mirror of
https://github.com/Kaelio/ktx.git
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* refactor(connectors): split KtxDialect into core and KtxSqlDialect Separate the dialect contract into a driver-agnostic core (display/ref formatting and type mapping) and a SQL-only extension (query generators). The catalog and entity-details paths resolve the core dialect for any snapshot driver, so it must stay free of SQL generation; this is the prerequisite refactor for adding non-SQL primary sources. - KtxDialect keeps type, formatDisplayRef, parseDisplayRef, columnDisplayTablePartCount, mapDataType, mapToDimensionType - KtxSqlDialect extends it with quoteIdentifier, formatTableName, and the query/sample/statistics generators; the 7 SQL dialects implement it - add getSqlDialectForDriver for SQL drivers; the 7 connectors and the relationship-benchmark harness consume it - thread the relationship pipeline (profiling/validation/composite/ discovery) as KtxSqlDialect | null so a non-SQL source skips coverage SQL and its candidates stay in review; local-enrichment builds the SQL dialect only when the connector advertises readOnlySql Pure extraction: no behavior change for the existing 7 drivers. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * feat(connectors): add MongoDB connector for issue #305 Add a read-only MongoDB connector that treats a database as a primary context source: collections map to tables and inferred top-level fields to columns. MongoDB is the first non-SQL source (readOnlySql: false), so ktx sql and metric compilation do not apply, but its collections flow through ingest, descriptions, and relationship discovery. - schema-inference: infer a flat column schema from the most recent sample_size documents (by _id desc, or order_by for non-ObjectId keys). Union BSON types per field, mark multi-type fields mixed (string), keep sub-documents/arrays as a single opaque json column, derive nullability from presence, treat _id as the primary key - connector: KtxMongoDbScanConnector behind an injectable client seam; strictly read-only (find/listCollections/estimatedDocumentCount only), no executeReadOnly; resolves env:/file: via resolveKtxConfigReference - core-only KtxMongoDbDialect and a live-database introspection adapter - wire the mongodb driver: driver union, dialect registry, driver registration (scopeConfigKey databases), mongodbConnectionSchema, connection-drivers, normalizeDriver, the live-database route, and the ktx setup picker. ktx sql is refused by the read-only SQL capability gate - tests: schema inference, connector snapshot via a fake client, dialect, driver-schema parsing, and the ktx sql rejection Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * docs(integrations): document the MongoDB primary source Add a MongoDB section to the primary-sources reference: connection config (url, databases, enabled_tables, sample_size, order_by), mongodb+srv/TLS/ Atlas notes, the schema-inference explainer, a features matrix, and the non-SQL caveat. Update the frontmatter and connection field reference. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * fix(connectors): address review blockers on the MongoDB connector - introspect: skip estimatedDocumentCount for views. The count command is rejected on a MongoDB view (CommandNotSupportedOnView), so counting a view aborted introspect for the whole connection; compute estimatedRows only for real collections, as ClickHouse does. - sl: refuse a semantic-layer query against a non-SQL connection instead of defaulting it to the Postgres dialect. compileLocalSlQuery (the shared CLI + MCP path) now rejects a driver with no SQL dialect via the new isSqlQueryableDriver authority, keeping MongoDB context-only per issue #305. - tests: cover input.tableScope and the empty-scope skip for the Mongo connector (the scan layer does not post-filter), the view no-count path, and the ktx sl query refusal for a mongodb connection. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * polish(mongodb): compute sampled nullCount and document sampling caveats Address the non-blocking review notes: - sampleColumn now counts null/absent values over the sampled window instead of returning nullCount: null, since the documents are already in hand - warn that a custom order_by must be indexed (an unindexed sort hits MongoDB's in-memory sort limit on large collections) in the connection schema and docs - note that sampled values for nested fields are stringified, not faithfully serialized, so the json opacity is deliberate Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * docs(examples): add a MongoDB connector example A manual, container-backed example mirroring examples/postgres-historic: - docker-compose.yml + init/seed.js seed a representative dataset (nested documents, arrays, a Decimal128, a mixed-type field, a nullable field, an ObjectId reference, and a view) on first container start - scripts/smoke.sh + introspect-smoke.mjs assert the connector's inferred schema with no LLM credentials — the same introspection entry point ktx ingest's database-schema stage uses, including the view-no-count path - README.md documents the smoke and a full keyless ktx ingest run (claude-code LLM + managed sentence-transformers embeddings) Works with Docker Compose or podman compose. Verified end to end. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * chore: ignore examples/** in knip to fix dead-code false positives The MongoDB connector example files (examples/mongodb/init/seed.js and examples/mongodb/scripts/introspect-smoke.mjs) are used at runtime but were flagged as unused by knip. Add examples/** to the ignore array, matching the existing .context/** entry. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_0114qQV8fJ5a5ME3XbMVRzbL * fix(mongodb): refuse non-SQL connections before SQL analysis `ktx sql` and the MCP sql_execution tool resolved a SQL-analysis dialect (falling back to Postgres for a non-SQL driver) and ran read-only validation before the connector capability gate refused the connection. For a MongoDB connection that spun up the parser/daemon and produced Postgres parser diagnostics instead of a clean non-SQL refusal. Route both entry points through a shared assertSqlQueryableConnection guard before dialect selection, mirroring compileLocalSlQuery. The federated duckdb path has no driver and is exempted at each call site. Add CLI and MCP regression tests asserting validation/connector work never starts for a MongoDB connection. * fix(mongodb): pass CI gates (dialect boundary, secrets, setup test) Three latent failures in the connector surfaced once CI ran on the branch: - connector.ts imported the concrete KtxMongoDbDialect, which the connector dialect-import boundary forbids. Route it through getDialectForDriver('mongodb') and widen inferKtxMongoCollectionColumns to the base KtxDialect (it only uses mapDataType/mapToDimensionType). - detect-secrets flagged a test ObjectId hex and the mongodb+srv example URL; annotate both with allowlist pragmas. - the "shows every supported database" setup test omitted the new MongoDB option. --------- Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Co-authored-by: Luca Martial <48870843+luca-martial@users.noreply.github.com> Co-authored-by: Luca Martial <lucamrtl@gmail.com> Co-authored-by: Andrey Avtomonov <andreybavt@gmail.com>
359 lines
10 KiB
TypeScript
359 lines
10 KiB
TypeScript
import { mkdtemp, rm } from 'node:fs/promises';
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import { tmpdir } from 'node:os';
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import { join } from 'node:path';
