zhangyue19921010 commented on code in PR #12514:
URL: https://github.com/apache/hudi/pull/12514#discussion_r1893757478


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rfc/rfc-83/rfc-83.md:
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+-->
+# RFC-83: Incremental Table Service
+
+## Proposers
+
+- @zhangyue19921010
+
+## Approvers
+- @danny0405
+- @yuzhaojing
+
+## Status
+
+JIRA: https://issues.apache.org/jira/browse/HUDI-8780
+
+## Abstract
+
+In Hudi, when scheduling Compaction and Clustering, the default behavior is to 
scan all partitions under the current table. 
+When there are many historical partitions, such as 640,000 in our production 
environment, this scanning and planning operation becomes very inefficient. 
+For Flink, it often leads to checkpoint timeouts, resulting in data delays.
+As for cleaning, we already have the ability to do cleaning for incremental 
partitions.
+
+This RFC will draw on the design of Incremental Clean to generalize the 
capability of processing incremental partitions to all table services, such as 
Clustering and Compaction.
+
+## Background
+
+`earliestInstantToRetain` in clean plan meta
+
+HoodieCleanerPlan.avsc
+
+```text
+{
+  "namespace": "org.apache.hudi.avro.model",
+  "type": "record",
+  "name": "HoodieCleanerPlan",
+  "fields": [
+    {
+      "name": "earliestInstantToRetain",
+      "type":["null", {
+        "type": "record",
+        "name": "HoodieActionInstant",
+        "fields": [
+          {
+            "name": "timestamp",
+            "type": "string"
+          },
+          {
+            "name": "action",
+            "type": "string"
+          },
+          {
+            "name": "state",
+            "type": "string"
+          }
+        ]
+      }],
+      "default" : null
+    },
+    xxxx
+  ]
+}
+```
+
+`EarliestCommitToRetan` in clean commit meta
+
+HoodieCleanMetadata.avsc
+
+```text
+{"namespace": "org.apache.hudi.avro.model",
+ "type": "record",
+ "name": "HoodieCleanMetadata",
+ "fields": [
+     xxxx,
+     {"name": "earliestCommitToRetain", "type": "string"},
+     xxxx
+ ]
+}
+```
+How to get incremental partitions during cleaning
+
+![cleanIncrementalpartitions.png](cleanIncrementalpartitions.png)
+
+**Note**
+`EarliestCommitToRetain` is recorded in `HoodieCleanMetadata`
+newInstantToRetain is computed based on Clean configs such as 
`hoodie.clean.commits.retained` and will be record in clean meta as new 
EarliestCommitToRetain
+
+## Design And Implementation
+
+### Changes in TableService Metadata Schema
+
+Add new column `earliestInstantToRetain` (default null) in 
Clustering/Compaction plan same as `earliestInstantToRetain` in clean plan
+
+```text
+    {
+      "name": "earliestInstantToRetain",
+      "type":["null", {
+        "type": "record",
+        "name": "HoodieActionInstant",
+        "fields": [
+          {
+            "name": "timestamp",
+            "type": "string"
+          },
+          {
+            "name": "action",
+            "type": "string"
+          },
+          {
+            "name": "state",
+            "type": "string"
+          }
+        ]
+      }],
+      "default" : null
+    },
+```
+
+We also need a unified interface/abstract-class to control the Plan behavior 
of the TableService including clustering and compaction.
+
+### Abstraction
+
+Use `PartitionBaseTableServicePlanStrategy` to control the behavior of getting 
partitions, filter partitions and generate table service plan etc.
+
+Since we want to control the logic of partition acquisition, partition 
filtering, and plan generation through different strategies, 
+in the first step, we need to use an abstraction to converge the logic of 
partition acquisition, partition filtering, and plan generation into the base 
strategy.
+
+```java
+package org.apache.hudi.table;
+
+import org.apache.hudi.common.engine.HoodieEngineContext;
+import org.apache.hudi.common.table.HoodieTableMetaClient;
+import org.apache.hudi.common.table.timeline.HoodieInstant;
+import org.apache.hudi.common.util.Option;
+import org.apache.hudi.config.HoodieWriteConfig;
+
+import java.io.IOException;
+import java.util.List;
+
+public abstract class PartitionBaseTableServicePlanStrategy<R,S> {
+
+  /**
+   * Generate table service plan based on given instant.
+   * @return
+   */
+  public abstract R generateTableServicePlan(Option<String> instant) throws 
IOException;
+
+  /**
+   * Generate table service plan based on given instant.
+   * @return
+   */
+  public abstract R generateTableServicePlan(List<S> operations) throws 
IOException;
+
+
+  /**
+   * Get partition paths to be performed for current table service.
+   * @param metaClient
+   * @return
+   */
+  public abstract List<String> getPartitionPaths(HoodieWriteConfig 
writeConfig, HoodieTableMetaClient metaClient, HoodieEngineContext 
engineContext);
+
+  /**
+   * Filter partition path for given fully paths.
+   * @param metaClient
+   * @return
+   */
+  public abstract List<String> filterPartitionPaths(HoodieWriteConfig 
writeConfig, List<String> partitionPaths);
+
+  /**
+   * Get incremental partitions from EarliestCommitToRetain to instantToRetain
+   * @param instantToRetain
+   * @param type
+   * @param deleteEmptyCommit
+   * @return
+   * @throws IOException
+   */
+  public List<String> getIncrementalPartitionPaths(Option<HoodieInstant> 
instantToRetain) {
+    throw new UnsupportedOperationException("Not support yet");
+  }
+
+  /**
+   * Returns the earliest commit to retain from instant meta
+   */
+  public Option<HoodieInstant> getEarliestCommitToRetain() {
+    throw new UnsupportedOperationException("Not support yet");

Review Comment:
   In addition, Danny, what's your opinion for the logic of incremental 
partition acquisition? 
   Option1 : Record a metadata field in the commit to indicate where the last 
processing was done
   Option2: Directly obtain the last completed table service commit time as the 
new starting point
   
   Option2 is simpler and does not require modifying and processing commit 
metadata fields.



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