ktx/packages/cli/test/context/sl/local-query.test.ts
Pintouch 2afab61417
feat(connectors): add MongoDB connector (#305) (#310)
* 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>
2026-06-29 15:17:56 +02:00

359 lines
10 KiB
TypeScript

import { mkdtemp, rm } from 'node:fs/promises';
import { tmpdir } from 'node:os';
import { join } from 'node:path';
import { afterEach, beforeEach, describe, expect, it, vi } from 'vitest';
import type { KtxSemanticLayerComputePort } from '../../../src/context/daemon/semantic-layer-compute.js';
import { initKtxProject, type KtxLocalProject } from '../../../src/context/project/project.js';
import { compileLocalSlQuery } from '../../../src/context/sl/local-query.js';
describe('compileLocalSlQuery', () => {
let tempDir: string;
let project: KtxLocalProject;
let compute: KtxSemanticLayerComputePort;
beforeEach(async () => {
tempDir = await mkdtemp(join(tmpdir(), 'ktx-local-query-'));
project = await initKtxProject({ projectDir: join(tempDir, 'project') });
project.config.connections.warehouse = { driver: 'postgres' };
await project.fileStore.writeFile(
'semantic-layer/warehouse/orders.yaml',
`name: orders
table: public.orders
grain:
- id
columns:
- name: id
type: number
- name: status
type: string
measures:
- name: order_count
expr: count(*)
joins: []
`,
'ktx',
'ktx@example.com',
'Add orders source',
);
await project.fileStore.writeFile(
'semantic-layer/warehouse/orders_overlay.yaml',
`name: orders_overlay
inherits_columns_from: orders
columns:
- name: paid_at
type: timestamp
joins: []
measures: []
grain: []
`,
'ktx',
'ktx@example.com',
'Add overlay source',
);
compute = {
query: vi.fn(async (input) => ({
sql: 'select status, count(*) as order_count from public.orders group by status',
dialect: input.dialect,
columns: [{ name: 'orders.status' }, { name: 'orders.order_count' }],
plan: { measures: input.query.measures, dimensions: input.query.dimensions },
})),
validateSources: vi.fn(),
generateSources: vi.fn(),
};
});
afterEach(async () => {
await rm(tempDir, { recursive: true, force: true });
});
it('refuses a non-SQL (context-only) connection instead of compiling it as Postgres', async () => {
project.config.connections['mongo-prod'] = { driver: 'mongodb', url: 'mongodb://localhost:27017/app' };
await expect(
compileLocalSlQuery(project, {
connectionId: 'mongo-prod',
query: { measures: ['orders.order_count'], dimensions: ['orders.status'], limit: 25 },
compute,
}),
).rejects.toThrow(/non-SQL driver 'mongodb'|require a SQL warehouse connection/);
expect(compute.query).not.toHaveBeenCalled();
});
it('compiles a local semantic-layer query with computable sources only', async () => {
const result = await compileLocalSlQuery(project, {
connectionId: 'warehouse',
query: {
measures: ['orders.order_count'],
dimensions: ['orders.status'],
limit: 25,
},
compute,
});
expect(compute.query).toHaveBeenCalledWith({
sources: [
{
name: 'orders',
table: 'public.orders',
grain: ['id'],
columns: [
{ name: 'id', type: 'number' },
{ name: 'status', type: 'string' },
],
measures: [{ name: 'order_count', expr: 'count(*)' }],
joins: [],
},
],
dialect: 'postgres',
query: {
measures: ['orders.order_count'],
dimensions: ['orders.status'],
limit: 25,
},
});
expect(result).toEqual({
connectionId: 'warehouse',
dialect: 'postgres',
sql: 'select status, count(*) as order_count from public.orders group by status',
headers: ['orders.status', 'orders.order_count'],
rows: [],
totalRows: 0,
plan: {
measures: ['orders.order_count'],
dimensions: ['orders.status'],
execution: {
mode: 'compile_only',
reason: 'Local semantic-layer query compiled SQL but no data-source execution adapter is configured.',
},
},
});
});
it('compiles a local semantic-layer query from manifest-backed scan sources', async () => {
await project.fileStore.writeFile(
'semantic-layer/warehouse/_schema/public.yaml',
`tables:
payments:
table: public.payments
columns:
- name: payment_id
type: number
pk: true
- name: amount
type: number
`,
'ktx',
'ktx@example.com',
'Add manifest shard',
);
await compileLocalSlQuery(project, {
connectionId: 'warehouse',
query: {
measures: ['sum(payments.amount)'],
dimensions: [],
},
compute,
});
expect(compute.query).toHaveBeenLastCalledWith({
sources: expect.arrayContaining([
{
name: 'payments',
table: 'public.payments',
grain: ['payment_id'],
columns: [
{
name: 'payment_id',
type: 'number',
role: undefined,
descriptions: undefined,
constraints: undefined,
enum_values: undefined,
tests: undefined,
},
{
name: 'amount',
type: 'number',
role: undefined,
descriptions: undefined,
constraints: undefined,
enum_values: undefined,
tests: undefined,
},
],
joins: [],
measures: [],
},
]),
dialect: 'postgres',
query: {
measures: ['sum(payments.amount)'],
dimensions: [],
},
});
});
it('strips authoring-only fields (usage, inherits_columns_from) before sending sources to the daemon', async () => {
await project.fileStore.writeFile(
'semantic-layer/warehouse/_schema/public.yaml',
`tables:
invoices:
table: public.invoices
columns:
- name: invoice_id
type: number
pk: true
- name: amount
type: number
usage:
narrative: Activation policy windows table for invoice analytics.
