21af36a591
Profiler: - pg/mysql: table-level metrics via DB statistics (exact-ish row counts) only; source tables hold 24-53M rows and OM's column profiler full-scans per column (no TABLESAMPLE pushdown), which would hammer the live CDC source. - trino/iceberg: full column metrics + sample data on the small (20-25k row) curated_masked + hadoop tables. Data quality: 16 test cases across 5 tables (row counts on big sources; row count + uniqueness/not-null/range on curated/masked + historical), all passing. This populates OM's Data Quality dashboard (coverage, healthy assets, dimensions, test results).
41 lines
1.1 KiB
YAML
41 lines
1.1 KiB
YAML
source:
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type: postgres
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serviceName: atc_postgres
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serviceConnection:
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config:
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type: Postgres
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username: mo
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authType:
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password: Dell2026!
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hostPort: 10.0.21.51:5432
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database: postgres
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# Hard server-side cap so no profiler query can run away on huge tables.
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connectionArguments:
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options: "-c statement_timeout=90000"
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sourceConfig:
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config:
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type: Profiler
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# Table-level metrics from DB statistics only. The source tables hold tens
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# of millions of rows; OM's column profiler full-scans per column (it does
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# not push down TABLESAMPLE), which would hammer the live CDC source. Row
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# counts come from pg_class stats instantly.
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computeTableMetrics: true
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computeColumnMetrics: false
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useStatistics: true
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threadCount: 5
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schemaFilterPattern:
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includes:
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- public
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processor:
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type: orm-profiler
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config: {}
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sink:
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type: metadata-rest
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config: {}
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workflowConfig:
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openMetadataServerConfig:
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hostPort: http://openmetadata-server:8585/api
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authProvider: openmetadata
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securityConfig:
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jwtToken: "__JWT__"
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