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import { afterEach, beforeEach, describe, expect, it, vi } from 'vitest';
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import type { KtxSemanticLayerComputePort } from '../../../src/context/daemon/semantic-layer-compute.js';
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import { initKtxProject, type KtxLocalProject } from '../../../src/context/project/project.js';
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import { compileLocalSlQuery } from '../../../src/context/sl/local-query.js';
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describe('compileLocalSlQuery', () => {
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let tempDir: string;
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let project: KtxLocalProject;
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let compute: KtxSemanticLayerComputePort;
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beforeEach(async () => {
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tempDir = await mkdtemp(join(tmpdir(), 'ktx-local-query-'));
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project = await initKtxProject({ projectDir: join(tempDir, 'project') });
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project.config.connections.warehouse = { driver: 'postgres' };
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await project.fileStore.writeFile(
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'semantic-layer/warehouse/orders.yaml',
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`name: orders
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table: public.orders
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grain:
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- id
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columns:
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- name: id
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type: number
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- name: status
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type: string
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measures:
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- name: order_count
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expr: count(*)
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joins: []
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`,
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'ktx',
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'ktx@example.com',
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'Add orders source',
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);
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await project.fileStore.writeFile(
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'semantic-layer/warehouse/orders_overlay.yaml',
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`name: orders_overlay
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inherits_columns_from: orders
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columns:
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- name: paid_at
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type: timestamp
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joins: []
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measures: []
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grain: []
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`,
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'ktx',
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'ktx@example.com',
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'Add overlay source',
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);
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compute = {
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query: vi.fn(async (input) => ({
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sql: 'select status, count(*) as order_count from public.orders group by status',
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dialect: input.dialect,
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columns: [{ name: 'orders.status' }, { name: 'orders.order_count' }],
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plan: { measures: input.query.measures, dimensions: input.query.dimensions },
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})),
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validateSources: vi.fn(),
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generateSources: vi.fn(),
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};
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});
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afterEach(async () => {
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await rm(tempDir, { recursive: true, force: true });
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});
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it('refuses a non-SQL (context-only) connection instead of compiling it as Postgres', async () => {
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project.config.connections['mongo-prod'] = { driver: 'mongodb', url: 'mongodb://localhost:27017/app' };
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await expect(
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compileLocalSlQuery(project, {
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connectionId: 'mongo-prod',
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query: { measures: ['orders.order_count'], dimensions: ['orders.status'], limit: 25 },
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compute,
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}),
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).rejects.toThrow(/non-SQL driver 'mongodb'|require a SQL warehouse connection/);
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expect(compute.query).not.toHaveBeenCalled();
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});
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it('compiles a local semantic-layer query with computable sources only', async () => {
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const result = await compileLocalSlQuery(project, {
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connectionId: 'warehouse',
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query: {
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measures: ['orders.order_count'],
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dimensions: ['orders.status'],
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limit: 25,
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},
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compute,
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});
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expect(compute.query).toHaveBeenCalledWith({
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sources: [
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{
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name: 'orders',
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table: 'public.orders',
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grain: ['id'],
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columns: [
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{ name: 'id', type: 'number' },
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{ name: 'status', type: 'string' },
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],