frequencyTier: mid
commonFilters:
- amount
commonGroupBys: []
commonJoins: []
staleSince: null
`,
'ktx',
'ktx@example.com',
'Add manifest shard with usage',
);
await compileLocalSlQuery(project, {
connectionId: 'warehouse',
query: { measures: ['sum(invoices.amount)'], dimensions: [] },
compute,
});
const lastCall = (compute.query as ReturnType<typeof vi.fn>).mock.calls.at(-1)?.[0];
const invoices = lastCall?.sources.find((s: Record<string, unknown>) => s.name === 'invoices');
expect(invoices).toBeDefined();
expect(invoices).not.toHaveProperty('usage');
expect(invoices).not.toHaveProperty('inherits_columns_from');
expect(invoices).not.toHaveProperty('source_type');
});
it('resolves the only configured connection when connectionId is omitted', async () => {
await compileLocalSlQuery(project, {
query: { measures: ['orders.order_count'], dimensions: [] },
compute,
});
expect(compute.query).toHaveBeenCalledWith(
expect.objectContaining({
dialect: 'postgres',
}),
);
});
it('executes compiled SQL through a local query executor when requested', async () => {
const queryExecutor = {
execute: vi.fn(async () => ({
headers: ['status', 'order_count'],
rows: [['paid', 2]],
totalRows: 1,
command: 'SELECT',
rowCount: 1,
})),
};
const result = await compileLocalSlQuery(project, {
connectionId: 'warehouse',
query: {
measures: ['orders.order_count'],
dimensions: ['orders.status'],
limit: 25,
},
compute,
execute: true,
maxRows: 10,
queryExecutor,
});
expect(queryExecutor.execute).toHaveBeenCalledWith({
connectionId: 'warehouse',
projectDir: project.projectDir,
connection: { driver: 'postgres' },
sql: 'select status, count(*) as order_count from public.orders group by status',
maxRows: 10,
});
expect(result.rows).toEqual([['paid', 2]]);
expect(result.totalRows).toBe(1);
expect(result.plan.execution).toEqual({
mode: 'executed',
driver: 'postgres',
maxRows: 10,
rowCount: 1,
});
});
it('emits progress while compiling and executing a local semantic-layer query', async () => {
const progress: Array<{ progress: number; message: string }> = [];
const queryExecutor = {
execute: vi.fn(async () => ({
headers: ['status', 'order_count'],
rows: [['paid', 2]],
totalRows: 1,
command: 'SELECT',
rowCount: 1,
})),
};
const result = await compileLocalSlQuery(project, {
connectionId: 'warehouse',
query: {
measures: ['orders.order_count'],
dimensions: ['orders.status'],
limit: 25,
},
compute,
execute: true,
maxRows: 10,
queryExecutor,
onProgress: (event) => {
progress.push({ progress: event.progress, message: event.message });
},
});
expect(result.totalRows).toBe(1);
expect(progress).toEqual([
{ progress: 0, message: 'Compiling query' },
{ progress: 0.3, message: 'Generating SQL' },
{ progress: 0.6, message: 'Executing' },
{ progress: 1, message: 'Fetched 1 rows' },
]);
});
it('requires a query executor for executed mode', async () => {
await expect(
compileLocalSlQuery(project, {
connectionId: 'warehouse',
query: { measures: ['orders.order_count'], dimensions: [] },
compute,
execute: true,
}),
).rejects.toThrow('Local semantic-layer execution requires a query executor.');
});
it('requires connectionId, listing the configured connections, when several exist', async () => {
project.config.connections.analytics = { driver: 'bigquery' };
await expect(
compileLocalSlQuery(project, {
query: { measures: ['orders.order_count'], dimensions: [] },
compute,
}),
).rejects.toThrow('connectionId is required. Configured connections: analytics, warehouse.');
});
it('rejects a connectionId that is not configured, listing the configured connections', async () => {
await expect(
compileLocalSlQuery(project, {
connectionId: 'DIG_SMART_REP',
query: { measures: ['orders.order_count'], dimensions: [] },
compute,
}),
).rejects.toThrow('Connection "DIG_SMART_REP" is not configured in ktx.yaml. Configured connections: warehouse.');
});
});