diff --git a/nebula-exchange_spark_2.2/src/main/scala/com/vesoft/nebula/exchange/processor/EdgeProcessor.scala b/nebula-exchange_spark_2.2/src/main/scala/com/vesoft/nebula/exchange/processor/EdgeProcessor.scala
index 471e5fb..86dcf55 100644
--- a/nebula-exchange_spark_2.2/src/main/scala/com/vesoft/nebula/exchange/processor/EdgeProcessor.scala
+++ b/nebula-exchange_spark_2.2/src/main/scala/com/vesoft/nebula/exchange/processor/EdgeProcessor.scala
@@ -78,19 +78,14 @@ class EdgeProcessor(spark: SparkSession,
         batchFailure.add(1)
         recordFailure.add(edge.toList.size)
         if (batchFailure.value >= config.errorConfig.errorMaxSize) {
+          writeErrorStatement(errorBuffer)
           throw TooManyErrorsException(
             s"There are too many failed batches, batch amount: ${batchFailure.value}, " +
               s"your config max error size: ${config.errorConfig.errorMaxSize}")
         }
       }
     }
-    if (errorBuffer.nonEmpty) {
-      val appId = SparkEnv.get.blockManager.conf.getAppId
-      ErrorHandler.save(
-        errorBuffer,
-        s"${config.errorConfig.errorPath}/${appId}/${edgeConfig.name}.${TaskContext.getPartitionId}")
-      errorBuffer.clear()
-    }
+    writeErrorStatement(errorBuffer)
     LOG.info(s"edge ${edgeConfig.name} import in spark partition ${TaskContext
       .getPartitionId()} cost ${System.currentTimeMillis() - startTime}ms")
     writer.close()
@@ -408,4 +403,14 @@ class EdgeProcessor(spark: SparkSession,
     val edgeValue = codec.encodeEdge(edgeItem, nebulaKeys.asJava, values.asJava)
     (positiveEdgeKey, reverseEdgeKey, edgeValue)
   }
+
+  private def writeErrorStatement(errorBuffer: ArrayBuffer[String]): Unit = {
+    if (errorBuffer.nonEmpty) {
+      val appId = SparkEnv.get.blockManager.conf.getAppId
+      ErrorHandler.save(
+        errorBuffer,
+        s"${config.errorConfig.errorPath}/${appId}/${edgeConfig.name}.${TaskContext.getPartitionId}")
+      errorBuffer.clear()
+    }
+  }
 }
diff --git a/nebula-exchange_spark_2.2/src/main/scala/com/vesoft/nebula/exchange/processor/VerticesProcessor.scala b/nebula-exchange_spark_2.2/src/main/scala/com/vesoft/nebula/exchange/processor/VerticesProcessor.scala
index 1213c76..73d53ae 100644
--- a/nebula-exchange_spark_2.2/src/main/scala/com/vesoft/nebula/exchange/processor/VerticesProcessor.scala
+++ b/nebula-exchange_spark_2.2/src/main/scala/com/vesoft/nebula/exchange/processor/VerticesProcessor.scala
@@ -85,19 +85,14 @@ class VerticesProcessor(spark: SparkSession,
         batchFailure.add(1)
         recordFailure.add(vertex.toList.size)
         if (batchFailure.value >= config.errorConfig.errorMaxSize) {
+          writeErrorStatement(errorBuffer)
           throw TooManyErrorsException(
             s"There are too many failed batches, batch amount: ${batchFailure.value}, " +
               s"your config max error size: ${config.errorConfig.errorMaxSize}")
         }
       }
     }
-    if (errorBuffer.nonEmpty) {
-      val appId = SparkEnv.get.blockManager.conf.getAppId
-      ErrorHandler.save(
-        errorBuffer,
-        s"${config.errorConfig.errorPath}/${appId}/${tagConfig.name}.${TaskContext.getPartitionId()}")
-      errorBuffer.clear()
-    }
+    writeErrorStatement(errorBuffer)
     LOG.info(s">>>>>> tag ${tagConfig.name} import in spark partition ${TaskContext
       .getPartitionId()} cost ${System.currentTimeMillis() - startTime} ms")
     writer.close()
@@ -326,4 +321,14 @@ class VerticesProcessor(spark: SparkSession,
     val orphanVertexKey = codec.orphanVertexKey(spaceVidLen, partitionId, vidBytes)
     (orphanVertexKey, vertexKey, vertexValue)
   }
+
+  private def writeErrorStatement(errorBuffer: ArrayBuffer[String]): Unit = {
