# SQL Usage

> Timeplus streaming SQL covering stream types, EMIT policies, window functions, JOINs, materialized views, external streams, and UDFs. Make sure to use this skill for any SQL-related question including writing queries, debugging SQL errors, understanding streaming behavior, or designing stream processing pipelines, even if the user doesn't explicitly mention streaming SQL.

- Skill: `timeplus-io/sql-usage` (Agent Skill, multi-file: 8 files)
- Install (CLI): `npx skillmds@latest add timeplus-io/sql-usage`
- Raw SKILL.md: https://api.skillmd.com/api/skills/timeplus-io/sql-usage/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Data & Analytics
- Author: timeplus-io (https://skillmd.com/u/timeplus-io)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/timeplus-io/sql-usage

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# Streaming SQL

Source of truth: https://docs.timeplus.com | Raw markdown: https://github.com/timeplus-io/docs/tree/main/docs

## Naming rules

| Element | Style | Example |
|---------|-------|---------|
| Keywords | `UPPERCASE` | `SELECT`, `CREATE STREAM`, `EMIT`, `JOIN` |
| Functions | `lowercase` | `count()`, `tumble()`, `date_diff_within()` |
| Data types | `lowercase` | `int64`, `float64`, `string`, `datetime64` |
| Identifiers | `lowercase_with_underscores` | `event_time`, `user_id` |
| Reserved fields | `_tp_` prefix | `_tp_time` (event timestamp), `_tp_delta` (changelog) |

## Stream type decision table

| Need | Type | Syntax |
|------|------|--------|
| Immutable events, time-series, high throughput | append (default) | `CREATE STREAM ... ORDER BY` |
| Updates/upserts, point queries, KV (first choice) | mutable | `CREATE MUTABLE STREAM ... PRIMARY KEY` |
| Version history, ASOF JOINs | versioned_kv | `CREATE STREAM ... PRIMARY KEY ... SETTINGS mode='versioned_kv'` |
| CDC semantics, track deletes via `_tp_delta` | changelog_kv | `CREATE STREAM ... PRIMARY KEY ... SETTINGS mode='changelog_kv'` |
| External source (Kafka, Pulsar, etc.) | external | `CREATE EXTERNAL STREAM ... SETTINGS type='kafka'` |

Full details → [references/stream-types.md](references/stream-types.md)

## Query modes

- `SELECT FROM stream` → streaming (continuous, future events)
- `SELECT FROM table(stream)` → historical (batch scan, returns once)

Three trigger types:
| Query type | Trigger |
|-----------|---------|
| Non-aggregation (tail/filter/transform) | When events arrive |
| Window aggregation | Window end + watermark |
| Global aggregation | Fixed interval (default 2s if `EMIT PERIODIC` omitted) |

## Window functions quick reference

| Function | Signature | Use case |
|----------|-----------|----------|
| `tumble` | `tumble(stream, [time_col], interval, [tz])` | Fixed non-overlapping windows |
| `hop` | `hop(stream, [time_col], slide, size, [tz])` | Sliding/overlapping windows |
| `session` | `session(stream, [time_col], MAXSPAN x AND TIMEOUT y)` | Inactivity-based windows |

- `time_col` defaults to `_tp_time` if omitted
- Intervals: `1s`, `5m`, `2h`, `3d`, `1w`, `1M`, `1q`, `1y`
- `window_start`, `window_end` auto-generated (left-closed, right-open `[)`)
- Hop: slide and size must use same unit; slide > size is unsupported
- Window nesting: max 2 levels; window-over-global is unsupported

