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* refactor(connectors): split KtxDialect into core and KtxSqlDialect Separate the dialect contract into a driver-agnostic core (display/ref formatting and type mapping) and a SQL-only extension (query generators). The catalog and entity-details paths resolve the core dialect for any snapshot driver, so it must stay free of SQL generation; this is the prerequisite refactor for adding non-SQL primary sources. - KtxDialect keeps type, formatDisplayRef, parseDisplayRef, columnDisplayTablePartCount, mapDataType, mapToDimensionType - KtxSqlDialect extends it with quoteIdentifier, formatTableName, and the query/sample/statistics generators; the 7 SQL dialects implement it - add getSqlDialectForDriver for SQL drivers; the 7 connectors and the relationship-benchmark harness consume it - thread the relationship pipeline (profiling/validation/composite/ discovery) as KtxSqlDialect | null so a non-SQL source skips coverage SQL and its candidates stay in review; local-enrichment builds the SQL dialect only when the connector advertises readOnlySql Pure extraction: no behavior change for the existing 7 drivers. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * feat(connectors): add MongoDB connector for issue #305 Add a read-only MongoDB connector that treats a database as a primary context source: collections map to tables and inferred top-level fields to columns. MongoDB is the first non-SQL source (readOnlySql: false), so ktx sql and metric compilation do not apply, but its collections flow through ingest, descriptions, and relationship discovery. - schema-inference: infer a flat column schema from the most recent sample_size documents (by _id desc, or order_by for non-ObjectId keys). Union BSON types per field, mark multi-type fields mixed (string), keep sub-documents/arrays as a single opaque json column, derive nullability from presence, treat _id as the primary key - connector: KtxMongoDbScanConnector behind an injectable client seam; strictly read-only (find/listCollections/estimatedDocumentCount only), no executeReadOnly; resolves env:/file: via resolveKtxConfigReference - core-only KtxMongoDbDialect and a live-database introspection adapter - wire the mongodb driver: driver union, dialect registry, driver registration (scopeConfigKey databases), mongodbConnectionSchema, connection-drivers, normalizeDriver, the live-database route, and the ktx setup picker. ktx sql is refused by the read-only SQL capability gate - tests: schema inference, connector snapshot via a fake client, dialect, driver-schema parsing, and the ktx sql rejection Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * docs(integrations): document the MongoDB primary source Add a MongoDB section to the primary-sources reference: connection config (url, databases, enabled_tables, sample_size, order_by), mongodb+srv/TLS/ Atlas notes, the schema-inference explainer, a features matrix, and the non-SQL caveat. Update the frontmatter and connection field reference. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * fix(connectors): address review blockers on the MongoDB connector - introspect: skip estimatedDocumentCount for views. The count command is rejected on a MongoDB view (CommandNotSupportedOnView), so counting a view aborted introspect for the whole connection; compute estimatedRows only for real collections, as ClickHouse does. - sl: refuse a semantic-layer query against a non-SQL connection instead of defaulting it to the Postgres dialect. compileLocalSlQuery (the shared CLI + MCP path) now rejects a driver with no SQL dialect via the new isSqlQueryableDriver authority, keeping MongoDB context-only per issue #305. - tests: cover input.tableScope and the empty-scope skip for the Mongo connector (the scan layer does not post-filter), the view no-count path, and the ktx sl query refusal for a mongodb connection. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * polish(mongodb): compute sampled nullCount and document sampling caveats Address the non-blocking review notes: - sampleColumn now counts null/absent values over the sampled window instead of returning nullCount: null, since the documents are already in hand - warn that a custom order_by must be indexed (an unindexed sort hits MongoDB's in-memory sort limit on large collections) in the connection schema and docs - note that sampled values for nested fields are stringified, not faithfully serialized, so the json opacity is deliberate Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * docs(examples): add a MongoDB connector example A manual, container-backed example mirroring examples/postgres-historic: - docker-compose.yml + init/seed.js seed a representative dataset (nested documents, arrays, a Decimal128, a mixed-type field, a nullable field, an ObjectId reference, and a view) on first container start - scripts/smoke.sh + introspect-smoke.mjs assert the connector's inferred schema with no LLM credentials — the same introspection entry point ktx ingest's database-schema stage uses, including the view-no-count path - README.md documents the smoke and a full keyless ktx ingest run (claude-code LLM + managed sentence-transformers embeddings) Works with Docker Compose or podman compose. Verified end to end. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * chore: ignore examples/** in knip to fix dead-code false positives The MongoDB connector example files (examples/mongodb/init/seed.js and examples/mongodb/scripts/introspect-smoke.mjs) are used at runtime but were flagged as unused by knip. Add examples/** to the ignore array, matching the existing .context/** entry. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_0114qQV8fJ5a5ME3XbMVRzbL * fix(mongodb): refuse non-SQL connections before SQL analysis `ktx sql` and the MCP sql_execution tool resolved a SQL-analysis dialect (falling back to Postgres for a non-SQL driver) and ran read-only validation before the connector capability gate refused the connection. For a MongoDB connection that spun up the parser/daemon and produced Postgres parser diagnostics instead of a clean non-SQL refusal. Route both entry points through a shared assertSqlQueryableConnection guard before dialect selection, mirroring compileLocalSlQuery. The federated duckdb path has no driver and is exempted at each call site. Add CLI and MCP regression tests asserting validation/connector work never starts for a MongoDB connection. * fix(mongodb): pass CI gates (dialect boundary, secrets, setup test) Three latent failures in the connector surfaced once CI ran on the branch: - connector.ts imported the concrete KtxMongoDbDialect, which the connector dialect-import boundary forbids. Route it through getDialectForDriver('mongodb') and widen inferKtxMongoCollectionColumns to the base KtxDialect (it only uses mapDataType/mapToDimensionType). - detect-secrets flagged a test ObjectId hex and the mongodb+srv example URL; annotate both with allowlist pragmas. - the "shows every supported database" setup test omitted the new MongoDB option. --------- Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Co-authored-by: Luca Martial <48870843+luca-martial@users.noreply.github.com> Co-authored-by: Luca Martial <lucamrtl@gmail.com> Co-authored-by: Andrey Avtomonov <andreybavt@gmail.com>
210 lines
6.1 KiB
TypeScript
210 lines
6.1 KiB
TypeScript
import type { KtxSqlDialect } from '../../context/connections/dialects.js';
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import {
