HuangZhenQiu commented on code in PR #19046:
URL: https://github.com/apache/hudi/pull/19046#discussion_r3562735890


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rfc/rfc-107/rfc-107.md:
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+# RFC-107: Dynamic Partitioned Cache for Flink Hudi Upsert
+
+## Proposers
+
+- @zhenqiu-huang
+
+## Approvers
+ - TBD
+
+## Status
+ - In Progress
+
+## Abstract
+
+[RFC-106](../rfc-106/rfc-106.md) introduces Record Level Index (RLI) support 
for Flink streaming writes, including a simple in-memory cache for index 
lookups in the `BucketAssigner` operator. While the in-memory cache works well 
for small to moderate workloads, it faces scalability challenges for large 
tables with billions of records: the cache either consumes excessive JVM heap 
memory or suffers from high eviction rates that degrade lookup performance.
+In modern CloudLake systems that rely on object storage platforms such as GCS, 
OCI Object Storage, and Amazon S3, data is typically transitioned to lower 
storage tiers over time to optimize storage costs. However, using an in-memory 
cache to accelerate index lookups may result in increased data processing 
overhead.
+
+This RFC proposes a **Dynamic Partitioned Cache** backed by RocksDB that 
serves as a local materialized replica of the MDT RLI. The cache provides:
+
+- **O(1) local lookups** for record location resolution during streaming 
writes, eliminating per-record MDT I/O

Review Comment:
   To make the flink ingestion continuously run, we probably don't do 
clustering on MOR table. But still If there is data rewrite needs for data 
security concern, we probably need to consider a policy to minimize the 
concurrent writer on partitions. 



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