feat: implement external source sensor ZIP-726 #967

tchow-zlai · 2025-07-15T20:44:56Z

Summary

Complement to https://github.com/zipline-ai/platform/pull/81

Checklist

Added Unit Tests
Covered by existing CI
Integration tested
Documentation update

Summary by CodeRabbit

New Features
- Added support for external source sensor nodes to verify required data partitions with configurable retries.
- Enhanced error handling and logging for missing partitions, improving process reliability and transparency.

coderabbitai · 2025-07-15T20:45:02Z

Walkthrough

The BatchNodeRunner was updated to support the EXTERNAL_SOURCE_SENSOR node type by adding logic to check for required partitions in an external source table, including retry behavior. A new private method handles partition checks, and the main run method now processes this node type with success or failure exit codes.

Changes

File	Change Summary
spark/.../BatchNodeRunner.scala	Added support for `EXTERNAL_SOURCE_SENSOR` node: new private `checkPartitions` method, updated `run` to handle this node type with partition checking and retry logic.
spark/.../BatchNodeRunnerTest.scala	Added tests for `checkPartitions` covering success, failure, retry behavior, and error cases.

Sequence Diagram(s)

sequenceDiagram
    participant User
    participant BatchNodeRunner
    participant MetaData
    participant TableUtils

    User->>BatchNodeRunner: run(metadata, conf, range, tableUtils)
    alt conf is EXTERNAL_SOURCE_SENSOR
        BatchNodeRunner->>BatchNodeRunner: checkPartitions(conf, metadata, tableUtils, range)
        BatchNodeRunner->>MetaData: get partition spec for table
        BatchNodeRunner->>TableUtils: verify partitions exist
        alt partitions missing & retries left
            BatchNodeRunner->>BatchNodeRunner: wait retryInterval, retry
        end
        alt all partitions exist
            BatchNodeRunner-->>User: exit(0)
        else retries exhausted
            BatchNodeRunner-->>User: log error, exit(1)
        end
    else
        BatchNodeRunner->>User: handle other node types (unchanged)
    end

Estimated code review effort

2 (~20 minutes)

Possibly related PRs

feat: rename to externalsourcesensor node #937: Renamed struct and union field to ExternalSourceSensorNode, which this PR now supports.
feat: Add retry properties to the external sensor #983: Added retryCount and retryIntervalMin fields used in the new retry logic.
feat: batch node runner #870: Initial BatchNodeRunner implementation; this PR extends it for a new node type.

Suggested reviewers

nikhil-zlai
varant-zlai
chewy-zlai
david-zlai

Poem

In the land of nodes, a sensor awakes,
Checking partitions for all our sakes.
With retries and logs, it bravely persists,
Until every partition exists!
BatchNodeRunner, you scan and you strive—
Ensuring our data jobs always survive.
🚦✨

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coderabbitai

Actionable comments posted: 0

🧹 Nitpick comments (1)

spark/src/main/scala/ai/chronon/spark/batch/BatchNodeRunner.scala (1)
56-71: Consider error handling for missing table in metadata.

The find() operation could return None if the table isn't found in tableDependencies, leading to spec = None. While tableUtils.partitions() accepts Option[PartitionSpec], consider logging a warning when the table isn't found in metadata.
        val spec = metadata.executionInfo.tableDependencies.asScala
          .find(_.tableInfo.table == tableName)
          .map(_.tableInfo.partitionSpec(tableUtils.partitionSpec))
+        if (spec.isEmpty) {
+          logger.warn(s"Table ${tableName} not found in metadata dependencies")
+        }

📜 Review details

Configuration used: CodeRabbit UI
Review profile: CHILL
Plan: Pro

📥 Commits

Reviewing files that changed from the base of the PR and between 848f913 and 2d05dd3.

📒 Files selected for processing (1)

spark/src/main/scala/ai/chronon/spark/batch/BatchNodeRunner.scala (2 hunks)

🧰 Additional context used

🧬 Code Graph Analysis (1)

spark/src/main/scala/ai/chronon/spark/batch/BatchNodeRunner.scala (1)

api/src/main/scala/ai/chronon/api/Extensions.scala (1)

partitionSpec (1206-1211)

⏰ Context from checks skipped due to timeout of 90000ms. You can increase the timeout in your CodeRabbit configuration to a maximum of 15 minutes (900000ms). (9)

GitHub Check: scala_compile_fmt_fix
GitHub Check: analyzer_tests
GitHub Check: groupby_tests
GitHub Check: streaming_tests
GitHub Check: join_tests
GitHub Check: batch_tests
GitHub Check: fetcher_tests
GitHub Check: spark_tests
GitHub Check: enforce_triggered_workflows

🔇 Additional comments (1)

spark/src/main/scala/ai/chronon/spark/batch/BatchNodeRunner.scala (1)

144-144: LGTM on metadata extraction.

Follows the established pattern for other node content types.

coderabbitai

Actionable comments posted: 1

📜 Review details

Configuration used: CodeRabbit UI
Review profile: CHILL
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📥 Commits

Reviewing files that changed from the base of the PR and between 66af081 and 40854bf.

