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
|
|
|
import { describe, expect, it } from 'vitest';
|
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
|
|
|
import { getDialectForDriver, getSqlDialectForDriver } from '../../../src/context/connections/dialects.js';
|
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
|
|
|
import type { KtxConnectionDriver, KtxTableRef } from '../../../src/context/scan/types.js';
|
|
|
|
|
|
|
|
|
|
interface DialectFixture {
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|
driver: KtxConnectionDriver;
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table: KtxTableRef;
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quoteInput: string;
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quotedIdentifier: string;
|
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formattedTable: string;
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display: string;
|
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invalidDisplay: string;
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columnDisplayTablePartCount: 1 | 2 | 3;
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limitClause: string;
|
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topClause: string;
|
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randomFilter: string;
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tableSampleClause: string;
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sampleQuery: string;
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columnSampleContains: string;
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nullCountExpression: string;
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distinctCountExpression: string;
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textLengthExpression: string;
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castToText: string;
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sampleValueAggregation: string;
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cardinalityContains: string;
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randomizedCardinalityContains: string;
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distinctValuesContains: string;
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statisticsContains: string | null;
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dimensionInput: string;
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dimensionType: 'time' | 'string' | 'number' | 'boolean';
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nativeTypeInput: string;
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normalizedType: string;
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}
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const innerSampleSql = 'SELECT status AS value FROM orders';
|
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const fixtures: DialectFixture[] = [
|
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{
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driver: 'postgres',
|
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table: { catalog: null, db: 'public', name: 'orders' },
|
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quoteInput: 'order"items',
|
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quotedIdentifier: '"order""items"',
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formattedTable: '"public"."orders"',
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display: 'public.orders',
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invalidDisplay: 'orders',
|
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columnDisplayTablePartCount: 2,
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limitClause: 'LIMIT 25 OFFSET 5',
|
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topClause: '',
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randomFilter: 'RANDOM() < 0.25',
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tableSampleClause: 'TABLESAMPLE SYSTEM (25)',
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sampleQuery: 'SELECT "id", "status" FROM "public"."orders" LIMIT 5',
|
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columnSampleContains: 'TRIM(CAST("status" AS TEXT)) != \'\'',
|
