2026-05-10 23:12:26 +02:00
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import { describe, expect, it, vi } from 'vitest';
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test: split cli tests from source tree (#216)
* feat(cli): define full warehouse dialect contract
* test(cli): keep dialect edge tests focused
* fix(cli): stabilize dialect contract foundation
* refactor(connectors): own read-only query preparation
* refactor(connectors): resolve dialects through registry
* refactor(connectors): keep concrete dialect classes internal
* chore(workspace): enforce dialect import boundary
* refactor(cli): resolve relationship dialect at scan boundary
* refactor(cli): use dialect display parsing for entity details
* refactor(cli): use dialect display parsing for warehouse catalog
* refactor(cli): use dialect SQL in relationship workflows
* test(cli): verify solid dialect scan workflow closure
* test: split cli tests from source tree
* refactor(cli): standardize BigQuery scope listing
* feat(sqlite): implement connector scope listing
* test(connectors): cover required table listing
* feat(cli): add warehouse driver registry
* refactor(setup): route scope discovery through driver registry
* refactor(cli): route local query execution through driver registry
* refactor(historic-sql): route dialect support through driver registry
* refactor(cli): test warehouse connections through driver registry
* fix(cli): close driver registry type export gaps
* Improve setup daemon diagnostics
* refactor(setup): centralize rail-prefixed diagnostics + query-history fallback
Extract errorMessage, writePrefixedLines, and flushPrefixedBufferedCommandOutput
into clack.ts so the setup wizard, managed daemons, and embedding/agent steps
share one rail-formatted writer. setup-databases.ts also adds a
"disable query history and retry" option when the schema-context build fails
and query history is the likely culprit, surfaced via a new
failed-query-history-unavailable status.
* fix(cli): carry catalog through the picker so BigQuery/Snowflake/SQL Server scope filters match
The setup picker's KtxTableListEntry was a 2-level { schema, name }, so
qualifiedTableId always wrote db.name into enabled_tables. When BigQuery,
Snowflake, or SQL Server later ran fast ingest, their introspect step filtered
the scope set with scopedTableNames(scope, { catalog: projectId|database, db })
— catalog was non-null on the introspect side but null in the scope refs, so
every entry was rejected, the live-database adapter staged zero table files,
and detect() failed with 'Adapter "live-database" did not recognize fetched
source output'.
Align the picker boundary with the canonical 3-level KtxTableRef:
- Add catalog: string | null to KtxTableListEntry.
- BigQuery/Snowflake/SQL Server listTables populate catalog from the
resolved projectId / database; Postgres/MySQL/ClickHouse/SQLite set null.
- qualifiedTableId emits catalog.schema.name when catalog is non-null
(resolveEnabledTables already accepts the 3-part shape) and
schemasFromEnabledTables now goes through parseDottedTableEntry so it
recovers the schema correctly from both 2-part and 3-part entries.
- Export parseDottedTableEntry from enabled-tables.ts (@internal) for picker
reuse.
Update listTables expectations in all seven connector tests and the setup /
picker test fixtures. Add a picker regression test that covers the
catalog-bearing round-trip (save + refine).
* fix(cli): allow debug telemetry under opt-out env
2026-05-26 08:49:05 +02:00
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import { clickHouseClientConfigFromConfig, isKtxClickHouseConnectionConfig, KtxClickHouseScanConnector, prepareClickHouseReadOnlyQuery, type KtxClickHouseClientFactory } from '../../../src/connectors/clickhouse/connector.js';
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import { createClickHouseLiveDatabaseIntrospection } from '../../../src/connectors/clickhouse/live-database-introspection.js';
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import { tableRefSet } from '../../../src/context/scan/table-ref.js';
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2026-05-10 23:12:26 +02:00
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function result<T>(payload: T) {
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return {
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async json(): Promise<T> {
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return payload;
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},
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};
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}
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2026-05-10 23:51:24 +02:00
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function fakeClientFactory(): KtxClickHouseClientFactory {
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2026-05-10 23:12:26 +02:00
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const query = vi.fn(async (input: { query: string; format: string; query_params?: Record<string, unknown> }) => {
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if (input.query.includes('FROM system.tables')) {
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return result([
|
test: split cli tests from source tree (#216)
* feat(cli): define full warehouse dialect contract
* test(cli): keep dialect edge tests focused
* fix(cli): stabilize dialect contract foundation
* refactor(connectors): own read-only query preparation
* refactor(connectors): resolve dialects through registry
* refactor(connectors): keep concrete dialect classes internal
* chore(workspace): enforce dialect import boundary
* refactor(cli): resolve relationship dialect at scan boundary
* refactor(cli): use dialect display parsing for entity details
* refactor(cli): use dialect display parsing for warehouse catalog
* refactor(cli): use dialect SQL in relationship workflows
* test(cli): verify solid dialect scan workflow closure
* test: split cli tests from source tree
* refactor(cli): standardize BigQuery scope listing
* feat(sqlite): implement connector scope listing
* test(connectors): cover required table listing
* feat(cli): add warehouse driver registry
* refactor(setup): route scope discovery through driver registry
* refactor(cli): route local query execution through driver registry
* refactor(historic-sql): route dialect support through driver registry
* refactor(cli): test warehouse connections through driver registry
* fix(cli): close driver registry type export gaps
* Improve setup daemon diagnostics
* refactor(setup): centralize rail-prefixed diagnostics + query-history fallback
Extract errorMessage, writePrefixedLines, and flushPrefixedBufferedCommandOutput
into clack.ts so the setup wizard, managed daemons, and embedding/agent steps
share one rail-formatted writer. setup-databases.ts also adds a
"disable query history and retry" option when the schema-context build fails
and query history is the likely culprit, surfaced via a new
failed-query-history-unavailable status.