📒 Files selected for processing (1)

spark/src/main/scala/ai/chronon/spark/batch/BatchNodeRunner.scala (3 hunks)

🧠 Learnings (1)

spark/src/main/scala/ai/chronon/spark/batch/BatchNodeRunner.scala (11)

Learnt from: piyush-zlai
PR: #33
File: cloud_aws/src/main/scala/ai/chronon/integrations/aws/DynamoDBKVStoreImpl.scala:29-30
Timestamp: 2024-10-08T16:18:45.669Z
Learning: In the codebase, the KVStore implementation provides an implicit ExecutionContext in scope, so it's unnecessary to import another.

Learnt from: chewy-zlai
PR: #50
File: spark/src/test/scala/ai/chronon/spark/test/MockKVStore.scala:19-28
Timestamp: 2024-10-31T18:29:45.027Z
Learning: In MockKVStore located at spark/src/test/scala/ai/chronon/spark/test/MockKVStore.scala, the multiPut method is intended to be a simple implementation without dataset existence validation, duplicate validation logic elimination, or actual storage of key-value pairs for verification.

Learnt from: nikhil-zlai
PR: #70
File: service/src/main/java/ai/chronon/service/ApiProvider.java:6-6
Timestamp: 2024-12-03T04:04:33.809Z
Learning: The import scala.util.ScalaVersionSpecificCollectionsConverter in service/src/main/java/ai/chronon/service/ApiProvider.java is correct and should not be flagged in future reviews.

Learnt from: chewy-zlai
PR: #62
File: spark/src/main/scala/ai/chronon/spark/stats/drift/SummaryUploader.scala:9-10
Timestamp: 2024-11-06T21:54:56.160Z
Learning: In Spark applications, when defining serializable classes, passing an implicit ExecutionContext parameter can cause serialization issues. In such cases, it's acceptable to use scala.concurrent.ExecutionContext.Implicits.global.

Learnt from: chewy-zlai
PR: #47
File: online/src/main/scala/ai/chronon/online/MetadataStore.scala:232-0
Timestamp: 2024-10-17T00:12:09.763Z
Learning: In the KVStore trait located at online/src/main/scala/ai/chronon/online/KVStore.scala, there are two create methods: def create(dataset: String): Unit and def create(dataset: String, props: Map[String, Any]): Unit. The version with props ignores the props parameter, and the simpler version without props is appropriate when props are not needed.

Learnt from: piyush-zlai
PR: #33
File: cloud_aws/src/test/scala/ai/chronon/integrations/aws/DynamoDBKVStoreTest.scala:175-175
Timestamp: 2024-10-07T15:09:51.567Z
Learning: Hardcoding future timestamps in tests within DynamoDBKVStoreTest.scala is acceptable when data is generated and queried within the same time range, ensuring the tests remain valid over time.

Learnt from: piyush-zlai
PR: #44
File: hub/app/store/DynamoDBMonitoringStore.scala:98-143
Timestamp: 2024-10-15T15:30:15.514Z
Learning: In the Scala file hub/app/store/DynamoDBMonitoringStore.scala, within the makeLoadedConfs method, the .recover method is correctly applied to the Try returned by response.values to handle exceptions from the underlying store.

Learnt from: piyush-zlai
PR: #33
File: online/src/main/scala/ai/chronon/online/Api.scala:69-69
Timestamp: 2024-10-07T15:21:50.787Z
Learning: In the KVStore trait located at online/src/main/scala/ai/chronon/online/Api.scala, the default implementation of the create method (def create(dataset: String, props: Map[String, Any]): Unit = create(dataset)) doesn't leverage the props parameter, but subclasses like DynamoDBKVStoreImpl use the props parameter in their overridden implementations.

Learnt from: piyush-zlai
PR: #33
File: online/src/main/scala/ai/chronon/online/Api.scala:69-69
Timestamp: 2024-10-08T16:18:45.669Z
Learning: In the KVStore trait located at online/src/main/scala/ai/chronon/online/Api.scala, the default implementation of the create method (def create(dataset: String, props: Map[String, Any]): Unit = create(dataset)) doesn't leverage the props parameter, but subclasses like DynamoDBKVStoreImpl use the props parameter in their overridden implementations.

Learnt from: piyush-zlai
PR: #53
File: hub/app/controllers/TimeSeriesController.scala:224-224
Timestamp: 2024-10-29T15:21:58.102Z
Learning: In the mocked data implementation in hub/app/controllers/TimeSeriesController.scala, potential NumberFormatException exceptions due to parsing errors (e.g., when using val featureId = name.split("_").last.toInt) are acceptable and will be addressed when adding the concrete backend.

Learnt from: tchow-zlai
PR: #263
File: cloud_gcp/src/main/scala/ai/chronon/integrations/cloud_gcp/BigQueryFormat.scala:29-60
Timestamp: 2025-01-24T23:55:30.256Z
Learning: In BigQuery integration, table existence check is performed outside the BigQueryFormat.createTable method, at a higher level in TableUtils.createTable.