ktx/packages/cli/test/context/scan/relationship-validation.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

506 lines
18 KiB
TypeScript

import Database from 'better-sqlite3';
import { afterEach, describe, expect, it } from 'vitest';
import { getSqlDialectForDriver } from '../../../src/context/connections/dialects.js';
import type { KtxEnrichedColumn, KtxEnrichedSchema, KtxEnrichedTable } from '../../../src/context/scan/enrichment-types.js';
import { generateKtxRelationshipDiscoveryCandidates } from '../../../src/context/scan/relationship-candidates.js';
import type { KtxRelationshipProfileArtifact } from '../../../src/context/scan/relationship-profiling.js';
import { profileKtxRelationshipSchema } from '../../../src/context/scan/relationship-profiling.js';
import { validateKtxRelationshipDiscoveryCandidates } from '../../../src/context/scan/relationship-validation.js';
import type { KtxQueryResult, KtxReadOnlyQueryInput, KtxScanContext } from '../../../src/context/scan/types.js';
// This harness runs SQL directly through SQLite; row-limit wrapper coverage lives
// in read-only-sql.test.ts and the SQL Server connector test.
class InMemorySqliteExecutor {
readonly db = new Database(':memory:');
queryCount = 0;
executeReadOnly(input: KtxReadOnlyQueryInput, _ctx: KtxScanContext): Promise<KtxQueryResult> {
this.queryCount += 1;
const rows = this.db.prepare(input.sql).all() as Record<string, unknown>[];
const headers = Object.keys(rows[0] ?? {});
return Promise.resolve({
headers,
rows: rows.map((row) => headers.map((header) => row[header])),
totalRows: rows.length,
rowCount: rows.length,
});
}
close(): void {
this.db.close();
}
}
function column(tableId: string, name: string, overrides: Partial<KtxEnrichedColumn> = {}): KtxEnrichedColumn {
const tableRef = overrides.tableRef ?? { catalog: null, db: null, name: tableId };
return {
id: `${tableId}.${name}`,
tableId,
tableRef,
name,
nativeType: overrides.nativeType ?? 'INTEGER',
normalizedType: overrides.normalizedType ?? 'integer',
dimensionType: overrides.dimensionType ?? 'number',
nullable: overrides.nullable ?? true,
primaryKey: overrides.primaryKey ?? false,
parentColumnId: null,
descriptions: {},
embedding: null,
sampleValues: null,
cardinality: null,
...overrides,
};
}
function table(name: string, columns: KtxEnrichedColumn[]): KtxEnrichedTable {
const ref = { catalog: null, db: null, name };
return {
id: name,
ref,
enabled: true,
descriptions: {},
columns: columns.map((item) => ({ ...item, tableId: name, tableRef: ref })),
};
}
function schema(tables?: KtxEnrichedTable[]): KtxEnrichedSchema {
return {
connectionId: 'warehouse',
tables: tables ?? [
table('accounts', [
column('accounts', 'id', { nullable: false }),
column('accounts', 'name', { nativeType: 'TEXT', normalizedType: 'text', dimensionType: 'string' }),
]),
table('users', [column('users', 'id', { nullable: false }), column('users', 'account_id', { nullable: false })]),
table('invoices', [
column('invoices', 'id', { nullable: false }),
column('invoices', 'account_id', { nullable: false }),
]),
],
relationships: [],
};
}
describe('relationship validation', () => {
let executor: InMemorySqliteExecutor | null = null;
afterEach(() => {
executor?.close();
executor = null;
});
it('accepts a relationship-discovery candidate with unique parent values and full source coverage', async () => {
executor = new InMemorySqliteExecutor();
executor.db.exec(`
CREATE TABLE accounts (id INTEGER, name TEXT);
CREATE TABLE users (id INTEGER, account_id INTEGER);
CREATE TABLE invoices (id INTEGER, account_id INTEGER);
INSERT INTO accounts (id, name) VALUES (1, 'Acme'), (2, 'Globex'), (3, 'Initech');
INSERT INTO users (id, account_id) VALUES (10, 1), (11, 2), (12, 3);
INSERT INTO invoices (id, account_id) VALUES (20, 1), (21, 2), (22, 999);
`);
const testSchema = schema();
const profiles = await profileKtxRelationshipSchema({
