mirror of
https://github.com/Kaelio/ktx.git
synced 2026-06-07 07:55:13 +02:00
* 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
316 lines
14 KiB
TypeScript
316 lines
14 KiB
TypeScript
import { describe, expect, it } from 'vitest';
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import { getDialectForDriver } 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: null,
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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 KtxDialect for $driver', (fixture) => {
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const dialect = getDialectForDriver(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 warehouse driver "oracle". Supported drivers: bigquery, clickhouse, mysql, postgres, sqlite, snowflake, 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 warehouse driver "postgresql"');
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expect(() => getDialectForDriver('sqlite3')).toThrow('Unsupported warehouse driver "sqlite3"');
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});
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});
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