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measures: [{ name: 'order_count', expr: 'count(*)' }],
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joins: [],
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},
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],
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dialect: 'postgres',
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query: {
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measures: ['orders.order_count'],
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dimensions: ['orders.status'],
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limit: 25,
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},
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});
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expect(result).toEqual({
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connectionId: 'warehouse',
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dialect: 'postgres',
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sql: 'select status, count(*) as order_count from public.orders group by status',
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headers: ['orders.status', 'orders.order_count'],
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rows: [],
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totalRows: 0,
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plan: {
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measures: ['orders.order_count'],
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dimensions: ['orders.status'],
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execution: {
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mode: 'compile_only',
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reason: 'Local semantic-layer query compiled SQL but no data-source execution adapter is configured.',
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},
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},
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});
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});
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it('compiles a local semantic-layer query from manifest-backed scan sources', async () => {
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await project.fileStore.writeFile(
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'semantic-layer/warehouse/_schema/public.yaml',
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`tables:
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payments:
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table: public.payments
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columns:
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- name: payment_id
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type: number
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pk: true
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- name: amount
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type: number
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`,
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'ktx',
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'ktx@example.com',
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'Add manifest shard',
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);
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await compileLocalSlQuery(project, {
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connectionId: 'warehouse',
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query: {
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measures: ['sum(payments.amount)'],
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dimensions: [],
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},
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compute,
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});
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expect(compute.query).toHaveBeenLastCalledWith({
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sources: expect.arrayContaining([
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{
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name: 'payments',
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table: 'public.payments',
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grain: ['payment_id'],
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columns: [
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{
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name: 'payment_id',
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type: 'number',
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role: undefined,
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descriptions: undefined,
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constraints: undefined,
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enum_values: undefined,
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tests: undefined,
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},
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{
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name: 'amount',
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type: 'number',
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role: undefined,
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descriptions: undefined,
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constraints: undefined,
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enum_values: undefined,
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tests: undefined,
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},
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],
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joins: [],
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measures: [],
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},
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]),
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dialect: 'postgres',
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query: {
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measures: ['sum(payments.amount)'],
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dimensions: [],
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},
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});
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});
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it('strips authoring-only fields (usage, inherits_columns_from) before sending sources to the daemon', async () => {
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await project.fileStore.writeFile(
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'semantic-layer/warehouse/_schema/public.yaml',
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`tables:
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invoices:
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table: public.invoices
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columns:
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- name: invoice_id
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type: number
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pk: true
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- name: amount
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type: number
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usage:
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narrative: Activation policy windows table for invoice analytics.