* fix(cli): carry catalog through the picker so BigQuery/Snowflake/SQL Server scope filters match
The setup picker's KtxTableListEntry was a 2-level { schema, name }, so
qualifiedTableId always wrote db.name into enabled_tables. When BigQuery,
Snowflake, or SQL Server later ran fast ingest, their introspect step filtered
the scope set with scopedTableNames(scope, { catalog: projectId|database, db })
— catalog was non-null on the introspect side but null in the scope refs, so
every entry was rejected, the live-database adapter staged zero table files,
and detect() failed with 'Adapter "live-database" did not recognize fetched
source output'.
Align the picker boundary with the canonical 3-level KtxTableRef:
- Add catalog: string | null to KtxTableListEntry.
- BigQuery/Snowflake/SQL Server listTables populate catalog from the
resolved projectId / database; Postgres/MySQL/ClickHouse/SQLite set null.
- qualifiedTableId emits catalog.schema.name when catalog is non-null
(resolveEnabledTables already accepts the 3-part shape) and
schemasFromEnabledTables now goes through parseDottedTableEntry so it
recovers the schema correctly from both 2-part and 3-part entries.
- Export parseDottedTableEntry from enabled-tables.ts (@internal) for picker
reuse.
Update listTables expectations in all seven connector tests and the setup /
picker test fixtures. Add a picker regression test that covers the
catalog-bearing round-trip (save + refine).
* fix(cli): allow debug telemetry under opt-out env
2026-05-26 08:49:05 +02:00
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{ database: 'analytics', name: 'event_summary', engine: 'View', comment: '' },
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{ database: 'analytics', name: 'events', engine: 'MergeTree', comment: 'Event stream' },
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2026-05-10 23:12:26 +02:00
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]);
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}
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if (input.query.includes('FROM system.columns')) {
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return result([
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{ table: 'events', name: 'id', type: 'UInt64', comment: 'PK', is_in_primary_key: 1 },
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{ table: 'events', name: 'event_name', type: 'LowCardinality(String)', comment: '', is_in_primary_key: 0 },
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{ table: 'event_summary', name: 'event_name', type: 'String', comment: '', is_in_primary_key: 0 },
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]);
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}
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2026-05-22 14:22:11 +02:00
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if (input.query.includes('FROM system.parts') && input.query.includes('GROUP BY')) {
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2026-05-10 23:12:26 +02:00
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return result([{ table: 'events', row_count: '2' }]);
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}
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if (input.query.includes('SELECT `id`, `event_name` FROM `analytics`.`events` LIMIT 1')) {
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return result({
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meta: [
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{ name: 'id', type: 'UInt64' },
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{ name: 'event_name', type: 'String' },
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],
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data: [[10, 'signup']],
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rows: 1,
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});
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}
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if (input.query.includes('SELECT `event_name` FROM `analytics`.`events`')) {
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return result({
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meta: [{ name: 'event_name', type: 'String' }],
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data: [['signup'], ['purchase']],
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rows: 2,
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});
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}
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if (input.query.includes('COUNT(DISTINCT val)')) {
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return result({
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meta: [{ name: 'cardinality', type: 'UInt64' }],
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data: [[2]],
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rows: 1,
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});
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}
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if (input.query.includes('SELECT DISTINCT toString(`event_name`) AS val')) {
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return result({
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meta: [{ name: 'val', type: 'String' }],
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data: [['purchase'], ['signup']],
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rows: 2,
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});
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}
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if (input.query.includes('sum(rows) AS count')) {
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return result({
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meta: [{ name: 'count', type: 'UInt64' }],
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data: [[2]],
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rows: 1,
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});
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}
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if (input.query.includes('FROM system.databases')) {
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return result([{ name: 'analytics' }, { name: 'warehouse' }]);
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}
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if (input.query.trim() === 'SELECT 1') {
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return result({ meta: [{ name: '1', type: 'UInt8' }], data: [[1]], rows: 1 });
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}
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2026-05-10 23:51:24 +02:00
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if (input.query.includes('select * from (select id, event_name from analytics.events) as ktx_query_result limit 1')) {
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2026-05-10 23:12:26 +02:00
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return result({
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meta: [
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{ name: 'id', type: 'UInt64' },
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{ name: 'event_name', type: 'String' },
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],
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data: [[10, 'signup']],
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rows: 1,
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});
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}