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columnDisplayPartCount,
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formatDialectDisplayRef,
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formatDialectTableName,
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limitOffsetClause,
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parseDialectDisplayRef,
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} from '../../context/connections/dialect-helpers.js';
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import type { KtxSchemaDimensionType, KtxTableRef } from '../../context/scan/types.js';
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type PostgresTableNameRef = Pick<KtxTableRef, 'name'> & Partial<Pick<KtxTableRef, 'catalog' | 'db'>>;
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/** @internal */
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export class KtxPostgresDialect implements KtxSqlDialect {
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readonly type = 'postgres' as const;
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private readonly typeMappings: Record<string, KtxSchemaDimensionType> = {
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timestamp: 'time',
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'timestamp without time zone': 'time',
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'timestamp with time zone': 'time',
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timestamptz: 'time',
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datetime: 'time',
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date: 'time',
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time: 'time',
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integer: 'number',
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int: 'number',
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int2: 'number',
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int4: 'number',
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int8: 'number',
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bigint: 'number',
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smallint: 'number',
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decimal: 'number',
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numeric: 'number',
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float: 'number',
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float4: 'number',
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float8: 'number',
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'double precision': 'number',
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real: 'number',
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money: 'number',
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text: 'string',
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varchar: 'string',
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'character varying': 'string',
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char: 'string',
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character: 'string',
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uuid: 'string',
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json: 'string',
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jsonb: 'string',
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boolean: 'boolean',
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bool: 'boolean',
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};
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quoteIdentifier(identifier: string): string {
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return `"${identifier.replace(/"/g, '""')}"`;
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}
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formatTableName(table: PostgresTableNameRef): string {
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return formatDialectTableName(table, this.quoteIdentifier.bind(this), 'ansi');
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}
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formatDisplayRef(table: PostgresTableNameRef): string {
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return formatDialectDisplayRef(table, 'ansi');
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}
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parseDisplayRef(display: string): KtxTableRef | null {
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return parseDialectDisplayRef(display, 'ansi');
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}
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columnDisplayTablePartCount(): 1 | 2 | 3 {
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return columnDisplayPartCount('ansi');
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}
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mapDataType(nativeType: string): string {
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return nativeType;
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}
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mapToDimensionType(nativeType: string): KtxSchemaDimensionType {
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if (!nativeType) {
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return 'string';
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}
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const lower = nativeType.toLowerCase().trim();
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const normalized = lower.includes('(') ? lower.split('(')[0]!.trim() : lower;
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if (this.typeMappings[normalized]) {
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return this.typeMappings[normalized];
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}
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if (normalized.includes('time') || normalized.includes('date')) {
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return 'time';
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}
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if (
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normalized.includes('int') ||
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normalized.includes('num') ||
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normalized.includes('dec') ||
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normalized.includes('float') ||
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normalized.includes('double')
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) {
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return 'number';
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}
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if (normalized.includes('bool')) {
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return 'boolean';
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}
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return 'string';
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}
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generateSampleQuery(tableName: string, limit: number, columns?: string[]): string {
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const columnList =
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columns && columns.length > 0 ? columns.map((column) => this.quoteIdentifier(column)).join(', ') : '*';
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return `SELECT ${columnList} FROM ${tableName} LIMIT ${limit}`;