connectionId: 'warehouse',
driver: 'sqlite',
dialect: getSqlDialectForDriver('sqlite'),
schema: testSchema,
executor,
ctx: { runId: 'validate-test' },
});
const candidates = generateKtxRelationshipDiscoveryCandidates(testSchema).filter(
(candidate) => candidate.from.table.name === 'users',
);
const validated = await validateKtxRelationshipDiscoveryCandidates({
connectionId: 'warehouse',
dialect: getSqlDialectForDriver('sqlite'),
candidates,
profiles,
executor,
ctx: { runId: 'validate-test' },
tableCount: testSchema.tables.length,
});
expect(validated).toHaveLength(1);
expect(validated[0]).toMatchObject({
from: { table: { name: 'users' }, columns: ['account_id'] },
to: { table: { name: 'accounts' }, columns: ['id'] },
status: 'accepted',
score: expect.any(Number),
validation: {
targetUniqueness: 1,
sourceCoverage: 1,
violationCount: 0,
violationRatio: 0,
reasons: expect.arrayContaining(['validation_passed']),
},
});
expect(validated[0]?.score).toBeGreaterThanOrEqual(0.85);
});
it('rejects a candidate with missing parent values and records the deterministic reason', async () => {
executor = new InMemorySqliteExecutor();
executor.db.exec(`
CREATE TABLE accounts (id INTEGER, name TEXT);
CREATE TABLE users (id INTEGER, account_id INTEGER);
CREATE TABLE invoices (id INTEGER, account_id INTEGER);
INSERT INTO accounts (id, name) VALUES (1, 'Acme'), (2, 'Globex');
INSERT INTO users (id, account_id) VALUES (10, 1), (11, 2);
INSERT INTO invoices (id, account_id) VALUES (20, 1), (21, 999), (22, 1000);
`);
const testSchema = schema();
const profiles = await profileKtxRelationshipSchema({
connectionId: 'warehouse',
driver: 'sqlite',
dialect: getSqlDialectForDriver('sqlite'),
schema: testSchema,
executor,
ctx: { runId: 'validate-test' },
});
const candidates = generateKtxRelationshipDiscoveryCandidates(testSchema).filter(
(candidate) => candidate.from.table.name === 'invoices',
);
const validated = await validateKtxRelationshipDiscoveryCandidates({
connectionId: 'warehouse',
dialect: getSqlDialectForDriver('sqlite'),
candidates,
profiles,
executor,
ctx: { runId: 'validate-test' },
tableCount: testSchema.tables.length,
settings: {
minSourceCoverage: 0.9,
maxViolationRatio: 0.01,
},
});
expect(validated).toHaveLength(1);
expect(validated[0]).toMatchObject({
from: { table: { name: 'invoices' }, columns: ['account_id'] },
to: { table: { name: 'accounts' }, columns: ['id'] },
status: 'rejected',
validation: {
sourceCoverage: 1 / 3,
violationCount: 2,
violationRatio: 2 / 3,
reasons: expect.arrayContaining(['low_source_coverage', 'excessive_violations']),
},
});
});
it('keeps over-budget candidates review-only without executing coverage SQL for them', async () => {
executor = new InMemorySqliteExecutor();
executor.db.exec(`
CREATE TABLE accounts (id INTEGER, name TEXT);
CREATE TABLE users (id INTEGER, account_id INTEGER);
CREATE TABLE invoices (id INTEGER, account_id INTEGER);
INSERT INTO accounts (id, name) VALUES (1, 'Acme'), (2, 'Globex'), (3, 'Initech');
INSERT INTO users (id, account_id) VALUES (10, 1), (11, 2), (12, 3);
INSERT INTO invoices (id, account_id) VALUES (20, 1), (21, 2), (22, 3);
`);
const testSchema = schema();
const profiles = await profileKtxRelationshipSchema({
connectionId: 'warehouse',
driver: 'sqlite',
dialect: getSqlDialectForDriver('sqlite'),
schema: testSchema,
executor,
ctx: { runId: 'validate-budget-profile' },
});
executor.queryCount = 0;
const candidates = generateKtxRelationshipDiscoveryCandidates(testSchema).map((candidate) => ({
...candidate,
confidence: candidate.from.table.name === 'users' ? 0.99 : 0.5,
}));
const validated = await validateKtxRelationshipDiscoveryCandidates({
connectionId: 'warehouse',
dialect: getSqlDialectForDriver('sqlite'),
candidates,
profiles,
executor,
ctx: { runId: 'validate-budget' },
tableCount: testSchema.tables.length,
settings: {
validationBudget: 1,
},
});
expect(executor.queryCount).toBe(1);