+    if (errorBuffer.nonEmpty) {
+      val appId = SparkEnv.get.blockManager.conf.getAppId
+      ErrorHandler.save(
+        errorBuffer,
+        s"${config.errorConfig.errorPath}/${appId}/${tagConfig.name}.${TaskContext.getPartitionId}")
+      errorBuffer.clear()
+    }
+  }
 }
diff --git a/nebula-exchange_spark_2.4/src/main/scala/com/vesoft/nebula/exchange/processor/EdgeProcessor.scala b/nebula-exchange_spark_2.4/src/main/scala/com/vesoft/nebula/exchange/processor/EdgeProcessor.scala
index b9861a4..a458c3b 100644
--- a/nebula-exchange_spark_2.4/src/main/scala/com/vesoft/nebula/exchange/processor/EdgeProcessor.scala
+++ b/nebula-exchange_spark_2.4/src/main/scala/com/vesoft/nebula/exchange/processor/EdgeProcessor.scala
@@ -79,19 +79,14 @@ class EdgeProcessor(spark: SparkSession,
         batchFailure.add(1)
         recordFailure.add(edge.toList.size)
         if (batchFailure.value >= config.errorConfig.errorMaxSize) {
+          writeErrorStatement(errorBuffer)
           throw TooManyErrorsException(
             s"There are too many failed batches, batch amount: ${batchFailure.value}, " +
               s"your config max error size: ${config.errorConfig.errorMaxSize}")
         }
       }
     }
-    if (errorBuffer.nonEmpty) {
-      val appId = SparkEnv.get.blockManager.conf.getAppId
-      ErrorHandler.save(
-        errorBuffer,
-        s"${config.errorConfig.errorPath}/${appId}/${edgeConfig.name}.${TaskContext.getPartitionId}")
-      errorBuffer.clear()
-    }
+    writeErrorStatement(errorBuffer)
     LOG.info(s">>>>> edge ${edgeConfig.name} import in spark partition ${TaskContext
       .getPartitionId()} cost ${System.currentTimeMillis() - startTime}ms")
     writer.close()
@@ -431,4 +426,14 @@ class EdgeProcessor(spark: SparkSession,
     val edgeValue = codec.encodeEdge(edgeItem, nebulaKeys.asJava, values.asJava)
     (positiveEdgeKey, reverseEdgeKey, edgeValue)
   }
+
+  private def writeErrorStatement(errorBuffer:ArrayBuffer[String]): Unit = {
+    if (errorBuffer.nonEmpty) {
+      val appId = SparkEnv.get.blockManager.conf.getAppId
+      ErrorHandler.save(
+        errorBuffer,
+        s"${config.errorConfig.errorPath}/${appId}/${edgeConfig.name}.${TaskContext.getPartitionId}")
+      errorBuffer.clear()
+    }
+  }
 }
diff --git a/nebula-exchange_spark_2.4/src/main/scala/com/vesoft/nebula/exchange/processor/VerticesProcessor.scala b/nebula-exchange_spark_2.4/src/main/scala/com/vesoft/nebula/exchange/processor/VerticesProcessor.scala
index 55c3a8a..ece0052 100644
--- a/nebula-exchange_spark_2.4/src/main/scala/com/vesoft/nebula/exchange/processor/VerticesProcessor.scala
+++ b/nebula-exchange_spark_2.4/src/main/scala/com/vesoft/nebula/exchange/processor/VerticesProcessor.scala
@@ -87,19 +87,14 @@ class VerticesProcessor(spark: SparkSession,
         batchFailure.add(1)
         recordFailure.add(vertex.toList.size)
         if (batchFailure.value >= config.errorConfig.errorMaxSize) {
+          writeErrorStatement(errorBuffer)
           throw TooManyErrorsException(
             s"There are too many failed batches, batch amount: ${batchFailure.value}, " +
               s"your config max error size: ${config.errorConfig.errorMaxSize}")
         }
       }
     }
-    if (errorBuffer.nonEmpty) {
-      val appId = SparkEnv.get.blockManager.conf.getAppId
-      ErrorHandler.save(
-        errorBuffer,
-        s"${config.errorConfig.errorPath}/${appId}/${tagConfig.name}.${TaskContext.getPartitionId()}")
-      errorBuffer.clear()
-    }
+    writeErrorStatement(errorBuffer)
     LOG.info(s">>>>> tag ${tagConfig.name} import in spark partition ${TaskContext
       .getPartitionId()} cost ${System.currentTimeMillis() - startTime} ms")