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}
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generateColumnSampleQuery(tableName: string, columnName: string, limit: number): string {
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const quotedColumn = this.quoteIdentifier(columnName);
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return `SELECT ${quotedColumn} FROM ${tableName} WHERE ${quotedColumn} IS NOT NULL AND TRIM(CAST(${quotedColumn} AS TEXT)) != '' LIMIT ${limit}`;
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}
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getRandomSampleFilter(samplePct: number): string {
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if (samplePct <= 0 || samplePct >= 1) {
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return '';
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}
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return `RANDOM() < ${samplePct}`;
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}
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getTableSampleClause(samplePct: number): string {
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if (samplePct <= 0 || samplePct >= 1) {
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return '';
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}
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return `TABLESAMPLE SYSTEM (${samplePct * 100})`;
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}
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getLimitOffsetClause(limit: number, offset?: number): string {
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return limitOffsetClause(limit, offset);
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}
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getTopClause(_limit: number): string {
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return '';
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}
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getNullCountExpression(column: string): string {
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return `COUNT(*) FILTER (WHERE ${column} IS NULL)`;
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}
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getDistinctCountExpression(column: string): string {
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return `COUNT(DISTINCT ${column})`;
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}
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textLengthExpression(columnSql: string): string {
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return `LENGTH(CAST(${columnSql} AS TEXT))`;
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}
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castToText(columnSql: string): string {
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return `CAST(${columnSql} AS TEXT)`;
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}
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getSampleValueAggregation(innerSql: string): string {
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return `(SELECT STRING_AGG(CAST(value AS TEXT), CHR(31)) FROM (${innerSql}) AS relationship_profile_values)`;
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}
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generateCardinalitySampleQuery(tableName: string, columnName: string, sampleSize: number): string {
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return `
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WITH sampled AS (
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SELECT ${columnName} AS val
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FROM ${tableName}
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WHERE ${columnName} IS NOT NULL
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LIMIT ${sampleSize}
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)
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SELECT COUNT(DISTINCT val) AS cardinality
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FROM sampled
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`;
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}
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generateDistinctValuesQuery(tableName: string, columnName: string, limit: number): string {
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return `
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SELECT DISTINCT ${columnName}::text AS val
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FROM ${tableName}
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WHERE ${columnName} IS NOT NULL
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ORDER BY val
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LIMIT ${limit}
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`;
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}
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generateColumnStatisticsQuery(schemaName: string, tableName: string): string | null {
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return `
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SELECT
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s.attname AS column_name,
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CASE
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WHEN s.n_distinct > 0 THEN s.n_distinct::bigint
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WHEN s.n_distinct < 0 THEN (-s.n_distinct * c.reltuples)::bigint
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ELSE NULL
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END AS estimated_cardinality
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FROM pg_stats s
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JOIN pg_class c ON c.relname = s.tablename
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JOIN pg_namespace n ON c.relnamespace = n.oid AND n.nspname = s.schemaname
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WHERE s.schemaname = '${schemaName.replace(/'/g, "''")}'
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AND s.tablename = '${tableName.replace(/'/g, "''")}'
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AND s.n_distinct IS NOT NULL
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`;
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}
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generateRandomizedCardinalitySampleQuery(tableName: string, columnName: string, sampleSize: number): string {
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return `
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WITH sampled AS (
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SELECT ${columnName} AS val
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FROM ${tableName}
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WHERE ${columnName} IS NOT NULL
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ORDER BY RANDOM()
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LIMIT ${sampleSize}
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)
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SELECT COUNT(DISTINCT val) AS cardinality
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FROM sampled
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`;
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}
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}
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