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throw new Error(`Unexpected SQL: ${input.query}`);
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});
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const close = vi.fn(async () => undefined);
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return {
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createClient: vi.fn(() => ({ query, close })),
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};
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}
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2026-05-22 14:22:11 +02:00
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function multiDatabaseClickHouseClientFactory(): KtxClickHouseClientFactory {
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const query = vi.fn(async (input: { query: string; format: string; query_params?: Record<string, unknown> }) => {
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if (input.query.includes('FROM system.tables')) {
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expect(input.query_params).toEqual({ databases: ['analytics', 'mart'] });
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return result([
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{ database: 'analytics', name: 'events', engine: 'MergeTree', comment: 'Event stream' },
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{ database: 'mart', name: 'order_events', engine: 'MergeTree', comment: '' },
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]);
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}
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if (input.query.includes('FROM system.columns')) {
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expect(input.query_params).toEqual({ databases: ['analytics', 'mart'] });
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return result([
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{
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database: 'analytics',
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table: 'events',
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name: 'id',
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type: 'UInt64',
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comment: '',
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is_in_primary_key: 1,
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},
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{
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database: 'mart',
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table: 'order_events',
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name: 'id',
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type: 'UInt64',
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comment: '',
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is_in_primary_key: 1,
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},
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]);
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}
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if (input.query.includes('FROM system.parts') && input.query.includes('GROUP BY')) {
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expect(input.query_params).toEqual({ databases: ['analytics', 'mart'] });
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return result([
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{ database: 'analytics', table: 'events', row_count: '2' },
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{ database: 'mart', table: 'order_events', row_count: '5' },
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]);
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}
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throw new Error(`Unexpected SQL: ${input.query}`);
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});
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return {
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createClient: vi.fn(() => ({ query, close: vi.fn(async () => undefined) })),
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};
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}
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2026-05-10 23:51:24 +02:00
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describe('KtxClickHouseScanConnector', () => {
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test: split cli tests from source tree (#216)
* feat(cli): define full warehouse dialect contract
* test(cli): keep dialect edge tests focused
* fix(cli): stabilize dialect contract foundation
* refactor(connectors): own read-only query preparation
* refactor(connectors): resolve dialects through registry
* refactor(connectors): keep concrete dialect classes internal
* chore(workspace): enforce dialect import boundary
* refactor(cli): resolve relationship dialect at scan boundary
* refactor(cli): use dialect display parsing for entity details
* refactor(cli): use dialect display parsing for warehouse catalog
* refactor(cli): use dialect SQL in relationship workflows
* test(cli): verify solid dialect scan workflow closure
* test: split cli tests from source tree
* refactor(cli): standardize BigQuery scope listing
* feat(sqlite): implement connector scope listing
* test(connectors): cover required table listing
* feat(cli): add warehouse driver registry
* refactor(setup): route scope discovery through driver registry
* refactor(cli): route local query execution through driver registry
* refactor(historic-sql): route dialect support through driver registry
* refactor(cli): test warehouse connections through driver registry
* fix(cli): close driver registry type export gaps
* Improve setup daemon diagnostics
* refactor(setup): centralize rail-prefixed diagnostics + query-history fallback
Extract errorMessage, writePrefixedLines, and flushPrefixedBufferedCommandOutput
into clack.ts so the setup wizard, managed daemons, and embedding/agent steps
share one rail-formatted writer. setup-databases.ts also adds a
"disable query history and retry" option when the schema-context build fails
and query history is the likely culprit, surfaced via a new
failed-query-history-unavailable status.
* fix(cli): carry catalog through the picker so BigQuery/Snowflake/SQL Server scope filters match
The setup picker's KtxTableListEntry was a 2-level { schema, name }, so
qualifiedTableId always wrote db.name into enabled_tables. When BigQuery,
Snowflake, or SQL Server later ran fast ingest, their introspect step filtered
the scope set with scopedTableNames(scope, { catalog: projectId|database, db })
— catalog was non-null on the introspect side but null in the scope refs, so
every entry was rejected, the live-database adapter staged zero table files,
and detect() failed with 'Adapter "live-database" did not recognize fetched
source output'.
Align the picker boundary with the canonical 3-level KtxTableRef:
- Add catalog: string | null to KtxTableListEntry.
- BigQuery/Snowflake/SQL Server listTables populate catalog from the
resolved projectId / database; Postgres/MySQL/ClickHouse/SQLite set null.
- qualifiedTableId emits catalog.schema.name when catalog is non-null
(resolveEnabledTables already accepts the 3-part shape) and
schemasFromEnabledTables now goes through parseDottedTableEntry so it
recovers the schema correctly from both 2-part and 3-part entries.
- Export parseDottedTableEntry from enabled-tables.ts (@internal) for picker
reuse.
Update listTables expectations in all seven connector tests and the setup /
picker test fixtures. Add a picker regression test that covers the
catalog-bearing round-trip (save + refine).
