diff --git a/core/amber/src/main/scala/edu/uci/ics/texera/workflow/WorkflowCompiler.scala b/core/amber/src/main/scala/edu/uci/ics/texera/workflow/WorkflowCompiler.scala
index 9144fa63d4..2eb645c2e2 100644
--- a/core/amber/src/main/scala/edu/uci/ics/texera/workflow/WorkflowCompiler.scala
+++ b/core/amber/src/main/scala/edu/uci/ics/texera/workflow/WorkflowCompiler.scala
@@ -67,66 +67,6 @@ class WorkflowCompiler(
                 .foldLeft(physicalPlan) { (plan, link) => plan.addLink(link) }
             }
           })
-
-        // assign the sinks to toAddSink operators' external output ports
-        subPlan
-          .topologicalIterator()
-          .map(subPlan.getOperator)
-          .flatMap { physicalOp =>
-            physicalOp.outputPorts.map(outputPort => (physicalOp, outputPort))
-          }
-          .filter({
-            case (physicalOp, (_, (outputPort, _, _))) =>
-              toAddSink.contains(physicalOp.id.logicalOpId) && !outputPort.id.internal
-          })
-          .foreach({
-            case (physicalOp, (_, (outputPort, _, schema))) =>
-              val storage = ResultStorage.getOpResultStorage(context.workflowId)
-              val storageKey = physicalOp.id.logicalOpId
-
-              // due to the size limit of single document in mongoDB (16MB)
-              // for sinks visualizing HTMLs which could possibly be large in size, we always use the memory storage.
-              val storageType = {
-                if (outputPort.mode == SINGLE_SNAPSHOT) OpResultStorage.MEMORY
-                else OpResultStorage.defaultStorageMode
-              }
-              if (!storage.contains(storageKey)) {
-                // get the schema for result storage in certain mode
-                val sinkStorageSchema: Option[Schema] =
-                  if (storageType == OpResultStorage.MONGODB) {
-                    // use the output schema on the first output port as the schema for storage
-                    Some(schema.right.get)
-                  } else {
-                    None
-                  }
-                storage.create(
-                  s"${context.executionId}_",
-                  storageKey,
-                  storageType,
-                  sinkStorageSchema
-                )
-                // add the sink collection name to the JSON array of sinks
-                val storageNode = objectMapper.createObjectNode()
-                storageNode.put("storageType", storageType)
-                storageNode.put("storageKey", s"${context.executionId}_$storageKey")
-                sinksPointers.add(storageNode)
-              }
-
-              val sinkPhysicalOp = SpecialPhysicalOpFactory.newSinkPhysicalOp(
-                context.workflowId,
-                context.executionId,
-                storageKey.id,
-                outputPort.mode
-              )
-              val sinkLink =
-                PhysicalLink(
-                  physicalOp.id,
-                  outputPort.id,
-                  sinkPhysicalOp.id,
-                  PortIdentity(internal = true)
-                )
-              physicalPlan = physicalPlan.addOperator(sinkPhysicalOp).addLink(sinkLink)
-          })
       } match {
         case Success(_) =>
 
@@ -138,6 +78,66 @@ class WorkflowCompiler(
       }
     )
 
+    // assign the sinks to toAddSink operators' external output ports
+    physicalPlan
+      .topologicalIterator()
+      .map(physicalPlan.getOperator)
+      .flatMap { physicalOp =>
+        physicalOp.outputPorts.map(outputPort => (physicalOp, outputPort))
+      }
+      .filter({
+        case (physicalOp, (_, (outputPort, _, _))) =>
+          toAddSink.contains(physicalOp.id.logicalOpId) && !outputPort.id.internal
+      })
+      .foreach({
+        case (physicalOp, (_, (outputPort, _, schema))) =>
+          val storage = ResultStorage.getOpResultStorage(context.workflowId)
+          val storageKey = physicalOp.id.logicalOpId
+
+          // due to the size limit of single document in mongoDB (16MB)
+          // for sinks visualizing HTMLs which could possibly be large in size, we always use the memory storage.
+          val storageType = {
+            if (outputPort.mode == SINGLE_SNAPSHOT) OpResultStorage.MEMORY
+            else OpResultStorage.defaultStorageMode
+          }
+          if (!storage.contains(storageKey)) {
+            // get the schema for result storage in certain mode
+            val sinkStorageSchema: Option[Schema] =
+              if (storageType == OpResultStorage.MONGODB) {
+                // use the output schema on the first output port as the schema for storage
+                Some(schema.right.get)
+              } else {
+                None
+              }
+            storage.create(
+              s"${context.executionId}_",
+              storageKey,
+              storageType,
+              sinkStorageSchema
+            )
+            // add the sink collection name to the JSON array of sinks
+            val storageNode = objectMapper.createObjectNode()
+            storageNode.put("storageType", storageType)
+            storageNode.put("storageKey", s"${context.executionId}_$storageKey")
+            sinksPointers.add(storageNode)
+          }
+
+          val sinkPhysicalOp = SpecialPhysicalOpFactory.newSinkPhysicalOp(
+            context.workflowId,
+            context.executionId,
+            storageKey.id,
+            outputPort.mode
+          )
+          val sinkLink =
+            PhysicalLink(
+              physicalOp.id,
+              outputPort.id,
+              sinkPhysicalOp.id,
+              PortIdentity(internal = true)
+            )
+          physicalPlan = physicalPlan.addOperator(sinkPhysicalOp).addLink(sinkLink)
+      })
+
     // update execution entry in MySQL to have pointers to the mongo collections
     resultsJSON.set("results", sinksPointers)
     ExecutionsMetadataPersistService.tryUpdateExistingExecution(context.executionId) {