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nullCountExpression: 'COUNT(*) FILTER (WHERE "status" IS NULL)',
|
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distinctCountExpression: 'COUNT(DISTINCT "status")',
|
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textLengthExpression: 'LENGTH(CAST("status" AS TEXT))',
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castToText: 'CAST("status" AS TEXT)',
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sampleValueAggregation:
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'(SELECT STRING_AGG(CAST(value AS TEXT), CHR(31)) FROM (SELECT status AS value FROM orders) AS relationship_profile_values)',
|
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cardinalityContains: 'SELECT COUNT(DISTINCT val) AS cardinality',
|
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randomizedCardinalityContains: 'ORDER BY RANDOM()',
|
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distinctValuesContains: 'SELECT DISTINCT "status"::text AS val',
|
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statisticsContains: 'FROM pg_stats s',
|
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dimensionInput: 'timestamp with time zone',
|
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dimensionType: 'time',
|
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nativeTypeInput: 'numeric(12,2)',
|
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normalizedType: 'numeric(12,2)',
|
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},
|
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{
|
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driver: 'mysql',
|
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table: { catalog: null, db: 'analytics', name: 'orders' },
|
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quoteInput: 'order`items',
|
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quotedIdentifier: '`order``items`',
|
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formattedTable: '`analytics`.`orders`',
|
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display: 'analytics.orders',
|
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invalidDisplay: 'orders',
|
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|
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columnDisplayTablePartCount: 2,
|
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|
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limitClause: 'LIMIT 25 OFFSET 5',
|
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|
|
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topClause: '',
|
|
|
|
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randomFilter: 'RAND() < 0.25',
|
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tableSampleClause: '',
|
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|
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sampleQuery: 'SELECT `id`, `status` FROM `analytics`.`orders` LIMIT 5',
|
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columnSampleContains: 'TRIM(CAST(`status` AS CHAR)) != \'\'',
|
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nullCountExpression: 'SUM(CASE WHEN `status` IS NULL THEN 1 ELSE 0 END)',
|
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|
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distinctCountExpression: 'COUNT(DISTINCT `status`)',
|
|
|
|
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textLengthExpression: 'CHAR_LENGTH(CAST(`status` AS CHAR))',
|
|
|
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castToText: 'CAST(`status` AS CHAR)',
|
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sampleValueAggregation:
|
|
|
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'(SELECT GROUP_CONCAT(CAST(value AS CHAR) SEPARATOR CHAR(31)) FROM (SELECT status AS value FROM orders) AS relationship_profile_values)',
|
|
|
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cardinalityContains: 'SELECT COUNT(DISTINCT val) AS cardinality',
|
|
|
|
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randomizedCardinalityContains: 'ORDER BY RAND()',
|
|
|
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distinctValuesContains: 'SELECT DISTINCT CAST(`status` AS CHAR) AS val',
|
2026-06-08 11:21:19 +01:00
|
|
|
statisticsContains: 'INFORMATION_SCHEMA.STATISTICS',
