timeplus-app-builder

name	timeplus-app-builder
description	Use when creating, packaging, or installing a Timeplus app (.tpapp) — converting existing SQL resources and dashboards into an installable app package, writing manifests, applying template variables, building dashboard JSON, or debugging install failures.
license	Apache-2.0
compatibility	Requires curl and zip. Installs against a Timeplus (neutron) server's app install API (default http://localhost:8000/<tenant>/api/v1beta2/apps/install).
metadata	{"author":"timeplus-io","version":"2.0.0","docs":"https://docs.timeplus.com","github":"https://github.com/timeplus-io/proton","tags":["timeplus","tpapp","app-packaging","manifest","dashboard","ddl"]}

Timeplus App Builder

Overview

A Timeplus app (.tpapp) is a zip archive that bundles a streaming data pipeline — DDL resources (streams, views, materialized views) plus dashboards — into a single installable unit. The installer provisions everything in order and rolls back on failure.

Quick Reference

Task	Reference
Dashboard panel spec — all chart types, viz_config, controls, position grid	references/dashboard-spec.md

Directory Structure

my-app/
├── manifest.yaml          # required
├── ddl/
│   ├── 001_first.sql      # executed in filename order
│   ├── 002_second.sql
│   └── ...
└── dashboards/
    └── main.json          # array of panel objects

Package it:

cd my-app && zip -r ../my-app.tpapp manifest.yaml ddl/ dashboards/

Install via API:

curl -X POST http://localhost:8000/default/api/v1beta2/apps/install \
  -F "file=@my-app.tpapp"

Override config: values at install time with config[<key>]=<value> form fields (multipart) — the neutron handler parses any form field matching config[*] into the rendered config map:

curl -X POST http://localhost:8000/default/api/v1beta2/apps/install \
  -F "file=@my-app.tpapp" \
  -F "config[strategy]=sign" \
  -F "config[num_stocks]=5"

For JSON-body installs (URL fetch), use {"url": "...", "config": {"strategy": "sign"}}.

manifest.yaml

package_format_version: 1          # must be 1
id: io.example.my-app              # reverse-domain, unique
name: My App
version: 1.0.0
author: Acme
description: What this app does.
icon: "data:image/png;base64,..."  # optional — base64 data URI; frontend shows default when absent
categories:                        # optional — free-form tags for discovery/filtering
  - security
  - observability
db_name: my_app                    # ^[a-z][a-z0-9_]{0,31}$, used as-is

config:                            # optional — user-supplied parameters
  - key: websocket_url
    type: string
    required: true
    description: WebSocket feed URL
  - key: api_key
    type: string
    required: true
    secret: true                   # mask value in UI; stored as IsSecret
    description: API key
  - key: timeout
    type: integer
    required: false
    default: "30"
    description: Connection timeout in seconds
  - key: tls_enabled
    type: bool
    required: false
    default: "false"
    description: Enable TLS
  - key: topics
    type: list
    required: true
    description: Kafka topics (JSON array of strings, e.g. '["a","b"]')
  - key: broker_type
    type: choice
    required: true
    description: Message broker
    options:
      - kafka
      - pulsar
      - redpanda
  - key: features
    type: multi_choice
    required: false
    default: '["metrics"]'
    description: Features to enable
    options:
      - metrics
      - tracing
      - alerting

python_packages:                   # optional — installed before any DDL runs
  - json5>=0.9.6
  - websocket-client>=1.4.0

resources:                         # executed in listed order
  - file: ddl/001_source.sql
    type: external_stream
    name: raw_feed
  - file: ddl/002_events.sql
    type: stream
    name: events
  - file: ddl/003_mv.sql
    type: materialized_view
    name: mv_events

dashboards:
  - file: dashboards/main.json
    name: My Dashboard
    description: Real-time view