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frequencyTier: mid
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commonFilters:
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- amount
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commonGroupBys: []
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commonJoins: []
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staleSince: null
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`,
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'ktx',
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'ktx@example.com',
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'Add manifest shard with usage',
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);
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await compileLocalSlQuery(project, {
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connectionId: 'warehouse',
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query: { measures: ['sum(invoices.amount)'], dimensions: [] },
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compute,
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});
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const lastCall = (compute.query as ReturnType<typeof vi.fn>).mock.calls.at(-1)?.[0];
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const invoices = lastCall?.sources.find((s: Record<string, unknown>) => s.name === 'invoices');
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expect(invoices).toBeDefined();
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expect(invoices).not.toHaveProperty('usage');
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expect(invoices).not.toHaveProperty('inherits_columns_from');
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expect(invoices).not.toHaveProperty('source_type');
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});
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it('resolves the only configured connection when connectionId is omitted', async () => {
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await compileLocalSlQuery(project, {
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query: { measures: ['orders.order_count'], dimensions: [] },
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compute,
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});
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expect(compute.query).toHaveBeenCalledWith(
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expect.objectContaining({
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dialect: 'postgres',
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}),
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);
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});
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it('executes compiled SQL through a local query executor when requested', async () => {
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const queryExecutor = {
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execute: vi.fn(async () => ({
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headers: ['status', 'order_count'],
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rows: [['paid', 2]],
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totalRows: 1,
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command: 'SELECT',
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rowCount: 1,
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})),
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};
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const result = await compileLocalSlQuery(project, {
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connectionId: 'warehouse',
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query: {
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measures: ['orders.order_count'],
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dimensions: ['orders.status'],
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limit: 25,
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},
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compute,
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execute: true,
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maxRows: 10,
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queryExecutor,
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});
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expect(queryExecutor.execute).toHaveBeenCalledWith({
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connectionId: 'warehouse',
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projectDir: project.projectDir,
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connection: { driver: 'postgres' },
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sql: 'select status, count(*) as order_count from public.orders group by status',
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maxRows: 10,
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});
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expect(result.rows).toEqual([['paid', 2]]);
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expect(result.totalRows).toBe(1);
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expect(result.plan.execution).toEqual({
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mode: 'executed',
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driver: 'postgres',
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maxRows: 10,
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rowCount: 1,
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});
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});
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it('emits progress while compiling and executing a local semantic-layer query', async () => {
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const progress: Array<{ progress: number; message: string }> = [];
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const queryExecutor = {
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execute: vi.fn(async () => ({
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headers: ['status', 'order_count'],
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rows: [['paid', 2]],
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totalRows: 1,
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command: 'SELECT',
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rowCount: 1,
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})),
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};
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const result = await compileLocalSlQuery(project, {
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connectionId: 'warehouse',
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query: {
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measures: ['orders.order_count'],
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dimensions: ['orders.status'],
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limit: 25,
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},
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compute,
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execute: true,
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maxRows: 10,
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queryExecutor,
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onProgress: (event) => {
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progress.push({ progress: event.progress, message: event.message });
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},
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});
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expect(result.totalRows).toBe(1);
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expect(progress).toEqual([
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{ progress: 0, message: 'Compiling query' },
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{ progress: 0.3, message: 'Generating SQL' },
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{ progress: 0.6, message: 'Executing' },
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{ progress: 1, message: 'Fetched 1 rows' },
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]);
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});
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it('requires a query executor for executed mode', async () => {
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await expect(
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compileLocalSlQuery(project, {
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connectionId: 'warehouse',
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query: { measures: ['orders.order_count'], dimensions: [] },
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compute,
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execute: true,
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}),
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).rejects.toThrow('Local semantic-layer execution requires a query executor.');
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});
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it('requires connectionId, listing the configured connections, when several exist', async () => {
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project.config.connections.analytics = { driver: 'bigquery' };
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await expect(
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compileLocalSlQuery(project, {
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query: { measures: ['orders.order_count'], dimensions: [] },
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compute,
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}),
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).rejects.toThrow('connectionId is required. Configured connections: analytics, warehouse.');
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});
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it('rejects a connectionId that is not configured, listing the configured connections', async () => {
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await expect(
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compileLocalSlQuery(project, {
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connectionId: 'DIG_SMART_REP',
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query: { measures: ['orders.order_count'], dimensions: [] },
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compute,
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}),
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).rejects.toThrow('Connection "DIG_SMART_REP" is not configured in ktx.yaml. Configured connections: warehouse.');
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});
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});
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