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test: reenabled tests removed in error
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tests/features/planets.feature

Lines changed: 27 additions & 27 deletions
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@@ -8,33 +8,33 @@ Feature: Pipeline tests using the planets dataset
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Some validation of entity attributes is performed: SQL expressions and Python filter
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functions are used, and templatable business rules feature in the transformations.
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# Scenario: Validate and filter planets (spark)
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# Given I submit the planets file planets_demo.csv for processing
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# And A spark pipeline is configured
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# And I add initial audit entries for the submission
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# Then the latest audit record for the submission is marked with processing status file_transformation
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# When I run the file transformation phase
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# Then the planets entity is stored as a parquet after the file_transformation phase
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# And the latest audit record for the submission is marked with processing status data_contract
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# When I run the data contract phase
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# Then there is 1 record rejection from the data_contract phase
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# And the planets entity is stored as a parquet after the data_contract phase
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# And the latest audit record for the submission is marked with processing status business_rules
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# When I run the business rules phase
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# Then The rules restrict "planets" to 1 qualifying record
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# And At least one row from "planets" has generated error code "HIGH_DENSITY"
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# And At least one row from "planets" has generated error code "WEAK_ESCAPE"
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# And the planets entity is stored as a parquet after the business_rules phase
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# And the latest audit record for the submission is marked with processing status error_report
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# When I run the error report phase
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# Then An error report is produced
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# And The entity "planets" does not contain an entry for "Jupiter" in column "planet"
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# And The entity "planets" contains an entry for "Neptune" in column "planet"
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# And The statistics entry for the submission shows the following information
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# | parameter | value |
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# | record_count | 9 |
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# | number_record_rejections | 18 |
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# | number_warnings | 0 |
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Scenario: Validate and filter planets (spark)
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Given I submit the planets file planets_demo.csv for processing
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And A spark pipeline is configured
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And I add initial audit entries for the submission
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Then the latest audit record for the submission is marked with processing status file_transformation
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When I run the file transformation phase
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Then the planets entity is stored as a parquet after the file_transformation phase
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And the latest audit record for the submission is marked with processing status data_contract
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When I run the data contract phase
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Then there is 1 record rejection from the data_contract phase
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And the planets entity is stored as a parquet after the data_contract phase
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And the latest audit record for the submission is marked with processing status business_rules
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When I run the business rules phase
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Then The rules restrict "planets" to 1 qualifying record
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And At least one row from "planets" has generated error code "HIGH_DENSITY"
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And At least one row from "planets" has generated error code "WEAK_ESCAPE"
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And the planets entity is stored as a parquet after the business_rules phase
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And the latest audit record for the submission is marked with processing status error_report
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When I run the error report phase
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Then An error report is produced
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And The entity "planets" does not contain an entry for "Jupiter" in column "planet"
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And The entity "planets" contains an entry for "Neptune" in column "planet"
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And The statistics entry for the submission shows the following information
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| parameter | value |
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| record_count | 9 |
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| number_record_rejections | 18 |
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| number_warnings | 0 |
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Scenario: Handle a file with no extension provided (spark)
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Given I submit the planets file planets_no_extension for processing

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