Resource types

type	DDL verb	idempotent form	rolled back with
stream	CREATE STREAM	CREATE STREAM IF NOT EXISTS	DROP STREAM
external_stream	CREATE EXTERNAL STREAM	CREATE EXTERNAL STREAM IF NOT EXISTS	DROP STREAM
mutable_stream	CREATE MUTABLE STREAM	CREATE MUTABLE STREAM IF NOT EXISTS	DROP STREAM
materialized_view	CREATE MATERIALIZED VIEW	CREATE MATERIALIZED VIEW IF NOT EXISTS	DROP VIEW
view	CREATE VIEW	CREATE VIEW IF NOT EXISTS	DROP VIEW
external_table	CREATE TABLE	CREATE TABLE IF NOT EXISTS	DROP TABLE
udf	CREATE FUNCTION	CREATE OR REPLACE FUNCTION (see below)	DROP FUNCTION
task	CREATE TASK	CREATE TASK IF NOT EXISTS	DROP TASK
alert	CREATE ALERT	CREATE ALERT IF NOT EXISTS	DROP ALERT
input	CREATE INPUT	CREATE INPUT IF NOT EXISTS	DROP INPUT
dictionary	CREATE DICTIONARY	CREATE DICTIONARY IF NOT EXISTS	DROP DICTIONARY
format_schema	CREATE FORMAT SCHEMA	CREATE FORMAT SCHEMA IF NOT EXISTS	DROP FORMAT SCHEMA
named_collection	CREATE NAMED COLLECTION	CREATE NAMED COLLECTION IF NOT EXISTS	DROP NAMED COLLECTION

DDL Template Variables

DDL files are rendered with Go text/template using {{ }} delimiters.

Expression	Expands to
{{ .DB }}	The resolved database name (value of db_name)
{{ .Config.key_name }}	Value of config key (after defaults applied)

Always use dot notation for config values — {{ .Config.my_key }}, never {{ index .Config "my_key" }}.

-- ddl/002_events.sql
CREATE STREAM IF NOT EXISTS {{ .DB }}.events (
  id       string,
  payload  string
)
TTL to_datetime(_tp_time) + INTERVAL 24 HOUR;

-- ddl/001_source.sql
CREATE EXTERNAL STREAM IF NOT EXISTS {{ .DB }}.raw_feed (msg string)
SETTINGS url='{{ .Config.websocket_url }}', type='websocket';

Idempotency: every CREATE must be re-runnable

App upgrades re-run every DDL file against the existing database — the installer does not drop resources first. A CREATE that fails on the second run breaks upgrade. Every DDL file in apps/*/ddl/ must use one of the following forms:

Resource	Required form	Why
Everything except udf	CREATE … IF NOT EXISTS <name>	Re-running is a no-op. Existing rows, downstream consumers, and the resource UUID are preserved — critical for view and materialized_view, which are referenced by name from other resources and from dashboards.
udf	CREATE OR REPLACE FUNCTION <name>	UDFs are global (no database qualifier — see udf) and their body is typically what changes in an upgrade. OR REPLACE hot-swaps the implementation; IF NOT EXISTS would silently keep the old code on upgrade.

Do not use CREATE OR REPLACE VIEW. A view is a dependency for downstream MVs, queries, and dashboards. OR REPLACE would drop and recreate it, breaking anything referencing the view during the brief recreation window and on schema changes. Use CREATE VIEW IF NOT EXISTS — if the view definition needs to change, bump the app version and treat it as a migration (drop + recreate explicitly, or version the view name).

Forms that do NOT accept IF NOT EXISTS:

• SYSTEM INSTALL PYTHON PACKAGE — parser rejects IF NOT EXISTS. Don't put this in DDL; declare packages in manifest.yaml under python_packages (see Python packages).
• CREATE FUNCTION IF NOT EXISTS db.fn and CREATE FORMAT SCHEMA IF NOT EXISTS db.fs — both reject the db. prefix. UDFs and format schemas live in a global namespace; never qualify them with {{ .DB }}..

Dashboard Template Variables

Dashboard JSON is rendered with [[ ]] delimiters (to avoid collision with the frontend's {{filter_*}} runtime variables).

{
  "viz_content": "SELECT * FROM [[ .DB ]].events WHERE _tp_time > now() - {{filter_time_range}}"
}

Expression	Expands to
[[ .DB ]]	Database name
[[ .Config.key ]]	Config value
{{filter_*}}	Left as-is — resolved by the frontend at query time

Template processing runs before JSON parsing. This means template expressions inside JSON string values may contain unescaped " characters — the file does not need to be valid JSON before substitution.

Template Functions (Sprig)

Both DDL ({{ }}) and dashboard ([[ ]]) templates have the full Sprig function library available — the same library used by Helm. Use these to manipulate config values at install time.