* fix(cli): allow debug telemetry under opt-out env
2026-05-26 08:49:05 +02:00
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it('prepares read-only SQL parameters with ClickHouse typed placeholders', () => {
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expect(
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prepareClickHouseReadOnlyQuery('select * from events where id = :id and event_name = :name', {
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id: 10,
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name: 'signup',
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}),
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).toEqual({
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sql: 'select * from events where id = {id:Int64} and event_name = {name:String}',
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params: { id: 10, name: 'signup' },
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});
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expect(
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prepareClickHouseReadOnlyQuery('select * from events where enabled = :enabled and ratio = :ratio and created_at = :created_at', {
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enabled: true,
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ratio: 1.5,
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created_at: new Date('2026-05-25T00:00:00.000Z'),
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}),
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).toEqual({
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sql: 'select * from events where enabled = {enabled:Bool} and ratio = {ratio:Float64} and created_at = {created_at:DateTime}',
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params: {
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enabled: true,
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ratio: 1.5,
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created_at: new Date('2026-05-25T00:00:00.000Z'),
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},
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});
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expect(prepareClickHouseReadOnlyQuery('select 1')).toEqual({ sql: 'select 1', params: undefined });
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});
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2026-05-10 23:12:26 +02:00
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it('resolves ClickHouse connection configuration safely', () => {
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2026-05-10 23:51:24 +02:00
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expect(isKtxClickHouseConnectionConfig({ driver: 'clickhouse', host: 'localhost', database: 'analytics' })).toBe(
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2026-05-10 23:12:26 +02:00
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true,
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);
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2026-05-10 23:51:24 +02:00
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expect(isKtxClickHouseConnectionConfig({ driver: 'mysql', host: 'localhost', database: 'analytics' })).toBe(false);
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2026-05-10 23:12:26 +02:00
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expect(
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clickHouseClientConfigFromConfig({
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connectionId: 'warehouse',
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connection: {
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driver: 'clickhouse',
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host: 'ch.example.test',
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port: 9440,
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database: 'analytics',
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username: 'reader',
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password: 'test-pass', // pragma: allowlist secret
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ssl: true,
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},
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}),
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).toMatchObject({
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host: 'ch.example.test',
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port: 9440,
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database: 'analytics',
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username: 'reader',
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password: 'test-pass', // pragma: allowlist secret
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ssl: true,
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});
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});
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it('introspects schema, primary keys, comments, row counts, and views', async () => {
|
2026-05-10 23:51:24 +02:00
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const connector = new KtxClickHouseScanConnector({
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2026-05-10 23:12:26 +02:00
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connectionId: 'warehouse',
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connection: {
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driver: 'clickhouse',
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host: 'ch.example.test',
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database: 'analytics',
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username: 'reader',
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password: 'test-pass', // pragma: allowlist secret
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},
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clientFactory: fakeClientFactory(),
|
|
|
|
|
now: () => new Date('2026-04-29T14:00:00.000Z'),
|
|
|
|
|
});
|
|
|
|
|
|
|
|
|
|
const snapshot = await connector.introspect(
|
|
|
|
|
{ connectionId: 'warehouse', driver: 'clickhouse' },
|
|
|
|
|
{ runId: 'scan-run-1' },
|
|
|
|
|
);
|
|
|
|
|
|
|
|
|
|
expect(snapshot).toMatchObject({
|
|
|
|
|
connectionId: 'warehouse',
|
|
|
|
|
driver: 'clickhouse',
|
|
|
|
|
extractedAt: '2026-04-29T14:00:00.000Z',
|
|
|
|
|
scope: { schemas: ['analytics'] },
|
|
|
|
|
metadata: {
|
|
|
|
|
database: 'analytics',
|
|
|
|
|
host: 'ch.example.test',
|
|
|
|
|
table_count: 2,
|
|
|
|
|
total_columns: 3,
|
|
|
|
|
},
|
|
|
|
|
});
|
|
|
|
|
expect(snapshot.tables.map((table) => [table.name, table.kind, table.estimatedRows, table.comment])).toEqual([
|
|
|
|
|
['event_summary', 'view', null, null],
|
test: split cli tests from source tree (#216)
* feat(cli): define full warehouse dialect contract
* test(cli): keep dialect edge tests focused
* fix(cli): stabilize dialect contract foundation
* refactor(connectors): own read-only query preparation
* refactor(connectors): resolve dialects through registry
* refactor(connectors): keep concrete dialect classes internal
* chore(workspace): enforce dialect import boundary
* refactor(cli): resolve relationship dialect at scan boundary
* refactor(cli): use dialect display parsing for entity details
* refactor(cli): use dialect display parsing for warehouse catalog
* refactor(cli): use dialect SQL in relationship workflows
* test(cli): verify solid dialect scan workflow closure
* test: split cli tests from source tree
* refactor(cli): standardize BigQuery scope listing
* feat(sqlite): implement connector scope listing
* test(connectors): cover required table listing
* feat(cli): add warehouse driver registry
* refactor(setup): route scope discovery through driver registry
* refactor(cli): route local query execution through driver registry
* refactor(historic-sql): route dialect support through driver registry
* refactor(cli): test warehouse connections through driver registry
* fix(cli): close driver registry type export gaps
* Improve setup daemon diagnostics
* refactor(setup): centralize rail-prefixed diagnostics + query-history fallback
Extract errorMessage, writePrefixedLines, and flushPrefixedBufferedCommandOutput
into clack.ts so the setup wizard, managed daemons, and embedding/agent steps
share one rail-formatted writer. setup-databases.ts also adds a
"disable query history and retry" option when the schema-context build fails
and query history is the likely culprit, surfaced via a new
failed-query-history-unavailable status.
* fix(cli): carry catalog through the picker so BigQuery/Snowflake/SQL Server scope filters match
The setup picker's KtxTableListEntry was a 2-level { schema, name }, so
qualifiedTableId always wrote db.name into enabled_tables. When BigQuery,
Snowflake, or SQL Server later ran fast ingest, their introspect step filtered
the scope set with scopedTableNames(scope, { catalog: projectId|database, db })
— catalog was non-null on the introspect side but null in the scope refs, so
every entry was rejected, the live-database adapter staged zero table files,
and detect() failed with 'Adapter "live-database" did not recognize fetched
source output'.
Align the picker boundary with the canonical 3-level KtxTableRef:
- Add catalog: string | null to KtxTableListEntry.
- BigQuery/Snowflake/SQL Server listTables populate catalog from the
resolved projectId / database; Postgres/MySQL/ClickHouse/SQLite set null.
- qualifiedTableId emits catalog.schema.name when catalog is non-null
(resolveEnabledTables already accepts the 3-part shape) and
schemasFromEnabledTables now goes through parseDottedTableEntry so it
recovers the schema correctly from both 2-part and 3-part entries.
