ktx/packages/cli/test/context/connections/dialects.test.ts

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test: split cli tests from source tree (#216) * feat(cli): define full warehouse dialect contract * test(cli): keep dialect edge tests focused * fix(cli): stabilize dialect contract foundation * refactor(connectors): own read-only query preparation * refactor(connectors): resolve dialects through registry * refactor(connectors): keep concrete dialect classes internal * chore(workspace): enforce dialect import boundary * refactor(cli): resolve relationship dialect at scan boundary * refactor(cli): use dialect display parsing for entity details * refactor(cli): use dialect display parsing for warehouse catalog * refactor(cli): use dialect SQL in relationship workflows * test(cli): verify solid dialect scan workflow closure * test: split cli tests from source tree * refactor(cli): standardize BigQuery scope listing * feat(sqlite): implement connector scope listing * test(connectors): cover required table listing * feat(cli): add warehouse driver registry * refactor(setup): route scope discovery through driver registry * refactor(cli): route local query execution through driver registry * refactor(historic-sql): route dialect support through driver registry * refactor(cli): test warehouse connections through driver registry * fix(cli): close driver registry type export gaps * Improve setup daemon diagnostics * refactor(setup): centralize rail-prefixed diagnostics + query-history fallback Extract errorMessage, writePrefixedLines, and flushPrefixedBufferedCommandOutput into clack.ts so the setup wizard, managed daemons, and embedding/agent steps share one rail-formatted writer. setup-databases.ts also adds a "disable query history and retry" option when the schema-context build fails and query history is the likely culprit, surfaced via a new failed-query-history-unavailable status. * fix(cli): carry catalog through the picker so BigQuery/Snowflake/SQL Server scope filters match The setup picker's KtxTableListEntry was a 2-level { schema, name }, so qualifiedTableId always wrote db.name into enabled_tables. When BigQuery, Snowflake, or SQL Server later ran fast ingest, their introspect step filtered the scope set with scopedTableNames(scope, { catalog: projectId|database, db }) — catalog was non-null on the introspect side but null in the scope refs, so every entry was rejected, the live-database adapter staged zero table files, and detect() failed with 'Adapter "live-database" did not recognize fetched source output'. Align the picker boundary with the canonical 3-level KtxTableRef: - Add catalog: string | null to KtxTableListEntry. - BigQuery/Snowflake/SQL Server listTables populate catalog from the resolved projectId / database; Postgres/MySQL/ClickHouse/SQLite set null. - qualifiedTableId emits catalog.schema.name when catalog is non-null (resolveEnabledTables already accepts the 3-part shape) and schemasFromEnabledTables now goes through parseDottedTableEntry so it recovers the schema correctly from both 2-part and 3-part entries. - Export parseDottedTableEntry from enabled-tables.ts (@internal) for picker reuse. Update listTables expectations in all seven connector tests and the setup / picker test fixtures. Add a picker regression test that covers the catalog-bearing round-trip (save + refine). * fix(cli): allow debug telemetry under opt-out env
2026-05-26 08:49:05 +02:00
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 {
driver: KtxConnectionDriver;
table: KtxTableRef;
quoteInput: string;
quotedIdentifier: string;
formattedTable: string;
display: string;
invalidDisplay: string;
columnDisplayTablePartCount: 1 | 2 | 3;
limitClause: string;
topClause: string;
randomFilter: string;
tableSampleClause: string;
sampleQuery: string;
columnSampleContains: string;
nullCountExpression: string;
distinctCountExpression: string;
textLengthExpression: string;
castToText: string;
sampleValueAggregation: string;
cardinalityContains: string;
randomizedCardinalityContains: string;
distinctValuesContains: string;
statisticsContains: string | null;
dimensionInput: string;
dimensionType: 'time' | 'string' | 'number' | 'boolean';
nativeTypeInput: string;
normalizedType: string;
}
const innerSampleSql = 'SELECT status AS value FROM orders';
const fixtures: DialectFixture[] = [
{
driver: 'postgres',
table: { catalog: null, db: 'public', name: 'orders' },
quoteInput: 'order"items',
quotedIdentifier: '"order""items"',
formattedTable: '"public"."orders"',
display: 'public.orders',
invalidDisplay: 'orders',
columnDisplayTablePartCount: 2,
limitClause: 'LIMIT 25 OFFSET 5',
topClause: '',
randomFilter: 'RANDOM() < 0.25',
tableSampleClause: 'TABLESAMPLE SYSTEM (25)',
sampleQuery: 'SELECT "id", "status" FROM "public"."orders" LIMIT 5',
columnSampleContains: 'TRIM(CAST("status" AS TEXT)) != \'\'',
nullCountExpression: 'COUNT(*) FILTER (WHERE "status" IS NULL)',
distinctCountExpression: 'COUNT(DISTINCT "status")',
textLengthExpression: 'LENGTH(CAST("status" AS TEXT))',
castToText: 'CAST("status" AS TEXT)',
sampleValueAggregation:
'(SELECT STRING_AGG(CAST(value AS TEXT), CHR(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 "status"::text AS val',
statisticsContains: 'FROM pg_stats s',
dimensionInput: 'timestamp with time zone',
dimensionType: 'time',
nativeTypeInput: 'numeric(12,2)',
normalizedType: 'numeric(12,2)',
},
{
driver: 'mysql',
table: { catalog: null, db: 'analytics', name: 'orders' },
quoteInput: 'order`items',
quotedIdentifier: '`order``items`',
formattedTable: '`analytics`.`orders`',
display: 'analytics.orders',
invalidDisplay: 'orders',
columnDisplayTablePartCount: 2,
limitClause: 'LIMIT 25 OFFSET 5',
topClause: '',
randomFilter: 'RAND() < 0.25',
tableSampleClause: '',
sampleQuery: 'SELECT `id`, `status` FROM `analytics`.`orders` LIMIT 5',
columnSampleContains: 'TRIM(CAST(`status` AS CHAR)) != \'\'',
nullCountExpression: 'SUM(CASE WHEN `status` IS NULL THEN 1 ELSE 0 END)',
distinctCountExpression: 'COUNT(DISTINCT `status`)',
textLengthExpression: 'CHAR_LENGTH(CAST(`status` AS CHAR))',
castToText: 'CAST(`status` AS CHAR)',
sampleValueAggregation:
'(SELECT GROUP_CONCAT(CAST(value AS CHAR) SEPARATOR CHAR(31)) 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 CAST(`status` AS CHAR) AS val',
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)',
normalizedType: 'varchar(255)',
},
{
driver: 'clickhouse',
table: { catalog: null, db: 'analytics', name: 'events' },
quoteInput: 'order`items',
quotedIdentifier: '`order``items`',
formattedTable: '`analytics`.`events`',
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>
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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
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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();
}
});
it('throws with a supported-driver list for unknown drivers', () => {
expect(() => getDialectForDriver('oracle')).toThrow(
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'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
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});
});