expect(validated).toHaveLength(2);
expect(validated.find((candidate) => candidate.from.table.name === 'users')).toMatchObject({
status: 'accepted',
validation: { reasons: expect.arrayContaining(['validation_passed']) },
});
expect(validated.find((candidate) => candidate.from.table.name === 'invoices')).toMatchObject({
status: 'review',
validation: {
reasons: ['validation_unattempted'],
},
});
});
it('treats validation budget zero as review-only validation without coverage SQL', async () => {
executor = new InMemorySqliteExecutor();
executor.db.exec(`
CREATE TABLE accounts (id INTEGER, name TEXT);
CREATE TABLE users (id INTEGER, account_id INTEGER);
INSERT INTO accounts (id, name) VALUES (1, 'Acme'), (2, 'Globex');
INSERT INTO users (id, account_id) VALUES (10, 1), (11, 2);
`);
const testSchema = schema([
table('accounts', [
column('accounts', 'id', { nullable: false }),
column('accounts', 'name', { nativeType: 'TEXT', normalizedType: 'text', dimensionType: 'string' }),
]),
table('users', [column('users', 'id', { nullable: false }), column('users', 'account_id', { nullable: false })]),
]);
const profiles = await profileKtxRelationshipSchema({
connectionId: 'warehouse',
driver: 'sqlite',
dialect: getSqlDialectForDriver('sqlite'),
schema: testSchema,
executor,
ctx: { runId: 'validate-zero-budget-profile' },
});
executor.queryCount = 0;
const candidates = generateKtxRelationshipDiscoveryCandidates(testSchema);
const validated = await validateKtxRelationshipDiscoveryCandidates({
connectionId: 'warehouse',
dialect: getSqlDialectForDriver('sqlite'),
candidates,
profiles,
executor,
ctx: { runId: 'validate-zero-budget' },
tableCount: testSchema.tables.length,
settings: {
validationBudget: 0,
},
});
expect(executor.queryCount).toBe(0);
expect(validated).toHaveLength(1);
expect(validated[0]).toMatchObject({
status: 'review',
score: expect.any(Number),
validation: {
checkedValues: 0,
reasons: ['validation_unattempted'],
},
});
});
it('marks rejected LLM proposals with the spec rejection reason', async () => {
executor = new InMemorySqliteExecutor();
executor.db.exec(`
CREATE TABLE customers (id INTEGER);
CREATE TABLE orders (buyer_ref INTEGER);
INSERT INTO customers (id) VALUES (1), (2);
INSERT INTO orders (buyer_ref) VALUES (98), (99);
`);
const testSchema = schema([
table('customers', [column('customers', 'id', { nullable: false })]),
table('orders', [column('orders', 'buyer_ref')]),
]);
const profiles = await profileKtxRelationshipSchema({
connectionId: 'warehouse',
driver: 'sqlite',
dialect: getSqlDialectForDriver('sqlite'),
schema: testSchema,
executor,
ctx: { runId: 'llm-rejected-validation' },
});
const [candidate] = generateKtxRelationshipDiscoveryCandidates(
schema([
table('customers', [column('customers', 'id', { nullable: false })]),
table('orders', [column('orders', 'customer_id')]),
]),
);
if (!candidate) {
throw new Error('Expected base candidate');
}
const llmCandidate = {
...candidate,
id: 'orders:(orders.buyer_ref)->customers:(customers.id)',
from: { ...candidate.from, columnIds: ['orders.buyer_ref'], columns: ['buyer_ref'] },
source: 'llm_proposal' as const,
evidence: {
...candidate.evidence,
reasons: ['llm_proposal'],
llmConfidence: 0.84,
llmRationale: 'Buyer references should map to customers.',
},
};
const [validated] = await validateKtxRelationshipDiscoveryCandidates({
connectionId: 'warehouse',
dialect: getSqlDialectForDriver('sqlite'),
candidates: [llmCandidate],
profiles,
executor,
ctx: { runId: 'llm-rejected-validation' },
tableCount: testSchema.tables.length,
});
expect(validated?.status).toBe('rejected');
expect(validated?.validation.reasons).toEqual(
expect.arrayContaining(['low_source_coverage', 'llm_proposed_but_validation_failed']),
);
});
it('limits validation query concurrency', async () => {
const executor = new InMemorySqliteExecutor();
executor.db.exec(`
CREATE TABLE accounts (id INTEGER NOT NULL);
