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