[SPARK-54403][SQL][Metric View] Add YAML serde infrastructure for metric views #53146
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… for metric views This commit adds the complete serialization/deserialization infrastructure for parsing metric view YAML definitions: - Add Jackson YAML dependencies to pom.xml - Implement canonical model for metric views: - Column, Expression (Dimension/Measure), MetricView, Source - YAMLVersion validation and exception types - Implement version-specific serde (v0.1): - YAML deserializer/serializer - Base classes for extensibility - Add JSON utilities for metadata serialization
pan3793
reviewed
Nov 21, 2025
pom.xml
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| <dependency> | ||
| <groupId>com.fasterxml.jackson.dataformat</groupId> | ||
| <artifactId>jackson-dataformat-yaml</artifactId> | ||
| <version>${fasterxml.jackson.version}</version> |
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all jackson deps are managed by jackson-bom now, you don't need to declare it again here
LuciferYang
reviewed
Nov 21, 2025
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| object JsonUtils { | ||
| // Singleton ObjectMapper that can be used across the project | ||
| private lazy val mapper: ObjectMapper = { |
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According to the comments, should we try to use this singleton as much as possible in the subsequent development?
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Yes, I'm surprised that there is no such util in the Spark repo. For now, I plan to use it for all the metric view development, but not sure how much other code needs this.
LuciferYang
reviewed
Nov 21, 2025
| // Only parse the "version" field and ignore all others | ||
| @JsonIgnoreProperties(ignoreUnknown = true) | ||
| case class YAMLVersion(version: String) extends Validatable { | ||
| def validYAMLVersions: Set[String] = Set("0.1") |
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Suggested change
| def validYAMLVersions: Set[String] = Set("0.1") | |
| private def validYAMLVersions: Set[String] = Set("0.1") |
LuciferYang
reviewed
Nov 21, 2025
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| val mapper = new ObjectMapper(yamlFactory) | ||
| // Exclude null values from serialized output | ||
| .setSerializationInclusion(JsonInclude.Include.NON_NULL) |
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| .setSerializationInclusion(JsonInclude.Include.NON_NULL) | |
| . setDefaultPropertyInclusion(JsonInclude.Include.NON_NULL) |
LuciferYang
reviewed
Nov 21, 2025
| // Exclude null values from serialized output | ||
| .setSerializationInclusion(JsonInclude.Include.NON_NULL) | ||
| // Exclude empty collections/strings from serialized output | ||
| .setSerializationInclusion(JsonInclude.Include.NON_EMPTY) |
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| .setSerializationInclusion(JsonInclude.Include.NON_EMPTY) | |
| . setDefaultPropertyInclusion(JsonInclude.Include.NON_EMPTY) |
LuciferYang
reviewed
Nov 21, 2025
| ) extends ColumnBase | ||
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| object ColumnV01 { | ||
| def fromCanonical(canonical: Column[_ <: Expression], ordinal: Int): ColumnV01 = { |
LuciferYang
reviewed
Nov 21, 2025
| Try(CatalystSqlParser.parseQuery(sourceText)) match { | ||
| case Success(_) => SQLSource(sourceText) | ||
| case Failure(queryEx) => | ||
| throw queryEx |
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Should queryEx be wrapped into MetricViewValidationException?
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cc @cloud-fan to review |
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What changes were proposed in this pull request?
This PR adds the complete serialization/deserialization infrastructure for parsing metric view YAML definitions:
Why are the changes needed?
SPIP: Metrics & semantic modeling in Spark
Does this PR introduce any user-facing change?
No
How was this patch tested?
Was this patch authored or co-authored using generative AI tooling?
Generated-by: Claude Code
Co-Authored-By: Claude [email protected]