- Export parseDottedTableEntry from enabled-tables.ts (@internal) for picker
reuse.
Update listTables expectations in all seven connector tests and the setup /
picker test fixtures. Add a picker regression test that covers the
catalog-bearing round-trip (save + refine).
* fix(cli): allow debug telemetry under opt-out env
2026-05-26 08:49:05 +02:00
|
|
|
['events', 'table', 2, 'Event stream'],
|
2026-05-10 23:12:26 +02:00
|
|
|
]);
|
|
|
|
|
expect(snapshot.tables.find((table) => table.name === 'events')?.columns[0]).toMatchObject({
|
|
|
|
|
name: 'id',
|
|
|
|
|
nativeType: 'UInt64',
|
|
|
|
|
normalizedType: 'UInt64',
|
|
|
|
|
dimensionType: 'number',
|
|
|
|
|
nullable: false,
|
|
|
|
|
primaryKey: true,
|
|
|
|
|
comment: 'PK',
|
|
|
|
|
});
|
|
|
|
|
expect(snapshot.tables.find((table) => table.name === 'events')?.foreignKeys).toEqual([]);
|
|
|
|
|
});
|
|
|
|
|
|
2026-05-22 14:22:11 +02:00
|
|
|
it('introspects every configured ClickHouse database scope while preserving the default database', async () => {
|
|
|
|
|
const connector = new KtxClickHouseScanConnector({
|
|
|
|
|
connectionId: 'warehouse',
|
|
|
|
|
connection: {
|
|
|
|
|
driver: 'clickhouse',
|
|
|
|
|
host: 'ch.example.test',
|
|
|
|
|
database: 'analytics',
|
|
|
|
|
databases: ['analytics', 'mart'],
|
|
|
|
|
username: 'reader',
|
|
|
|
|
password: 'test-pass', // pragma: allowlist secret
|
|
|
|
|
},
|
|
|
|
|
clientFactory: multiDatabaseClickHouseClientFactory(),
|
|
|
|
|
now: () => new Date('2026-05-21T10:00:00.000Z'),
|
|
|
|
|
});
|
|
|
|
|
|
|
|
|
|
const snapshot = await connector.introspect(
|
|
|
|
|
{ connectionId: 'warehouse', driver: 'clickhouse' },
|
|
|
|
|
{ runId: 'scan-run-1' },
|
|
|
|
|
);
|
|
|
|
|
|
|
|
|
|
expect(snapshot.scope).toEqual({ schemas: ['analytics', 'mart'] });
|
|
|
|
|
expect(snapshot.metadata).toMatchObject({ database: 'analytics', databases: ['analytics', 'mart'] });
|
|
|
|
|
expect(snapshot.tables.map((table) => `${table.db}.${table.name}`)).toEqual([
|
|
|
|
|
'analytics.events',
|
|
|
|
|
'mart.order_events',
|
|
|
|
|
]);
|
|
|
|
|
});
|
|
|
|
|
|
fix(snowflake): unblock multi-schema ingest and relationship discovery (#204)
* feat(setup): drop redundant Snowflake schema prompt; fall back to free-text on listSchemas failure
Snowflake setup previously asked for a single schema as free text, then
ran a multiselect against the discovered schemas — two schema questions
back-to-back, with the first being only a session bootstrap. The SDK's
`schema` is optional, so the bootstrap step is unnecessary.
- Remove the free-text Snowflake schema prompt; only pass `schema` to
snowflake-sdk when one is configured.
- When `listSchemas()` fails (e.g. role lacks SHOW SCHEMAS), prompt the
user for a comma-separated list, persist it as `schema_names`, and use
it as both the table-list filter and the multiselect default. Applies
to every driver with a scope-discovery spec, not just Snowflake.
- Update docs to lead with `schema_names`; keep `schema_name` as a
documented single-schema shorthand.
* fix(snowflake): keep introspecting when primary-key discovery is denied
The PK query joins INFORMATION_SCHEMA.TABLE_CONSTRAINTS and
INFORMATION_SCHEMA.KEY_COLUMN_USAGE, which require grants the
connection role may not have. Previously a 'SQL compilation error:
Object ANALYTICS.INFORMATION_SCHEMA.KEY_COLUMN_USAGE does not exist
or not authorized' aborted the entire introspect — schemas, columns,
and row counts were all discarded over a missing nice-to-have.
Wrap the constraint query in try/catch, log a one-line warning per
schema, and return an empty PK map. Columns end up with
primaryKey=false; relationship inference still has FK and profiling
to fall back on.
* fix(scan): unblock relationship discovery on Snowflake
Two adjacent bugs prevented the scan's relationship pipeline from producing
any joins on a Snowflake warehouse:
- relationship-profiling.ts fell through to a default `GROUP_CONCAT` branch
for unknown drivers. Snowflake has no GROUP_CONCAT, so every per-table
profile query failed with "Unknown function GROUP_CONCAT". Add an explicit
Snowflake branch that uses LISTAGG with a literal '\x1f' delimiter
(Snowflake requires the delimiter to be a constant, so CHR(31) is rejected).
- description-generation.ts destructured `connector.sampleTable` and
`connector.sampleColumn` into bare locals, losing the `this` binding when
the class-method connectors (Snowflake, Postgres, MySQL) were invoked.
Every sample call threw "Cannot read properties of undefined (reading
'assertConnection')" and degraded LLM descriptions to metadata-only
prompts. Call the methods through the connector instead.
