches):
>
> - **Append-only, non-idempotent.** No dedup, no upsert, no server-assigned id: the
>   identical point written twice is TWO rows. A lost response followed by a naive retry
>   duplicates every point in the body. There is no idempotent write path — before
>   retrying an unconfirmed write, verify whether it landed with a windowed `query/3`
>   count over the batch's time range.
> - **Mixed-body partial swallow.** When at least one line's type exists, lines naming an
>   unknown type are silently dropped (HTTP 204) rather than erroring. Verify with
>   `query/3` or `Arcadic.Schema.types/1` when it matters.
> - **Unknown FIELD zero-fill.** A line whose field name is not on the type inserts a
>   zero-filled row (204, no error).
> - **Unknown tag KEY fails open** on `query/3`/`latest/3` — the filter is ignored
>   server-side rather than rejected.

## Querying

A raw window query returns the server's columnar shape — `columns`/`rows`/`count` — for
every point regardless of tag.

```elixir
{:ok, %{columns: columns, rows: rows, count: count}} =
  Arcadic.TimeSeries.query(conn, "sensor", from: now_ms - 3_600_000, to: now_ms + 3_600_000)

{columns, count}
```

`:tags` is a map the server ANDs together — every entry must match.

```elixir
{:ok, %{count: s1_count}} =
  Arcadic.TimeSeries.query(conn, "sensor",
    from: now_ms - 3_600_000,
    to: now_ms + 3_600_000,
    tags: %{"sensor_id" => "s1", "location" => "lab-a"}
  )

s1_count
```

`:aggregation` with a REQUIRED `:bucket_interval` buckets the window and reduces each
bucket — here, an hourly `AVG` of `temperature` for `s1`.

```elixir
{:ok, %{aggregations: aggregations, buckets: buckets}} =
  Arcadic.TimeSeries.query(conn, "sensor",
    from: now_ms - 3_600_000,
    to: now_ms + 3_600_000,
    tags: %{"sensor_id" => "s1"},
    aggregation: [%{field: "temperature", type: :avg}],
    bucket_interval: {1, :hours}
  )

{aggregations, buckets}
```

`Arcadic.TimeSeries.latest/3` returns the single newest point matching one tag filter.

```elixir
{:ok, %{columns: latest_columns, latest: latest}} =
  Arcadic.TimeSeries.latest(conn, "sensor", tag: {"sensor_id", "s1"})

Enum.zip(latest_columns, latest) |> Map.new()
```

## PromQL

Every `TIMESERIES` type doubles as a Prometheus metric: the metric name is the type name,
and tags are labels — no separate registration step. `:time`/`from`/`to` are
epoch-**seconds** here (PromQL convention), unlike `query/3`'s epoch-milliseconds.

```elixir
# +1: div/2 floors the second, and a Prometheus instant query excludes a sample AT OR
# AFTER the eval instant -- evaluating one second past the floor is what actually shows
# the millisecond-timestamped sample written above (live-probed on 26.7.2).
now_s = div(now_ms, 1000) + 1

{:ok, %{"resultType" => "vector", "result" => instant_result}} =
  Arcadic.TimeSeries.prom_query(conn, ~S(sensor{sensor_id="s1"}), time: now_s)

instant_result
```

```elixir
{:ok, %{"resultType" => "matrix", "result" => range_result}} =
  Arcadic.TimeSeries.prom_query_range(
    conn,
    ~S(sensor{sensor_id="s1"}),
    now_s - 3600,
    now_s + 60,
    60
  )

range_result
```

```elixir
{:ok, labels} = Arcadic.TimeSeries.prom_labels(conn)
{:ok, metric_names} = Arcadic.TimeSeries.prom_label_values(conn, "__name__")

# "sensor" -- the TIMESERIES type name, not a name we registered anywhere -- shows up
# among __name__'s values: the metric name IS the type name.
{labels, "sensor" in metric_names}
```

## SQL over time-series

`Arcadic.query/4` reaches `sensor` like any other type — the `ts.timeBucket` SQL function
buckets the timestamp column, and the params-only rule (`:name` placeholders, never
interpolation) applies here exactly as it does everywhere else in Arcadic.

```elixir
{:ok, sql_rows} =
  Arcadic.query(
    conn,
    "SELECT ts.timeBucket('1h', ts) AS hour, sensor_id, avg(temperature) AS avg_temp " <>
      "FROM sensor WHERE sensor_id = :sensor_id GROUP BY hour, sensor_id",
    %{"sensor_id" => "s1"},
    language: "sql"
  )

Kino.DataTable.new(sql_rows)
```

## Continuous aggregates & downsampling

`Arcadic.TimeSeries.create_aggregate/3` materializes a `SELECT` as a document type,
refreshed on demand; neither it nor `drop_aggregate/2` has an `IF EXISTS` form, so this
cell creates, refreshes, reads, and drops within itself — safe to re-run.

```elixir
:ok =
  Arcadic.TimeSeries.create_aggregate(
    conn,
    "hourly_sensor",
    "SELECT ts.timeBucket('1h', ts) AS hour, sensor_id, avg(temperature) AS avg_temp " <>
      "FROM sensor GROUP BY hour, sensor_id"
  )

:ok = Arcadic.TimeSeries.refresh_aggregate(conn, "hourly_sensor")

{:ok, ca_rows} = Arcadic.query(conn, "SELECT FROM hourly_sensor", %{}, language: "sql")

:ok = Arcadic.TimeSeries.drop_aggregate(conn, "hourly_sensor")

ca_rows
```

A downsampling policy tells ArcadeDB to compact older points at a coarser granularity;
add and drop it here too, in the same cell.

```elixir
:ok =
  Arcadic.TimeSeries.add_downsampling(conn, "sensor", after: {7, :days}, granularity: {1, :hours})

:ok = Arcadic.TimeSeries.drop_downsampling(conn, "sensor")
```

## Prometheus & Grafana integration

The PromQL family above is arcadic's app-facing wrapper for the same data a real
Prometheus/Grafana deployment would scrape — the wire endpoints below are deployment
configuration, not something arcadic calls on your behalf.

Point a Prometheus server's remote-write/remote-read at this database's `/ts` prefix to
have it treat ArcadeDB as its storage backend:

```yaml
remote_write:
  - url: "http://<host>:2480/api/v1/ts/<db>/prom/write"
    basic_auth:
      username: root
      password: <password>
remote_read:
  - url: "http://<host>:2480/api/v1/ts/<db>/prom/read"
    basic_auth:
      username: root
      password: <password>
```

Point Grafana's built-in **Prometheus** datasource at the same prefix (its query path)
to graph `sensor` alongside any other Prometheus-compatible source:

```yaml
apiVersion: 1
datasources:
  - name: ArcadeDB Sensor
    type: prometheus
    url: http://<host>:2480/api/v1/ts/<db>/prom
    basicAuth: true
    basicAuthUser: root
    secureJsonData:
      basicAuthPassword: <password>
```

ArcadeDB also exposes Grafana Infinity/native endpoints server-side
(`/grafana/health|metadata|query`) for panels that talk to it directly rather than
through the Prometheus datasource. Arcadic wraps the app-facing PromQL and query/write
surfaces above; wiring either machine-to-machine path into a running Prometheus or
Grafana instance is deployment configuration outside the client's scope.

## Cleanup

Drop the throwaway database when you are done (or before a fresh top-to-bottom run).
This tears down `sensor`, its data, and any continuous aggregate or downsampling policy
left over from a partial run.

```elixir
Arcadic.Server.drop_database(admin, database)
```