CREATE TABLE orders (id INTEGER NOT NULL, account_id INTEGER NOT NULL);
CREATE TABLE invoices (id INTEGER NOT NULL, account_id INTEGER NOT NULL);
INSERT INTO accounts VALUES (1), (2);
INSERT INTO orders VALUES (10, 1), (11, 2);
INSERT INTO invoices VALUES (20, 1), (21, 2);
`);
let active = 0;
let maxActive = 0;
const throttled = {
executeReadOnly: async (input: KtxReadOnlyQueryInput, ctx: KtxScanContext) => {
active += 1;
maxActive = Math.max(maxActive, active);
await new Promise((resolve) => setTimeout(resolve, input.sql.includes('WITH child_values') ? 10 : 0));
const result = await executor.executeReadOnly(input, ctx);
active -= 1;
return result;
},
};
const testSchema = schema([
table('accounts', [column('accounts', 'id', { nullable: false })]),
table('orders', [column('orders', 'id', { nullable: false }), column('orders', 'account_id')]),
table('invoices', [column('invoices', 'id', { nullable: false }), column('invoices', 'account_id')]),
]);
const profiles = await profileKtxRelationshipSchema({
connectionId: 'warehouse',
driver: 'sqlite',
dialect: getSqlDialectForDriver('sqlite'),
schema: testSchema,
executor,
ctx: { runId: 'validation-concurrency-profile' },
});
const candidates = generateKtxRelationshipDiscoveryCandidates(testSchema);
await validateKtxRelationshipDiscoveryCandidates({
connectionId: 'warehouse',
dialect: getSqlDialectForDriver('sqlite'),
candidates,
profiles,
executor: throttled,
ctx: { runId: 'validation-concurrency' },
tableCount: testSchema.tables.length,
settings: { concurrency: 1 },
});
expect(maxActive).toBe(1);
executor.close();
});
it('pins column_suffix_match validation scoring for plan-code suffix candidates', async () => {
const candidate = {
id: 'mart:(current_plan_code)->plans:(plan_code)',
from: {
tableId: 'mart-account-segments-id',
columnIds: ['current-plan-code-col'],
table: { catalog: null, db: null, name: 'mart_account_segments' },
columns: ['current_plan_code'],
},
to: {
tableId: 'plans-id',
columnIds: ['plan-code-col'],
table: { catalog: null, db: null, name: 'stg_plans' },
columns: ['plan_code'],
},
relationshipType: 'many_to_one' as const,
confidence: 0.902,
source: 'column_suffix_match' as const,
status: 'review' as const,
evidence: {
sourceColumnBase: 'current_plan',
targetTableBase: 'plan',
targetColumnBase: 'plan_code',
targetKeyScore: 0.86,
nameScore: 0.78,
reasons: ['column_suffix_match', 'profile_unique_target'],
},
};
const profiles = {
connectionId: 'warehouse',
driver: 'sqlite',
sqlAvailable: true,
queryCount: 0,
tables: [],
warnings: [],
columns: {
'mart_account_segments.current_plan_code': {
table: { catalog: null, db: null, name: 'mart_account_segments' },
column: 'current_plan_code',
nativeType: 'TEXT',
normalizedType: 'text',
rowCount: 4,
nullCount: 0,
distinctCount: 4,
uniquenessRatio: 1,
nullRate: 0,
sampleValues: ['basic', 'enterprise', 'free', 'pro'],
minTextLength: 4,
maxTextLength: 10,
},
'stg_plans.plan_code': {
table: { catalog: null, db: null, name: 'stg_plans' },
column: 'plan_code',
nativeType: 'TEXT',
normalizedType: 'text',
rowCount: 4,
nullCount: 0,
distinctCount: 4,
uniquenessRatio: 1,
nullRate: 0,
sampleValues: ['basic', 'enterprise', 'free', 'pro'],
minTextLength: 4,
maxTextLength: 10,
},
},
} satisfies KtxRelationshipProfileArtifact;
const executor = {
async executeReadOnly() {
return {
headers: ['child_distinct', 'parent_distinct', 'overlap', 'violation_count'],
rows: [[4, 4, 4, 0]],
rowCount: 1,
totalRows: 1,
};
},
};
const [validated] = await validateKtxRelationshipDiscoveryCandidates({
connectionId: 'warehouse',
dialect: getSqlDialectForDriver('sqlite'),
candidates: [candidate],
profiles,
executor,
ctx: { runId: 'rule-b-validation-score' },
tableCount: 2,
});
expect(validated).toMatchObject({
status: 'accepted',
score: 0.98,
validation: {
targetUniqueness: 1,
sourceCoverage: 1,
violationRatio: 0,
reasons: ['validation_passed'],
},
});
});
});