Working with list config values

Config keys of type list are stored as a JSON array string (e.g. ["BTC-USD","ETH-USD","SOL-USD"]). Use fromJson to parse them before passing to other functions.

Render as comma-separated string (e.g. for dashboard selector inlineValues):

"inlineValues": "[[ join "," (fromJson .Config.product_ids) ]]"

→ "inlineValues": "BTC-USD,ETH-USD,SOL-USD"

Embed directly as JSON array (e.g. in a DDL Python string):

product_ids = '{{ .Config.product_ids }}'

→ product_ids = '["BTC-USD","ETH-USD","SOL-USD"]'

Get the first element (e.g. for a selector defaultValue):

"defaultValue": "[[ index (fromJson .Config.product_ids) 0 ]]"

→ "defaultValue": "BTC-USD"

Commonly used functions

Function	Example	Result
join sep list	join "," (fromJson .Config.topics)	a,b,c
fromJson s	fromJson .Config.product_ids	parsed slice
default val s	default "30" .Config.timeout	config value or fallback
upper s	upper .Config.env	PRODUCTION
lower s	lower .Config.env	production
trim s	trim .Config.url	strips whitespace
replace old new s	replace "-" "_" .Config.id	BTC_USD
splitList sep s	splitList "," .Config.tags	["a","b","c"]
first list	first (fromJson .Config.ids)	first element
last list	last (fromJson .Config.ids)	last element
len list	len (fromJson .Config.ids)	count

Full function reference: https://masterminds.github.io/sprig/

Dashboard JSON Reference

For the full dashboard panel specification — all chart types, viz_config fields, control panels, position grid, update modes, and working examples — see:

references/dashboard-spec.md

This covers:

• Panel structure (id, title, position, viz_type, viz_content, viz_config)
• 12-column position grid and common width/height values
• Template variables ([[ .DB ]] vs {{filter_*}})
• Control panels: selector (dropdown) and text_input
• Chart types: line, area, bar, column, singleValue, table, ohlc, geo, md, grammar (3.2+ — generic Vistral-grammar-driven viz: scatter, layered marks, band-axis bars, stacked area, custom transforms, etc.). For the underlying VistralSpec grammar (marks, transforms, scales, encode channels), see the Vistral skill: vistral/agentskill/SKILL.md.
• All viz_config.config fields per chart type with defaults
• updateMode ("all" / "key" / "time") — when to use each
• Default color palette
• Common mistakes

Timeplus SQL Reference

For writing correct Timeplus streaming SQL in DDL files, refer to the Timeplus SQL skill: https://github.com/timeplus-io/AgentSkills/tree/main/timeplus-sql-guide

This covers streaming query syntax, window functions, tumble/hop aggregations, _tp_time semantics, and other Timeplus-specific SQL features used in streams, views, and materialized views.

File Ordering and Dependencies

Name DDL files with a numeric prefix so they execute in dependency order:

001_source_stream.sql            ← external streams / sources
002_target_stream.sql            ← destination streams
003_mv_extract.sql               ← materialized views (depend on streams)
004_v_aggregated.sql             ← views (depend on streams/MVs)

Config Types

Seven types are supported. Omitting type defaults to string.

Type	Stored as	Valid example	Notes
string	plain string	"localhost:9092"	Default type
integer	decimal string	"30", "-5"	Must be a whole number
float	decimal string	"3.14", "30"	Decimal or whole
bool	"true" or "false"	"true"	No other values accepted
list	JSON array of strings	["a","b"]	Comma-separated strings NOT accepted
choice	string matching one option	"kafka"	Requires options: list
multi_choice	JSON array of strings, each matching an option	["kafka","pulsar"]	Requires options: list

options — required for choice and multi_choice; lists the allowed values:

  - key: broker_type
    type: choice
    required: true
    options:
      - kafka
      - pulsar

secret — only valid on string type; marks the value as sensitive (masked in UI, stored with IsSecret: true):

  - key: api_key
    type: string
    required: true
    secret: true
    description: API secret key

default — always a string regardless of type, and must be a valid encoding for the declared type:

  - key: timeout
    type: integer
    default: "30"         # valid — "30" is a legal integer encoding
  - key: features
    type: multi_choice
    default: '["metrics"]'
    options: [metrics, tracing]

Icon

The icon field in manifest.yaml sets the app's icon in the UI. It is optional — when absent, the frontend displays a default icon.