|
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
|
|
|
dimensionInput: 'tinyint(1)',
|
|
|
|
|
dimensionType: 'boolean',
|
|
|
|
|
nativeTypeInput: 'varchar(255)',
|
|
|
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|
normalizedType: 'varchar(255)',
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
driver: 'clickhouse',
|
|
|
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table: { catalog: null, db: 'analytics', name: 'events' },
|
|
|
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|
quoteInput: 'order`items',
|
|
|
|
|
quotedIdentifier: '`order``items`',
|
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|
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|
formattedTable: '`analytics`.`events`',
|
|
|
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|
display: 'analytics.events',
|
|
|
|
|
invalidDisplay: 'events',
|
|
|
|
|
columnDisplayTablePartCount: 2,
|
|
|
|
|
limitClause: 'LIMIT 25 OFFSET 5',
|
|
|
|
|
topClause: '',
|
|
|
|
|
randomFilter: 'rand() / 4294967295.0 < 0.25',
|
|
|
|
|
tableSampleClause: '',
|
|
|
|
|
sampleQuery: 'SELECT `id`, `status` FROM `analytics`.`events` LIMIT 5',
|
|
|
|
|
columnSampleContains: 'trim(toString(`status`)) != \'\'',
|
|
|
|
|
nullCountExpression: 'countIf(`status` IS NULL)',
|
|
|
|
|
distinctCountExpression: 'COUNT(DISTINCT `status`)',
|
|
|
|
|
textLengthExpression: 'length(toString(`status`))',
|
|
|
|
|
castToText: 'toString(`status`)',
|
|
|
|
|
sampleValueAggregation:
|
|
|
|
|
'(SELECT arrayStringConcat(groupArray(toString(value)), \'\\x1F\') FROM (SELECT status AS value FROM orders) AS relationship_profile_values)',
|
|
|
|
|
cardinalityContains: 'SELECT COUNT(DISTINCT val) AS cardinality',
|
|
|
|
|
randomizedCardinalityContains: 'ORDER BY rand()',
|
|
|
|
|
distinctValuesContains: 'SELECT DISTINCT toString(`status`) AS val',
|
|
|
|
|
statisticsContains: null,
|
|
|
|
|
dimensionInput: 'Nullable(DateTime64(3))',
|
|
|
|
|
dimensionType: 'time',
|
|
|
|
|
nativeTypeInput: 'LowCardinality(String)',
|
|
|
|
|
normalizedType: 'LowCardinality(String)',
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
driver: 'sqlite',
|
|
|
|
|
table: { catalog: null, db: null, name: 'orders' },
|
|
|
|
|
quoteInput: 'order"items',
|
|
|
|
|
quotedIdentifier: '"order""items"',
|
|
|
|
|
formattedTable: '"orders"',
|
|
|
|
|
display: 'orders',
|
|
|
|
|
invalidDisplay: 'public.orders',
|
|
|
|
|
columnDisplayTablePartCount: 1,
|
|
|
|
|
limitClause: 'LIMIT 25 OFFSET 5',
|
|
|
|
|
topClause: '',
|
|
|
|
|
randomFilter: '(RANDOM() % 100) < 25',
|
|
|
|
|
tableSampleClause: '',
|
|
|
|
|
sampleQuery: 'SELECT "id", "status" FROM "orders" LIMIT 5',
|
|
|
|
|
columnSampleContains: 'TRIM(CAST("status" AS TEXT)) != \'\'',
|
|
|
|
|
nullCountExpression: 'SUM(CASE WHEN "status" IS NULL THEN 1 ELSE 0 END)',
|
|
|
|
|
distinctCountExpression: 'COUNT(DISTINCT "status")',
|
|
|
|
|
textLengthExpression: 'LENGTH(CAST("status" AS TEXT))',
|
|
|
|
|
castToText: 'CAST("status" AS TEXT)',
|
|
|
|
|
sampleValueAggregation:
|
|
|
|
|
'(SELECT GROUP_CONCAT(CAST(value AS TEXT), char(31)) FROM (SELECT status AS value FROM orders) AS relationship_profile_values)',
|
|
|
|
|
cardinalityContains: 'SELECT COUNT(DISTINCT val) AS cardinality',
|
|
|
|
|
randomizedCardinalityContains: 'ORDER BY RANDOM()',
|
|
|
|
|
distinctValuesContains: 'SELECT DISTINCT CAST("status" AS TEXT) AS val',
|
|
|
|
|
statisticsContains: null,
|
|
|
|
|
dimensionInput: 'INTEGER',
|
|
|
|
|
dimensionType: 'number',
|
|
|
|
|
nativeTypeInput: 'VARCHAR(255)',
|
|
|
|
|
normalizedType: 'VARCHAR(255)',
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
driver: 'snowflake',
|
|
|
|
|
table: { catalog: 'ANALYTICS', db: 'PUBLIC', name: 'ORDERS' },
|
|
|
|
|
quoteInput: 'order"items',
|
|
|
|
|
quotedIdentifier: '"order""items"',
|
|
|
|
|
formattedTable: '"ANALYTICS"."PUBLIC"."ORDERS"',
|
|
|
|
|
display: 'ANALYTICS.PUBLIC.ORDERS',
|
|
|
|
|
invalidDisplay: 'PUBLIC.ORDERS',
|
|
|
|
|
columnDisplayTablePartCount: 3,
|
|
|
|
|
limitClause: 'LIMIT 25 OFFSET 5',
|
|
|
|
|
topClause: '',
|
|
|
|
|
randomFilter: 'UNIFORM(0::FLOAT, 1::FLOAT, RANDOM()) < 0.25',
|
|
|
|
|
tableSampleClause: 'SAMPLE (25)',
|
|
|
|
|
sampleQuery: 'SELECT "id", "status" FROM "ANALYTICS"."PUBLIC"."ORDERS" SAMPLE ROW (5 ROWS)',
