[GitHub] [flink] cshuo commented on a change in pull request #16979: [FLINK-23962][table-planner] Fix updateKind trait propagating problem…

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cshuo commented on a change in pull request #16979:
URL: https://github.com/apache/flink/pull/16979#discussion_r696579500



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File path: flink-table/flink-table-planner/src/main/scala/org/apache/flink/table/planner/plan/optimize/StreamCommonSubGraphBasedOptimizer.scala
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@@ -85,12 +83,13 @@ class StreamCommonSubGraphBasedOptimizer(planner: StreamPlanner)
       return sinkBlocks
     }
 
-    // infer updateAsRetraction property and miniBatchInterval property for all input blocks
+    // infer modifyKind property for each blocks independently
+    sinkBlocks.foreach(b => optimizeBlock(b, isSinkBlock = true))
+    // infer and propagate updateKind and miniBatchInterval property for each blocks
     sinkBlocks.foreach { b =>
-      inferTraits(b, b.isUpdateBeforeRequired, b.getMiniBatchInterval, isSinkBlock = true)
+      propagateUpdateKindAndMiniBatchInterval(
+        b, b.isUpdateBeforeRequired, b.getMiniBatchInterval, isSinkBlock = true)
     }
-    // propagate updateAsRetraction property and miniBatchInterval property to all input blocks
-    sinkBlocks.foreach(propagateTraits(_, isSinkBlock = true))
     // clear the intermediate result
     sinkBlocks.foreach(resetIntermediateResult)
     // optimize recursively RelNodeBlock

Review comment:
       For solution here, it cannot be remove. You're right that the final `optimizeBlock ` is updating the intermediate results, but the updated intermediate result is physical node plan optimized with correct `ModifyKind` and `UpdateKind` trait, which are inferred and propagated by Line 86 ~ 91.
   
   The plan is optimized 3 times currently. Actually, we can move changeLog and minibatch interval inference out of optimizing phase, in that way the plan only needs one optimizing. This refactor involves many changes, so I think we may put it in later version.




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