Without these, even after the primary-key probe is allowed to fail softly,
the scan ends up with 0 validated relationships and an empty `joins:` block
in every shard YAML.
* test(scan): cover table-ref helpers
* feat(scan): plumb tableScope through live-database introspection port
* feat(scan): apply tableScope during metadata fetch
* feat(scan): enforce table scope at fetch boundary
* feat(scan): pool Snowflake sessions and batch enrichment for faster ingest (#206)
* feat(cli): add RSA key-pair auth option to Snowflake setup wizard
Extends the interactive Snowflake setup flow with an authentication-method
prompt (password vs RSA/JWT key-pair). The RSA branch collects a private-key
path (env/file/absolute) and an optional passphrase; the resulting connection
config records `authMethod: 'rsa'` with `privateKey` and `passphrase` instead
of `password`.
* feat(scan): pool Snowflake sessions
* fix(scan): reuse structural snapshots and cleanup connectors
* feat(scan): parallelize relationship profiling
* feat(scan): batch table description generation
* docs: document Snowflake ingest concurrency knobs
* fix(scan): close Snowflake ingest perf verification gaps
* fix(scan): keep batched description failure bounded
* feat(scan): dispatch query-history probes by connection driver
Extract historic-sql dialect resolution into a shared helper so the
status-project readiness check and the local ingest factory agree on
which connections enable query history and which probe to run. The
status command now picks the postgres/snowflake/bigquery probe based on
the connection's driver instead of always reporting against postgres,
which previously caused snowflake connections with queryHistory.enabled
to surface a misleading "driver is snowflake" failure.
Also drops a noisy console.warn from Snowflake primary-key discovery —
INFORMATION_SCHEMA.KEY_COLUMN_USAGE is commonly ungranted for read-only
roles and the FK + profiling paths handle the empty PK map already.
* fix(llm): allow StructuredOutput tool and raise maxTurns for generateObject
The Claude Code agent SDK announces an internal pseudo-tool named
StructuredOutput in the system/init message whenever outputFormat is set
to { type: 'json_schema' }. The runtime's isolation check built its
allowedToolIds set only from MCP tool ids and treated StructuredOutput
as an unexpected host-injected tool, so every generateObject call threw
"Claude Code runtime isolation failed: tools=StructuredOutput ..." and
the table-descriptions and relationship-LLM-proposal enrichment stages
recorded null output across the board.
Whitelist StructuredOutput specifically in generateObject's
allowedToolIds — the check also enforces missing_tools symmetry, so
generateText and runAgentLoop, which do not see StructuredOutput, must
not require it.
generateObject also ran with maxTurns: 1, which the model intermittently
breached when it emitted thinking text before the structured response.
Raised to 5 to give the schema-bound call enough headroom without
allowing unbounded loops. The existing tests now exercise the path with
an init message that announces StructuredOutput so the regression cannot
slip back in.
* chore(scripts): add ktx-reset.sh project-cleanup helper
Convenience script for repeatable ingest testing: takes a project
directory and prunes everything except ktx.yaml and .ktx/secrets/, so
the next ktx setup or ktx ingest run starts from a known-clean state.
2026-05-23 10:41:30 +02:00
|
|
|
it('limits introspection to tables in tableScope', async () => {
|
|
|
|
|
const queries: Array<{ query: string; query_params?: Record<string, unknown> }> = [];
|
|
|
|
|
const clientFactory: KtxClickHouseClientFactory = {
|
|
|
|
|
createClient: vi.fn(() => ({
|
|
|
|
|
query: vi.fn(async (input: { query: string; format: string; query_params?: Record<string, unknown> }) => {
|
|
|
|
|
queries.push({ query: input.query, query_params: input.query_params });
|
|
|
|
|
if (input.query.includes('FROM system.tables')) {
|
|
|
|
|
return result([{ database: 'analytics', name: 'events', engine: 'MergeTree', comment: '' }]);
|
|
|
|
|
}
|
|
|
|
|
if (input.query.includes('FROM system.columns')) {
|
|
|
|
|
return result([
|
|
|
|
|
{
|
|
|
|
|
database: 'analytics',
|
|
|
|
|
table: 'events',
|
|
|
|
|
name: 'id',
|
|
|
|
|
type: 'UInt64',
|
|
|
|
|
comment: '',
|
|
|
|
|
is_in_primary_key: 1,
|
|
|
|
|
},
|
|
|
|
|
]);
|
|
|
|
|
}
|
|
|
|
|
if (input.query.includes('FROM system.parts')) {
|
|
|
|
|
return result([{ database: 'analytics', table: 'events', row_count: '2' }]);
|
|
|
|
|
}
|
|
|
|
|
throw new Error(`Unexpected SQL: ${input.query}`);
|
|
|
|
|
}),
|
|
|
|
|
close: vi.fn(async () => undefined),
|
|
|
|
|
})),
|
|
|
|
|
};
|
|
|
|
|
const connector = new KtxClickHouseScanConnector({
|
|
|
|
|
connectionId: 'warehouse',
|
|
|
|
|
connection: {
|
|
|
|
|
driver: 'clickhouse',
|
|
|
|
|
host: 'ch.example.test',
|
|
|
|
|
database: 'analytics',
|
|
|
|
|
username: 'reader',
|
|
|
|
|
password: 'test-pass', // pragma: allowlist secret