|
|
|
|
|
columnSampleContains: 'TRIM(CAST("status" AS STRING)) != \'\'',
|
|
|
|
|
nullCountExpression: 'COUNT_IF("status" IS NULL)',
|
|
|
|
|
distinctCountExpression: 'APPROX_COUNT_DISTINCT("status")',
|
|
|
|
|
textLengthExpression: 'LENGTH(CAST("status" AS TEXT))',
|
|
|
|
|
castToText: 'CAST("status" AS VARCHAR)',
|
|
|
|
|
sampleValueAggregation:
|
|
|
|
|
'(SELECT LISTAGG(CAST(value AS VARCHAR), \'\\x1f\') FROM (SELECT status AS value FROM orders) AS relationship_profile_values)',
|
|
|
|
|
cardinalityContains: 'SELECT COUNT(DISTINCT val) AS cardinality',
|
|
|
|
|
randomizedCardinalityContains: 'SAMPLE ROW (100 ROWS)',
|
|
|
|
|
distinctValuesContains: 'SELECT DISTINCT "status"::VARCHAR AS val',
|
|
|
|
|
statisticsContains: null,
|
|
|
|
|
dimensionInput: 'TIMESTAMP_NTZ',
|
|
|
|
|
dimensionType: 'time',
|
|
|
|
|
nativeTypeInput: 'NUMBER(38,0)',
|
|
|
|
|
normalizedType: 'NUMBER(38,0)',
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
driver: 'bigquery',
|
|
|
|
|
table: { catalog: 'analytics-project', db: 'warehouse', name: 'orders' },
|
|
|
|
|
quoteInput: 'order`items',
|
|
|
|
|
quotedIdentifier: '`order\\`items`',
|
|
|
|
|
formattedTable: '`analytics-project`.`warehouse`.`orders`',
|
|
|
|
|
display: 'analytics-project.warehouse.orders',
|
|
|
|
|
invalidDisplay: 'warehouse.orders',
|
|
|
|
|
columnDisplayTablePartCount: 3,
|
|
|
|
|
limitClause: 'LIMIT 25 OFFSET 5',
|
|
|
|
|
topClause: '',
|
|
|
|
|
randomFilter: 'RAND() < 0.25',
|
|
|
|
|
tableSampleClause: 'TABLESAMPLE SYSTEM (25 PERCENT)',
|
|
|
|
|
sampleQuery: 'SELECT `id`, `status` FROM `analytics-project`.`warehouse`.`orders` ORDER BY RAND() LIMIT 5',
|
|
|
|
|
columnSampleContains: 'TRIM(CAST(`status` AS STRING)) != \'\'',
|
|
|
|
|
nullCountExpression: 'COUNTIF(`status` IS NULL)',
|
|
|
|
|
distinctCountExpression: 'APPROX_COUNT_DISTINCT(`status`)',
|
|
|
|
|
textLengthExpression: 'LENGTH(CAST(`status` AS STRING))',
|
|
|
|
|
castToText: 'CAST(`status` AS STRING)',
|
|
|
|
|
sampleValueAggregation:
|
|
|
|
|
'(SELECT STRING_AGG(CAST(value AS STRING), \'\\u001F\') FROM (SELECT status AS value FROM orders) AS relationship_profile_values)',
|
|
|
|
|
cardinalityContains: 'SELECT APPROX_COUNT_DISTINCT(val) AS cardinality',
|
|
|
|
|
randomizedCardinalityContains: 'ORDER BY RAND()',
|
|
|
|
|
distinctValuesContains: 'SELECT DISTINCT CAST(`status` AS STRING) AS val',
|
|
|
|
|
statisticsContains: null,
|
|
|
|
|
dimensionInput: 'INT64',
|
|
|
|
|
dimensionType: 'number',
|
|
|
|
|
nativeTypeInput: 'INT64',
|
|
|
|
|
normalizedType: 'BIGINT',
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
driver: 'sqlserver',
|
|
|
|
|
table: { catalog: 'warehouse', db: 'dbo', name: 'events' },
|
|
|
|
|
quoteInput: 'odd]name',
|
|
|
|
|
quotedIdentifier: '[odd]]name]',
|
|
|
|
|
formattedTable: '[warehouse].[dbo].[events]',
|
|
|
|
|
display: 'warehouse.dbo.events',
|
|
|
|
|
invalidDisplay: 'dbo.events',
|
|
|
|
|
columnDisplayTablePartCount: 3,
|
|
|
|
|
limitClause: '',
|
|
|
|
|
topClause: 'TOP (25)',
|
|
|
|
|
randomFilter: 'ABS(CHECKSUM(NEWID())) % 100 < 25',
|
|
|
|
|
tableSampleClause: 'TABLESAMPLE (25 PERCENT)',
|
|
|
|
|
sampleQuery: 'SELECT TOP 5 [id], [status] FROM [warehouse].[dbo].[events]',
|
|
|
|
|
columnSampleContains: 'LTRIM(RTRIM(CAST([status] AS NVARCHAR(MAX)))) != \'\'',
|
|
|
|
|
nullCountExpression: 'SUM(CASE WHEN [status] IS NULL THEN 1 ELSE 0 END)',
|
|
|
|
|
distinctCountExpression: 'COUNT(DISTINCT [status])',
|
|
|
|
|
textLengthExpression: 'LEN(CAST([status] AS NVARCHAR(MAX)))',
|
|
|
|
|
castToText: 'CAST([status] AS NVARCHAR(MAX))',
|
|
|
|
|
sampleValueAggregation:
|
|
|
|
|
'(SELECT STRING_AGG(CAST(value AS NVARCHAR(MAX)), CHAR(31)) FROM (SELECT status AS value FROM orders) AS relationship_profile_values)',
|
|
|
|
|
cardinalityContains: 'SELECT COUNT(DISTINCT val) AS cardinality',
|
|
|
|
|
randomizedCardinalityContains: 'ORDER BY NEWID()',
|
|
|
|
|
distinctValuesContains: 'SELECT TOP 20 val',
|
|
|
|
|
statisticsContains: null,
|
|
|
|
|
dimensionInput: 'datetime2',
|
|
|
|
|
dimensionType: 'time',
|
|
|
|
|
nativeTypeInput: 'uniqueidentifier',
|
|
|
|
|
normalizedType: 'uniqueidentifier',
|
|
|
|
|
},
|
|
|
|
|
];
|
|
|
|
|
|
|
|
|
|
describe('getDialectForDriver', () => {
|
