ktx/packages/cli/test/connectors/snowflake/dialect.test.ts

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import { describe, expect, it } from 'vitest';
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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import { KtxSnowflakeDialect } from '../../../src/connectors/snowflake/dialect.js';
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describe('KtxSnowflakeDialect', () => {
const dialect = new KtxSnowflakeDialect();
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it('quotes identifiers and formats database.schema.table names', () => {
expect(dialect.quoteIdentifier('order"items')).toBe('"order""items"');
expect(dialect.formatTableName({ catalog: 'ANALYTICS', db: 'PUBLIC', name: 'ORDERS' })).toBe(
'"ANALYTICS"."PUBLIC"."ORDERS"',
);
expect(dialect.formatTableName({ db: 'PUBLIC', name: 'ORDERS' })).toBe('"PUBLIC"."ORDERS"');
expect(dialect.formatTableName({ name: 'ORDERS' })).toBe('"ORDERS"');
});
it('maps native Snowflake types to scan dimensions', () => {
expect(dialect.mapDataType('NUMBER(38,0)')).toBe('NUMBER(38,0)');
expect(dialect.mapToDimensionType('TIMESTAMP_NTZ')).toBe('time');
expect(dialect.mapToDimensionType('NUMBER(38,0)')).toBe('number');
expect(dialect.mapToDimensionType('BOOLEAN')).toBe('boolean');
expect(dialect.mapToDimensionType('VARIANT')).toBe('string');
});
it('generates sampling and dictionary SQL', () => {
expect(dialect.generateSampleQuery('"PUBLIC"."ORDERS"', 5, ['ID', 'STATUS'])).toBe(
'SELECT "ID", "STATUS" FROM "PUBLIC"."ORDERS" SAMPLE ROW (5 ROWS)',
);
expect(dialect.generateColumnSampleQuery('"PUBLIC"."ORDERS"', 'STATUS', 10)).toBe(
'SELECT "STATUS" FROM "PUBLIC"."ORDERS" WHERE "STATUS" IS NOT NULL AND TRIM(CAST("STATUS" AS STRING)) != \'\' LIMIT 10',
);
expect(dialect.generateCardinalitySampleQuery('"PUBLIC"."ORDERS"', '"STATUS"', 100)).toContain(
'SELECT COUNT(DISTINCT val) AS cardinality',
);
expect(dialect.generateDistinctValuesQuery('"PUBLIC"."ORDERS"', '"STATUS"', 20)).toContain(
'SELECT DISTINCT "STATUS"::VARCHAR AS val',
);
});
it('keeps unsupported statistics explicit', () => {
expect(dialect.generateColumnStatisticsQuery('PUBLIC', 'ORDERS')).toBeNull();
});
});