Format: base64 data URI with an image MIME type.

icon: "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mNk+M9QDwADhgGAWjR9awAAAABJRU5ErkJggg=="

Valid MIME types: image/png, image/jpeg, image/svg+xml, image/gif, etc.

Rules enforced by the installer:

• Must start with data:image/
• Must contain ;base64, followed by a non-empty payload
• An invalid icon causes the install to fail (same as a malformed manifest field)

Generating a data URI:

# PNG file → data URI
echo "data:image/png;base64,$(base64 -i icon.png | tr -d '\n')"

# SVG file → data URI
echo "data:image/svg+xml;base64,$(base64 -i icon.svg | tr -d '\n')"

Designing icons that match the Timeplus UI

The Timeplus frontend (AppCard.tsx) renders app icons as rounded squares. When no icon is provided it shows a default: a white outline box on a #D53F8C → #9F2BC0 diagonal gradient. Custom icons should be consistent with this style.

SVG is the best format — small, scalable, no raster artifacts.

Canonical icon template (48×48 viewBox):

<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 48 48">
  <defs>
    <linearGradient id="bg" x1="0" y1="0" x2="48" y2="48" gradientUnits="userSpaceOnUse">
      <stop offset="0%" stop-color="#D53F8C"/>
      <stop offset="100%" stop-color="#9F2BC0"/>
    </linearGradient>
  </defs>
  <rect width="48" height="48" rx="11" fill="url(#bg)"/>
  <!-- white stroke icon centered in the ~12–36 x/y region -->
</svg>

Icon style rules:

• Background: rounded square rx="11" with the pink→purple gradient (#D53F8C → #9F2BC0), matching the default icon's bg-gradient-to-br from-[#D53F8C] to-[#9F2BC0]
• Icon symbol: white, flat, thin-stroke outline (stroke="white" stroke-width="1.5" stroke-linecap="round" stroke-linejoin="round" fill="none")
• Icon occupies roughly the inner 24×24 area (coordinates 12–36 on the 48×48 canvas)
• Use fill="white" for solid accent shapes (e.g. a lightning bolt inside a shield)

Example icons for reference apps:

App	Symbol	SVG elements
Crypto market data	3-candle OHLC chart	<line> wicks + <rect> bodies (center candle filled)
GitHub activity	</> code brackets	Two <path> chevrons + a diagonal slash <line>
Complex event processing	3 nodes in a triangle	Three <circle> + connecting <line>/<path>
News feed	Newspaper	<rect> border + <line> rows
Trading / P&L	Trending-up chart	<polyline> with arrowhead
Security / DDoS	Shield + lightning bolt	Shield <path> (stroke) + bolt <path> (fill white)
Game analytics	Gamepad	Body <path> + D-pad <line> cross + button <circle>

Generating the data URI from an inline SVG string (Python):

import base64

svg = '<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 48 48">...</svg>'
b64 = base64.b64encode(svg.encode()).decode()
data_uri = f'data:image/svg+xml;base64,{b64}'
# paste into manifest.yaml as:  icon: ""

Categories

The categories field in manifest.yaml assigns free-form tags to the app for discovery and filtering in the UI. It is optional — when absent the app has no categories.

Format: a YAML list of strings. Values are unrestricted.

categories:
  - security
  - observability

Categories are surfaced in:

• GET /v1beta2/apps — each AppInstance includes a categories array
• GET /v1beta2/apps/available — each CatalogEntry includes a categories array

An app can belong to any number of categories. An empty or absent field is omitted from the JSON response (omitempty).

Config Defaults

Declared default values are applied automatically before template rendering. Users only need to supply required keys or keys they want to override.

config:
  - key: retention_hours
    type: integer
    required: false
    default: "24"
    description: Stream retention in hours

TTL to_datetime(_tp_time) + INTERVAL {{ .Config.retention_hours }} HOUR

Hiding Secrets in Python External Streams

Marking a config key secret: true only masks it in the install UI. Once the value is rendered into a DDL file via {{ .Config.<key> }}, it is stored verbatim in the resource definition — anyone with SHOW CREATE EXTERNAL STREAM privilege then sees it in cleartext. This matters most for Python external streams, where the $$ ... $$ body is the natural place to put credentials but is also the most exposed surface.