|
|
|
|
|
},
|
|
|
|
|
clientFactory,
|
|
|
|
|
});
|
|
|
|
|
const scope = tableRefSet([{ catalog: null, db: 'analytics', name: 'events' }]);
|
|
|
|
|
const snapshot = await connector.introspect(
|
|
|
|
|
{ connectionId: 'warehouse', driver: 'clickhouse', tableScope: scope },
|
|
|
|
|
{ runId: 'scope-test' },
|
|
|
|
|
);
|
|
|
|
|
expect(snapshot.tables.map((table) => table.name)).toEqual(['events']);
|
|
|
|
|
const tablesQuery = queries.find((query) => query.query.includes('FROM system.tables'));
|
|
|
|
|
expect(tablesQuery?.query).toContain('AND name IN {table_names:Array(String)}');
|
|
|
|
|
expect(tablesQuery?.query_params).toEqual({ databases: ['analytics'], table_names: ['events'] });
|
|
|
|
|
});
|
|
|
|
|
|
2026-05-10 23:12:26 +02:00
|
|
|
it('runs samples, distinct values, read-only SQL, row count, schema list, and cleanup', async () => {
|
|
|
|
|
const clientFactory = fakeClientFactory();
|
2026-05-10 23:51:24 +02:00
|
|
|
const connector = new KtxClickHouseScanConnector({
|
2026-05-10 23:12:26 +02:00
|
|
|
connectionId: 'warehouse',
|
|
|
|
|
connection: {
|
|
|
|
|
driver: 'clickhouse',
|
|
|
|
|
host: 'ch.example.test',
|
|
|
|
|
database: 'analytics',
|
|
|
|
|
username: 'reader',
|
|
|
|
|
password: 'test-pass', // pragma: allowlist secret
|
|
|
|
|
},
|
|
|
|
|
clientFactory,
|
|
|
|
|
});
|
|
|
|
|
|
|
|
|
|
await expect(
|
|
|
|
|
connector.sampleTable(
|
|
|
|
|
{
|
|
|
|
|
connectionId: 'warehouse',
|
|
|
|
|
table: { catalog: null, db: 'analytics', name: 'events' },
|
|
|
|
|
columns: ['id', 'event_name'],
|
|
|
|
|
limit: 1,
|
|
|
|
|
},
|
|
|
|
|
{ runId: 'scan-run-1' },
|
|
|
|
|
),
|
|
|
|
|
).resolves.toEqual({ headers: ['id', 'event_name'], rows: [[10, 'signup']], totalRows: 1 });
|
|
|
|
|
|
|
|
|
|
await expect(
|
|
|
|
|
connector.sampleColumn(
|
|
|
|
|
{ connectionId: 'warehouse', table: { catalog: null, db: 'analytics', name: 'events' }, column: 'event_name', limit: 5 },
|
|
|
|
|
{ runId: 'scan-run-1' },
|
|
|
|
|
),
|
|
|
|
|
).resolves.toMatchObject({ values: ['signup', 'purchase'], nullCount: null, distinctCount: null });
|
|
|
|
|
|
|
|
|
|
await expect(
|
|
|
|
|
connector.getColumnDistinctValues(
|
|
|
|
|
{ catalog: null, db: 'analytics', name: 'events' },
|
|
|
|
|
'event_name',
|
|
|
|
|
{ maxCardinality: 5, limit: 10, sampleSize: 100 },
|
|
|
|
|
),
|
|
|
|
|
).resolves.toEqual({ values: ['purchase', 'signup'], cardinality: 2 });
|
|
|
|
|
|
|
|
|
|
await expect(
|
|
|
|
|
connector.executeReadOnly(
|
|
|
|
|
{ connectionId: 'warehouse', sql: 'select id, event_name from analytics.events', maxRows: 1 },
|
|
|
|
|
{ runId: 'scan-run-1' },
|
|
|
|
|
),
|
|
|
|
|
).resolves.toMatchObject({ headers: ['id', 'event_name'], rows: [[10, 'signup']], totalRows: 1, rowCount: 1 });
|
|
|
|
|
|
|
|
|
|
await expect(
|
|
|
|
|
connector.executeReadOnly({ connectionId: 'warehouse', sql: 'delete from events' }, { runId: 'scan-run-1' }),
|
|
|
|
|
).rejects.toThrow('Only read-only SELECT/WITH queries can be executed locally');
|
|
|
|
|
|
|
|
|
|
await expect(connector.getTableRowCount('events')).resolves.toBe(2);
|
|
|
|
|
await expect(connector.listSchemas()).resolves.toEqual(['analytics', 'warehouse']);
|
test: split cli tests from source tree (#216)
* feat(cli): define full warehouse dialect contract
* test(cli): keep dialect edge tests focused
* fix(cli): stabilize dialect contract foundation
* refactor(connectors): own read-only query preparation
* refactor(connectors): resolve dialects through registry
* refactor(connectors): keep concrete dialect classes internal
* chore(workspace): enforce dialect import boundary
* refactor(cli): resolve relationship dialect at scan boundary
* refactor(cli): use dialect display parsing for entity details
* refactor(cli): use dialect display parsing for warehouse catalog
* refactor(cli): use dialect SQL in relationship workflows
* test(cli): verify solid dialect scan workflow closure
* test: split cli tests from source tree
* refactor(cli): standardize BigQuery scope listing
* feat(sqlite): implement connector scope listing
* test(connectors): cover required table listing
* feat(cli): add warehouse driver registry
* refactor(setup): route scope discovery through driver registry
* refactor(cli): route local query execution through driver registry
* refactor(historic-sql): route dialect support through driver registry
* refactor(cli): test warehouse connections through driver registry
* fix(cli): close driver registry type export gaps
* Improve setup daemon diagnostics
* refactor(setup): centralize rail-prefixed diagnostics + query-history fallback
Extract errorMessage, writePrefixedLines, and flushPrefixedBufferedCommandOutput
into clack.ts so the setup wizard, managed daemons, and embedding/agent steps
share one rail-formatted writer. setup-databases.ts also adds a
"disable query history and retry" option when the schema-context build fails
and query history is the likely culprit, surfaced via a new
failed-query-history-unavailable status.