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
|
|
|
it.each(fixtures)('returns a full KtxSqlDialect for $driver', (fixture) => {
|
|
|
|
|
const dialect = getSqlDialectForDriver(fixture.driver);
|
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
|
|
|
const column = dialect.quoteIdentifier('status');
|
|
|
|
|
|
|
|
|
|
expect(dialect.type).toBe(fixture.driver);
|
|
|
|
|
expect(dialect.quoteIdentifier(fixture.quoteInput)).toBe(fixture.quotedIdentifier);
|
|
|
|
|
expect(dialect.formatTableName(fixture.table)).toBe(fixture.formattedTable);
|
|
|
|
|
expect(dialect.formatDisplayRef(fixture.table)).toBe(fixture.display);
|
|
|
|
|
expect(dialect.parseDisplayRef(fixture.display)).toEqual(fixture.table);
|
|
|
|
|
expect(dialect.parseDisplayRef(fixture.invalidDisplay)).toBeNull();
|
|
|
|
|
expect(dialect.columnDisplayTablePartCount()).toBe(fixture.columnDisplayTablePartCount);
|
|
|
|
|
expect(dialect.getLimitOffsetClause(25, 5)).toBe(fixture.limitClause);
|
|
|
|
|
expect(dialect.getTopClause(25)).toBe(fixture.topClause);
|
|
|
|
|
expect(dialect.getRandomSampleFilter(0.25)).toBe(fixture.randomFilter);
|
|
|
|
|
expect(dialect.getTableSampleClause(0.25)).toBe(fixture.tableSampleClause);
|
|
|
|
|
expect(dialect.generateSampleQuery(fixture.formattedTable, 5, ['id', 'status'])).toBe(fixture.sampleQuery);
|
|
|
|
|
expect(dialect.generateColumnSampleQuery(fixture.formattedTable, 'status', 10)).toContain(
|
|
|
|
|
fixture.columnSampleContains,
|
|
|
|
|
);
|
|
|
|
|
expect(dialect.getNullCountExpression(column)).toBe(fixture.nullCountExpression);
|
|
|
|
|
expect(dialect.getDistinctCountExpression(column)).toBe(fixture.distinctCountExpression);
|
|
|
|
|
expect(dialect.textLengthExpression(column)).toBe(fixture.textLengthExpression);
|
|
|
|
|
expect(dialect.castToText(column)).toBe(fixture.castToText);
|
|
|
|
|
expect(dialect.getSampleValueAggregation(innerSampleSql)).toBe(fixture.sampleValueAggregation);
|
|
|
|
|
expect(dialect.generateCardinalitySampleQuery(fixture.formattedTable, column, 100)).toContain(
|
|
|
|
|
fixture.cardinalityContains,
|
|
|
|
|
);
|
|
|
|
|
expect(dialect.generateRandomizedCardinalitySampleQuery(fixture.formattedTable, column, 100)).toContain(
|
|
|
|
|
fixture.randomizedCardinalityContains,
|
|
|
|
|
);
|
|
|
|
|
expect(dialect.generateDistinctValuesQuery(fixture.formattedTable, column, 20)).toContain(
|
|
|
|
|
fixture.distinctValuesContains,
|
|
|
|
|
);
|
|
|
|
|
const statistics = dialect.generateColumnStatisticsQuery(fixture.table.db ?? '', fixture.table.name);
|
|
|
|
|
if (fixture.statisticsContains) {
|
|
|
|
|
expect(statistics).toContain(fixture.statisticsContains);
|
|
|
|
|
} else {
|
|
|
|
|
expect(statistics).toBeNull();
|
|
|
|
|
}
|
|
|
|
|
expect(dialect.mapToDimensionType(fixture.dimensionInput)).toBe(fixture.dimensionType);
|
|
|
|
|
expect(dialect.mapDataType(fixture.nativeTypeInput)).toBe(fixture.normalizedType);
|
|
|
|
|
});
|
|
|
|
|
|
|
|
|
|
it('accepts three-part ANSI display refs while keeping one-part names caller-owned', () => {
|
|
|
|
|
for (const driver of ['postgres', 'mysql', 'clickhouse'] as const) {
|
|
|
|
|
const dialect = getDialectForDriver(driver);
|
|
|
|
|
expect(dialect.parseDisplayRef('warehouse.public.orders')).toEqual({
|
|
|
|
|
catalog: 'warehouse',
|
|
|
|
|
db: 'public',
|
|
|
|
|
name: 'orders',
|
|
|
|
|
});
|
|
|
|
|
expect(dialect.parseDisplayRef('orders')).toBeNull();
|
|
|
|
|
}
|
|
|
|
|
});
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|
|
|
|
|
|
|
|
|
it('throws with a supported-driver list for unknown drivers', () => {
|
|
|
|
|
expect(() => getDialectForDriver('oracle')).toThrow(
|
2026-07-02 06:00:26 -07:00
|
|
|
'Unsupported driver "oracle". Supported drivers: athena, bigquery, clickhouse, duckdb, mongodb, mysql, postgres, snowflake, sqlite, sqlserver',
|
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
|
|
|
);
|
|
|
|
|
});
|
|
|
|
|
|
|
|
|
|
it('rejects legacy driver aliases', () => {
|
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
|
|
|
expect(() => getDialectForDriver('postgresql')).toThrow('Unsupported driver "postgresql"');
|
|
|
|
|
expect(() => getDialectForDriver('sqlite3')).toThrow('Unsupported driver "sqlite3"');
|
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
|
|
|
});
|
|
|
|
|
});
|