Fix to increase the maximum allowed string length with Object Storage

[KodaiD]

Description

This PR fixes the JSON serializer to increase Jackson stream read constraints, enabling the handling of large data in Object Storage adapter.

Currently, when storing a record with large data (e.g., 100MiB), Object Storage adapter fails to get the record due to the following error:

Caused by: com.fasterxml.jackson.databind.JsonMappingException: String value length (20054016) exceeds the maximum allowed (20000000, from `StreamReadConstraints.getMaxStringLength()`) (through reference chain: 

To allow handling of large data, the PR increases the maximum allowed string length in Jackson's stream read constraints. Also, the validation that checks if the string length exceeds the maximum allowed length or not is added to the write side to prevent storing data that cannot be read back.

Related issues and/or PRs

N/A

Changes made

• Updated he JSON serializer to increase Jackson stream read constraints.
• Added validation on the write side to prevent storing data that cannot be read back.

Checklist

• I have commented my code, particularly in hard-to-understand areas.
• I have updated the documentation to reflect the changes.
• I have considered whether similar issues could occur in other products, components, or modules if this PR is for bug fixes.
• Any remaining open issues linked to this PR are documented and up-to-date (Jira, GitHub, etc.).
• Tests (unit, integration, etc.) have been added for the changes.
• My changes generate no new warnings.
• Any dependent changes in other PRs have been merged and published.

Additional notes (optional)

N/A

Release notes

Fix to increase the maximum allowed string length with Object Storage.

[gemini-code-assist]

Summary of Changes

Hello @KodaiD, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request resolves an issue where the Object Storage adapter failed to retrieve records containing large data due to strict string length constraints in the Jackson JSON serializer. By significantly increasing this limit and introducing a proactive validation step during data writes, the system can now reliably handle and store larger data payloads, preventing potential read failures and ensuring data integrity.

Highlights

• Increased Jackson String Length Limit: The maximum allowed string length for Jackson's stream reading has been significantly increased to Integer.MAX_VALUE to accommodate larger data payloads during deserialization.
• Write-Side Validation for Large Values: New validation logic has been introduced in ObjectStorageOperationChecker to prevent TextColumn and BlobColumn values from being written if their serialized length (including Base64 encoding for blobs) exceeds the newly defined MAX_STRING_LENGTH_ALLOWED.
• New Error Code for Exceeded Lengths: A specific error, OBJECT_STORAGE_EXCEEDS_MAX_VALUE_LENGTH_ALLOWED, has been added to CoreError.java to clearly indicate when column values exceed the maximum allowed size during write operations.
• Enhanced Test Coverage: Unit tests have been added to ObjectStorageOperationCheckerTest to verify the new write-side validation for TextColumn and BlobColumn. Additionally, an integration test in DistributedStorageIntegrationTestBase confirms the proper storage and retrieval of large text values.

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[gemini-code-assist]

Code Review

This pull request successfully addresses the issue of handling large data in the Object Storage adapter by increasing Jackson's stream read constraints and adding corresponding write-side validation. The changes are logical and well-tested with both unit and integration tests. I have a few suggestions to improve the robustness and performance of the implementation. My main feedback is to replace assert statements with explicit null checks to prevent potential NullPointerExceptions at runtime. Additionally, I've suggested an optimization for an integration test to improve its performance when handling large data.

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