Pattern: keep the secret out of the Python body by putting it in a named_collection, then have Proton inject it into the stream's init_function_parameters setting at runtime. A small _tp_init() hook parses the JSON and stashes the values in module globals that the read function reads.

1. Declare the named collection (a DDL resource)

-- ddl/000_creds_nc.sql
CREATE NAMED COLLECTION IF NOT EXISTS aws_cost_creds AS
  init_function_parameters = '{"access_key_id":{{ .Config.aws_access_key_id | quote }},"secret_access_key":{{ .Config.aws_secret_access_key | quote }}}'
  NOT OVERRIDABLE;

• {{ ... | quote }} is the sprig quote function — it wraps the value in double quotes and escapes any internal " or \. Use it for every interpolated secret to keep the resulting blob valid JSON regardless of the raw value.
• NOT OVERRIDABLE prevents a caller from passing a different value at query time.
• Named collections are global — they live outside any database. Pick a name that includes your app's db_name (e.g. aws_cost_creds) so two apps on the same cluster don't collide. Do not template it with {{ .DB }} — the manifest's name: field is not template-rendered, so the literal SQL identifier must match the literal manifest name:. (This is the same convention as UDFs.)

Manifest entry — must be ordered before any stream that references it. The name: must match the literal SQL identifier exactly:

resources:
  - file: ddl/000_creds_nc.sql
    type: named_collection
    name: aws_cost_creds
  - file: ddl/001_poller.sql
    type: external_stream
    name: poller

2. Reference the collection from the Python external stream

-- ddl/001_poller.sql
CREATE EXTERNAL STREAM IF NOT EXISTS {{ .DB }}.poller (...)
AS $$
import json

# Populated by _tp_init() at session start. Leaving the literals empty here
# is what keeps secrets out of SHOW CREATE EXTERNAL STREAM.
AWS_ACCESS_KEY_ID = ""
AWS_SECRET_ACCESS_KEY = ""

def _tp_init(params):
    global AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY
    cfg = json.loads(params)
    AWS_ACCESS_KEY_ID = cfg["access_key_id"]
    AWS_SECRET_ACCESS_KEY = cfg["secret_access_key"]

def poll():
    # AWS_ACCESS_KEY_ID / AWS_SECRET_ACCESS_KEY are available here
    ...
$$
SETTINGS type='python', mode='streaming', read_function_name='poll',
         init_function_name='_tp_init', named_collection='aws_cost_creds';

How it works

1. The installer creates the named collection with the JSON blob. The collection lives outside the stream definition.
2. At storage construction time, Proton's updateSettingsByNamedCollection merges the collection's init_function_parameters into the in-memory ExternalStreamSettings, but SHOW CREATE EXTERNAL STREAM re-serializes the original parsed AST — so all it shows is SETTINGS … named_collection='<db>_creds'. The keys never appear.
3. When a query starts a read session, Proton calls _tp_init(params) once with the JSON string from the collection. The init function shares the module's global namespace with the read function, so the read function picks up the credentials.

Caveats

• system.named_collections still exposes the blob. Reading the collection map or create_query column from system.named_collections returns the raw JSON, since Proton only auto-masks the literal key password. Restrict that privilege to operators. Selecting just the name column is safe and works for discovery (SELECT name FROM system.named_collections).
• init_function_parameters is one string. Pack multiple secrets as JSON (as above). For a single value, a plain string is fine.
• init_function_name and init_function_parameters must both be set — Proton throws INVALID_SETTING_VALUE if you set parameters without a function name.
• Don't put non-secret config in the collection. Keep things like region lists, intervals, and toggles as ordinary {{ .Config.* }} template substitutions — they are easier to read in the DDL and contribute nothing to the SHOW CREATE risk.
• The init hook runs per session, not once globally. It's cheap (one JSON parse), but if you do anything expensive there, scope it behind a if not _ready: … guard.
• Named-collection values are snapshotted at stream-create time. ALTER NAMED COLLECTION updates system.named_collections, but an existing external stream keeps using the value it captured at CREATE EXTERNAL STREAM time — proton calls updateSettingsByNamedCollection only during storage construction. ALTER STREAM … MODIFY SETTING on an external stream is accepted by the engine, but the Python body (the $$ … $$ script) is bound to the storage via exec_script at create time, not via SETTINGS, so no ALTER … MODIFY SETTING can rewrite it. To rotate credentials or change the body you must DROP STREAM and re-create. Plan for that in your install/upgrade flow.