* fix(cli): carry catalog through the picker so BigQuery/Snowflake/SQL Server scope filters match
The setup picker's KtxTableListEntry was a 2-level { schema, name }, so
qualifiedTableId always wrote db.name into enabled_tables. When BigQuery,
Snowflake, or SQL Server later ran fast ingest, their introspect step filtered
the scope set with scopedTableNames(scope, { catalog: projectId|database, db })
— catalog was non-null on the introspect side but null in the scope refs, so
every entry was rejected, the live-database adapter staged zero table files,
and detect() failed with 'Adapter "live-database" did not recognize fetched
source output'.
Align the picker boundary with the canonical 3-level KtxTableRef:
- Add catalog: string | null to KtxTableListEntry.
- BigQuery/Snowflake/SQL Server listTables populate catalog from the
resolved projectId / database; Postgres/MySQL/ClickHouse/SQLite set null.
- qualifiedTableId emits catalog.schema.name when catalog is non-null
(resolveEnabledTables already accepts the 3-part shape) and
schemasFromEnabledTables now goes through parseDottedTableEntry so it
recovers the schema correctly from both 2-part and 3-part entries.
- Export parseDottedTableEntry from enabled-tables.ts (@internal) for picker
reuse.
Update listTables expectations in all seven connector tests and the setup /
picker test fixtures. Add a picker regression test that covers the
catalog-bearing round-trip (save + refine).
* fix(cli): allow debug telemetry under opt-out env
2026-05-26 08:49:05 +02:00
|
|
|
await expect(connector.listTables(['analytics'])).resolves.toEqual([
|
|
|
|
|
{ catalog: null, schema: 'analytics', name: 'event_summary', kind: 'view' },
|
|
|
|
|
{ catalog: null, schema: 'analytics', name: 'events', kind: 'table' },
|
|
|
|
|
]);
|
2026-05-10 23:12:26 +02:00
|
|
|
await expect(
|
|
|
|
|
connector.columnStats(
|
|
|
|
|
{ connectionId: 'warehouse', table: { catalog: null, db: 'analytics', name: 'events' }, column: 'event_name' },
|
|
|
|
|
{ runId: 'scan-run-1' },
|
|
|
|
|
),
|
|
|
|
|
).resolves.toBeNull();
|
|
|
|
|
|
|
|
|
|
await connector.cleanup();
|
|
|
|
|
});
|
|
|
|
|
|
|
|
|
|
it('adapts native ClickHouse snapshots to live-database introspection for local ingest', async () => {
|
|
|
|
|
const introspection = createClickHouseLiveDatabaseIntrospection({
|
|
|
|
|
connections: {
|
|
|
|
|
warehouse: {
|
|
|
|
|
driver: 'clickhouse',
|
|
|
|
|
host: 'ch.example.test',
|
|
|
|
|
database: 'analytics',
|
|
|
|
|
username: 'reader',
|
|
|
|
|
password: 'test-pass', // pragma: allowlist secret
|
|
|
|
|
},
|
|
|
|
|
},
|
|
|
|
|
clientFactory: fakeClientFactory(),
|
|
|
|
|
now: () => new Date('2026-04-29T14:00:00.000Z'),
|
|
|
|
|
});
|
|
|
|
|
|
|
|
|
|
const snapshot = await introspection.extractSchema('warehouse');
|
|
|
|
|
|
|
|
|
|
expect(snapshot).toMatchObject({
|
|
|
|
|
connectionId: 'warehouse',
|
|
|
|
|
extractedAt: '2026-04-29T14:00:00.000Z',
|
|
|
|
|
});
|
|
|
|
|
expect(snapshot.tables.find((table) => table.name === 'events')).toMatchObject({
|
|
|
|
|
name: 'events',
|
|
|
|
|
catalog: null,
|
|
|
|
|
db: 'analytics',
|
|
|
|
|
columns: [
|
|
|
|
|
{
|
|
|
|
|
name: 'id',
|
|
|
|
|
nativeType: 'UInt64',
|
|
|
|
|
normalizedType: 'UInt64',
|
|
|
|
|
dimensionType: 'number',
|
|
|
|
|
nullable: false,
|
|
|
|
|
primaryKey: true,
|
|
|
|
|
comment: 'PK',
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
name: 'event_name',
|
|
|
|
|
nativeType: 'LowCardinality(String)',
|
|
|
|
|
normalizedType: 'LowCardinality(String)',
|
|
|
|
|
dimensionType: 'string',
|
|
|
|
|
nullable: false,
|
|
|
|
|
primaryKey: false,
|
|
|
|
|
comment: null,
|
|
|
|
|
},
|
|
|
|
|
],
|
|
|
|
|
foreignKeys: [],
|
|
|
|
|
});
|
|
|
|
|
});
|
|
|
|
|
});
|