## EMIT policy quick reference

| Context | Policy | Effect |
|---------|--------|--------|
| Window | `EMIT AFTER WINDOW CLOSE` | Default for windowed agg |
| Window | `EMIT AFTER WINDOW CLOSE WITH DELAY 2s` | Allow late events |
| Window | `EMIT AFTER WINDOW CLOSE WITH DELAY 1s AND TIMEOUT 3s` | Late events + force-close |
| Window | `EMIT ON UPDATE` | Emit when agg value changes per key |
| Window | `EMIT ON UPDATE WITH BATCH 2s` | Batched update detection |
| Global | `EMIT PERIODIC 5s` | Default (2s), batch periodic output |
| Global | `EMIT PERIODIC 5s REPEAT` | Emit even without new events |
| Global | `EMIT ON UPDATE` | Immediate on every change |
| Global | `EMIT CHANGELOG` | With `_tp_delta` (+1/-1) |
| Global | `EMIT PER EVENT` | Per-event (debug only, no parallelism) |
| Global | `EMIT AFTER KEY EXPIRE ... WITH MAXSPAN x AND TIMEOUT y` | Tracing/span aggregation |

Full formal syntax → [references/emit-policies.md](references/emit-policies.md)

## JOIN quick reference

| Pattern | Syntax key | Use case |
|---------|-----------|----------|
| Static enrichment | `stream JOIN table(lookup)` | Enrich with historical data |
| Dynamic enrichment | `append JOIN versioned_kv USING(k)` | Latest version auto-picked |
| Bidirectional | `mutable JOIN mutable` | Both sides updatable |
| Range (time-bounded) | `stream JOIN stream ... AND date_diff_within(2m)` | Bounded stream-to-stream |
| ASOF | `append ASOF JOIN versioned_kv ON ... AND t1 >= t2` | Closest version match |
| LATEST | `append LATEST JOIN versioned_kv ON ...` | Latest value only |
| Direct lookup | `stream JOIN mutable ... SETTINGS join_algorithm='direct'` | PK/index lookup, no full load |
| Dictionary | `stream JOIN dict ... SETTINGS join_algorithm='direct'` | External source lookup |

Supported: INNER, LEFT, FULL. Unsupported: RIGHT, CROSS.
Strictness: ALL (default), ASOF, LATEST.

Full examples → [references/join-patterns.md](references/join-patterns.md)

## Materialized view checklist

- [ ] Stateless test default: use MatView without `INTO`, then verify with `table(mv)`
- [ ] Create target stream FIRST only when you need an extra sink stream
- [ ] Use explicit `INTO target` only when a target stream is required by the scenario
- [ ] Configure checkpointing: `SETTINGS checkpoint_interval=30`
- [ ] High-cardinality: `SETTINGS default_hash_table='hybrid', max_hot_keys=10000`
- [ ] Schema evolution (with target stream): `ALTER STREAM` target + `ALTER VIEW ... MODIFY QUERY`
- [ ] Cleanup order: `DROP VIEW` → (if created) `DROP STREAM` target → `DROP STREAM` source

Full config → [references/mv-production.md](references/mv-production.md)

## External stream (Kafka) quick reference

```sql
CREATE EXTERNAL STREAM events(raw string)
SETTINGS type='kafka', brokers='host:9092', topic='events';
```

Key settings: `data_format`, `security_protocol`, `sasl_mechanism`, `kafka_schema_registry_url`
Virtual columns: `_tp_message_key`, `_tp_message_headers`, `_tp_sn` (offset), `_tp_shard` (partition)
Query options: `SETTINGS shards='0,2'`, `seek_to='earliest'`

Full details → [references/external-streams.md](references/external-streams.md)

## UDF quick reference

```sql
CREATE FUNCTION udf_name(param type) RETURNS type LANGUAGE JAVASCRIPT AS $$ ... $$;
```

Scalar: receives array of values (batched), returns array.
UDAF: implement `initialize`, `process`, `finalize`, `serialize`, `deserialize`, `merge`.

Full details → [references/udf.md](references/udf.md)

## References

- [Stream type details and examples](references/stream-types.md)
- [All EMIT policies with formal syntax](references/emit-policies.md)
- [JOIN patterns with full examples](references/join-patterns.md)
- [Production materialized view configuration](references/mv-production.md)
- [External streams (Kafka, Pulsar)](references/external-streams.md)
- [User-defined functions (UDF/UDAF)](references/udf.md)