Common Mistakes

CREATE without IF NOT EXISTS (breaks upgrade)

Cause: App upgrades re-run every DDL file. A CREATE STREAM … (no guard) succeeds on first install and fails on every upgrade with Code: 57 ... already exists. Fix: Use CREATE … IF NOT EXISTS on every resource type except udf. For UDFs, use CREATE OR REPLACE FUNCTION (the body is what typically changes on upgrade). For views specifically: never use CREATE OR REPLACE VIEW — drop+recreate breaks dependents (downstream MVs, dashboards, other views). See Idempotency.

Multi-statement SQL files

Error: Syntax error: Multi-statements are not allowed
Fix: One SQL statement per file.

Reserved column names

Error: Column window_start is reserved
Fix: window_start (and window_end) are generated by tumble/hop. Name stream columns time or ts instead, and alias in the MV:

-- stream column: `time`
-- MV select:
SELECT window_start AS time, product_id, ...

Python packages not available at DDL time

Fix: Declare packages in python_packages in the manifest — the installer installs them and waits for completion before running any DDL. Do not use SYSTEM INSTALL PYTHON PACKAGE as a DDL resource; it is not needed and has no rollback.

Wrong template delimiter in dashboards

Fix: Use [[ .DB ]] in dashboard JSON, not {{ .DB }}. The {{ }} delimiter is reserved for frontend filter variables like {{filter_product}}.

chartType: "grammar" temporal sliding window appears empty / spans years

Cause: temporalRange is in minutes, not milliseconds. Setting it to 60000 (intending 1 minute) actually gives ~41 days. Fix: Use minute values directly: "temporalRange": 1 for a 60-second window, "temporalRange": 5 for 5 minutes. See references/dashboard-spec.md → "grammar".

chartType: "grammar" advancedSpec marks override drops the form's encode

Cause: The advancedSpec JSON is deep-merged via mergeDeepRight, which replaces arrays atomically. Supplying marks in advancedSpec discards the entire form-built mark (and its encode). Fix: When using advancedSpec to layer marks (e.g. line + point), declare every mark explicitly in the JSON — don't expect the form's mark to be preserved underneath. See the "Layered line + points" example in the grammar reference.

chartType: "grammar" legend won't hide with legendPosition: "none"

Cause: The shared Selector engine reserves the literal value 'none' for its placeholder item and coerces it to ''. Fix: Use "legendPosition": "hidden" to suppress the legend.

Multi-series line/area chart renders as a single overlapping line

Cause: viz_config.config.color left at "". The chart treats the result as one series and draws every point on the same line. Fix: Set "color" to the column that distinguishes series (e.g. "color": "stock_id" for SELECT time, stock_id, close FROM ...). The reference doc lists this as the required key for multi-series; see references/dashboard-spec.md → "line and area".

Dashboard WHERE filter fails with Missing columns: '_tp_time'

Cause: Views that alias window_start AS time (typical for tumble bars) do not propagate _tp_time to consumers. Fix: Filter on the exposed time column instead — WHERE time > now() - 5m.

Dashboard / resource name silently truncated at #

Cause: YAML treats # after whitespace as the start of a comment. name: Alpha #1 Backtest is parsed as name: Alpha. Fix: Quote any manifest value that contains # — name: "Alpha #1 Backtest", description: "Live prices and Alpha #1 leaderboard". Folded block scalars (description: > ...) treat # literally and are safe.

Unknown function nullif. Maybe you meant: ['null_if','null_in']

Cause: Timeplus uses snake_case for ClickHouse-derived functions (array_element, count_if, null_if, …). The bare ClickHouse name nullif appears to work in ad-hoc HTTP SELECT nullif(...) queries but is rejected by both the .tpapp install validator and the dashboard panel query path. Fix: Write null_if(x, y) in every SQL string — DDL files, dashboard viz_content, README snippets. Don't trust a green ad-hoc curl test; live-validate via the install path or the dashboard render if the query will live there.

Sprig template in dashboard JSON gets replaced by its rendered value after a UI edit

Cause: The Timeplus dashboard UI loads dashboards in their resolved form (e.g. inlineValues: "STOCK_0,STOCK_1,STOCK_2"), and when the user saves a layout tweak the UI writes back the resolved string — overwriting the source template (e.g. inlineValues: "[[ range $i, $_ := until (int .Config.num_stocks) ]]…[[ end ]]"). Auto-scaling behavior tied to .Config.* then silently breaks on next reinstall with a different config value. Fix: After any user-side UI edit to a dashboard, diff the file against HEAD before committing. If any [[ ]] Sprig expressions disappeared, restore them. Other formatting changes (sorted keys, per-line objects, layout x/y tweaks) are usually fine to keep.

Resource Type Reference

stream

A stream is the core storage primitive — an append-only event log with optional TTL. Use it as the destination for materialized views or external stream ingestion.

-- ddl/002_events.sql
CREATE STREAM IF NOT EXISTS {{ .DB }}.events (
  id        string,
  product   string,
  price     float64,
  _tp_time  datetime64(3) DEFAULT now64(3)
)
TTL to_datetime(_tp_time) + INTERVAL 24 HOUR;

Manifest entry:

  - file: ddl/002_events.sql
    type: stream
    name: events

external_stream

An external_stream connects to an outside data source (Kafka, WebSocket, Pulsar, etc.) without storing data locally. Queries read directly from the external system.

-- ddl/001_source.sql
CREATE EXTERNAL STREAM IF NOT EXISTS {{ .DB }}.raw_feed (msg string)
SETTINGS
  type='websocket',
  url='{{ .Config.websocket_url }}';

Manifest entry:

  - file: ddl/001_source.sql
    type: external_stream
    name: raw_feed

Common type values: kafka, websocket, pulsar, redpanda, confluent.

mutable_stream

A mutable_stream is like a stream but supports upserts — rows with the same primary key overwrite each other. Use it for keyed state (e.g., latest price per symbol).

-- ddl/005_ohlc.sql
CREATE MUTABLE STREAM IF NOT EXISTS {{ .DB }}.ohlc_1m (
  time      datetime64(3),
  symbol    string,
  open      float64,
  high      float64,
  low       float64,
  close     float64,
  PRIMARY KEY (time, symbol)
);

Manifest entry:

  - file: ddl/005_ohlc.sql
    type: mutable_stream
    name: ohlc_1m

materialized_view

A materialized_view continuously reads from a source stream, transforms the data, and writes results into a target stream. It runs as a persistent background query.

-- ddl/003_mv_parse.sql
CREATE MATERIALIZED VIEW IF NOT EXISTS {{ .DB }}.mv_parse
INTO {{ .DB }}.events
AS SELECT
  json_value(msg, '$.id')    AS id,
  json_value(msg, '$.price') AS price,
  now64(3)                   AS _tp_time
FROM {{ .DB }}.raw_feed;

Manifest entry:

  - file: ddl/003_mv_parse.sql
    type: materialized_view
    name: mv_parse

The target stream (INTO) must be declared before the MV in the manifest.

view

A view is a saved streaming query with no storage of its own. Every query against the view re-executes the underlying SELECT in real time.

-- ddl/004_v_btc.sql
CREATE VIEW IF NOT EXISTS {{ .DB }}.v_btc
AS SELECT * FROM {{ .DB }}.events WHERE product = 'BTC-USD';

Never use CREATE OR REPLACE VIEW. A view is a stable dependency for downstream MVs, dashboards, and other views. OR REPLACE drops and recreates the view, breaking dependents — use IF NOT EXISTS and treat definition changes as explicit migrations (bump app version, drop and recreate, or version the view name).

Manifest entry:

  - file: ddl/004_v_btc.sql
    type: view
    name: v_btc

external_table

An external_table maps to external storage (S3, ClickHouse, etc.) for historical (batch) queries. Unlike external streams, it is not suited for real-time streaming reads.

-- ddl/006_s3_archive.sql
CREATE TABLE IF NOT EXISTS {{ .DB }}.s3_archive (
  event_time datetime,
  payload    string
) SETTINGS
  type='s3',
  url='{{ .Config.s3_url }}',
  format='JSONEachRow';

Manifest entry:

  - file: ddl/006_s3_archive.sql
    type: external_table
    name: s3_archive

udf

A udf registers a Python function for use in SQL queries. The function body is embedded directly in the DDL.

UDFs are global — they do not belong to a database. Never prefix the function name with {{ .DB }}. in CREATE FUNCTION or CALL; doing so causes a syntax error (failed at position N ('.')).

-- ddl/007_notify_slack.sql
CREATE OR REPLACE FUNCTION notify_slack(channel string, message string)
RETURNS bool
LANGUAGE PYTHON AS $$
import requests
def notify_slack(channel, message):
    url = '{{ .Config.slack_webhook_url }}'
    requests.post(url, json={'channel': channel, 'text': message})
    return [True] * len(channel)
$$;

Manifest entry:

  - file: ddl/007_notify_slack.sql
    type: udf
    name: notify_slack

Tasks, Alerts, and Inputs

Task

A task runs a historical (batch) query on a schedule and writes results to a target stream. It complements materialized views for periodic aggregations or snapshots.

-- ddl/010_hourly_summary.sql
CREATE TASK IF NOT EXISTS {{ .DB }}.hourly_summary
SCHEDULE INTERVAL 1 HOUR
TIMEOUT INTERVAL 5 MINUTE
INTO {{ .DB }}.summary_stream
AS SELECT product_id, avg(price) AS avg_price, count() AS trades
   FROM {{ .DB }}.coinbase_tickers
   WHERE _tp_time > now() - INTERVAL 1 HOUR;

Manifest entry:

  - file: ddl/010_hourly_summary.sql
    type: task
    name: hourly_summary

Key clauses:

• SCHEDULE INTERVAL <n> <unit> — how often to run; next run begins only after previous completes
• TIMEOUT INTERVAL <n> <unit> — aborts the run if it exceeds this duration
• INTO <target_stream> — destination stream for results

Alert

An alert monitors a streaming query and calls a Python UDF when the condition is met. Use it to send notifications (Slack, email, webhook) or trigger external actions.

-- ddl/011_price_alert.sql
CREATE ALERT IF NOT EXISTS {{ .DB }}.price_spike_alert
BATCH 10 EVENTS WITH TIMEOUT 5s
LIMIT 1 ALERTS PER 10s
CALL {{ .DB }}.notify_slack
AS SELECT product_id, price, _tp_time
   FROM {{ .DB }}.coinbase_tickers
   WHERE price > {{ .Config.alert_threshold }};

Manifest entry:

  - file: ddl/011_price_alert.sql
    type: alert
    name: price_spike_alert

Key clauses:

• BATCH <N> EVENTS WITH TIMEOUT <interval> — fires the UDF after N events accumulate or the timeout elapses, whichever comes first
• LIMIT <M> ALERTS PER <interval> — rate-limits to prevent alert storms
• CALL <python_udf> — the Python UDF to invoke; its signature must match the SELECT projection
• The query must be a simple SELECT — no joins or aggregations (use a materialized view upstream for complex logic)
• Only Python UDFs are supported

Input

An input starts a long-running server (TCP, UDP, HTTP, or gRPC) that accepts data pushed by external clients and writes it to a target stream. Supported protocols: splunk-s2s, splunk-hec, datadog, elastic, otel, netflow, syslog.

-- ddl/001_syslog_input.sql
CREATE INPUT IF NOT EXISTS {{ .DB }}.syslog_in
SETTINGS
  type='syslog',
  target_stream='{{ .DB }}.raw_logs',
  tcp_port={{ .Config.syslog_port }},
  listen_host='0.0.0.0'
COMMENT 'Syslog receiver';

Manifest entry:

  - file: ddl/001_syslog_input.sql
    type: input
    name: syslog_in

Key settings:

• type — protocol (splunk-s2s, splunk-hec, datadog, elastic, otel, netflow, syslog)
• target_stream — destination stream (must exist before the input is created)
• tcp_port — port to bind
• listen_host — address to bind (use '0.0.0.0' for all interfaces)

Error Messages Include Resource Name

Install errors are wrapped with the resource name:

provision mv_coinbase_1s: code: 44, message: Column window_start is reserved...

The prefix (provision <name>:) tells you exactly which DDL file failed.

Makefile Shortcut

APP_DIR  ?= my-app
OUT      ?= $(APP_DIR).tpapp
NEUTRON_URL ?= http://localhost:8000
TENANT      ?= default

build:
	cd $(APP_DIR) && zip -r ../$(OUT) manifest.yaml ddl/ dashboards/

install: build
	curl -X POST $(NEUTRON_URL)/$(TENANT)/api/v1beta2/apps/install -F "file=@$(OUT)"