     writer.close()
@@ -340,4 +335,14 @@ class VerticesProcessor(spark: SparkSession,
     val orphanVertexKey = codec.orphanVertexKey(spaceVidLen, partitionId, vidBytes)
     (orphanVertexKey, vertexKey, vertexValue)
   }
+
+  private def writeErrorStatement(errorBuffer: ArrayBuffer[String]): Unit = {
+    if (errorBuffer.nonEmpty) {
+      val appId = SparkEnv.get.blockManager.conf.getAppId
+      ErrorHandler.save(
+        errorBuffer,
+        s"${config.errorConfig.errorPath}/${appId}/${tagConfig.name}.${TaskContext.getPartitionId}")
+      errorBuffer.clear()
+    }
+  }
 }
diff --git a/nebula-exchange_spark_3.0/src/main/scala/com/vesoft/nebula/exchange/processor/EdgeProcessor.scala b/nebula-exchange_spark_3.0/src/main/scala/com/vesoft/nebula/exchange/processor/EdgeProcessor.scala
index 334274b..a7002ec 100644
--- a/nebula-exchange_spark_3.0/src/main/scala/com/vesoft/nebula/exchange/processor/EdgeProcessor.scala
+++ b/nebula-exchange_spark_3.0/src/main/scala/com/vesoft/nebula/exchange/processor/EdgeProcessor.scala
@@ -80,19 +80,14 @@ class EdgeProcessor(spark: SparkSession,
         recordFailure.add(edge.toList.size)
 
         if (batchFailure.value >= config.errorConfig.errorMaxSize) {
+          writeErrorStatement(errorBuffer)
           throw TooManyErrorsException(
             s"There are too many failed batches, batch amount: ${batchFailure.value}, " +
               s"your config max error size: ${config.errorConfig.errorMaxSize}")
         }
       }
     }
-    if (errorBuffer.nonEmpty) {
-      val appId = SparkEnv.get.blockManager.conf.getAppId
-      ErrorHandler.save(
-        errorBuffer,
-        s"${config.errorConfig.errorPath}/${appId}/${edgeConfig.name}.${TaskContext.getPartitionId}")
-      errorBuffer.clear()
-    }
+    writeErrorStatement(errorBuffer)
     LOG.info(s">>>>> edge ${edgeConfig.name} import in spark partition ${TaskContext
       .getPartitionId()} cost ${System.currentTimeMillis() - startTime}ms")
     writer.close()
@@ -431,4 +426,14 @@ class EdgeProcessor(spark: SparkSession,
     val edgeValue = codec.encodeEdge(edgeItem, nebulaKeys.asJava, values.asJava)
     (positiveEdgeKey, reverseEdgeKey, edgeValue)
   }
+
+  private def writeErrorStatement(errorBuffer: ArrayBuffer[String]): Unit = {
+    if (errorBuffer.nonEmpty) {
+      val appId = SparkEnv.get.blockManager.conf.getAppId
+      ErrorHandler.save(
+        errorBuffer,
+        s"${config.errorConfig.errorPath}/${appId}/${edgeConfig.name}.${TaskContext.getPartitionId}")
+      errorBuffer.clear()
+    }
+  }
 }
diff --git a/nebula-exchange_spark_3.0/src/main/scala/com/vesoft/nebula/exchange/processor/VerticesProcessor.scala b/nebula-exchange_spark_3.0/src/main/scala/com/vesoft/nebula/exchange/processor/VerticesProcessor.scala
index 1fe43cc..d39785e 100644
--- a/nebula-exchange_spark_3.0/src/main/scala/com/vesoft/nebula/exchange/processor/VerticesProcessor.scala
+++ b/nebula-exchange_spark_3.0/src/main/scala/com/vesoft/nebula/exchange/processor/VerticesProcessor.scala
@@ -87,19 +87,14 @@ class VerticesProcessor(spark: SparkSession,
         batchFailure.add(1)
         recordFailure.add(vertex.toList.size)
         if (batchFailure.value >= config.errorConfig.errorMaxSize) {
+          writeErrorStatement(errorBuffer)
           throw TooManyErrorsException(
             s"There are too many failed batches, batch amount: ${batchFailure.value}, " +
               s"your config max error size: ${config.errorConfig.errorMaxSize}")
         }
       }
     }
-    if (errorBuffer.nonEmpty) {
-      val appId = SparkEnv.get.blockManager.conf.getAppId
-      ErrorHandler.save(
-        errorBuffer,
-        s"${config.errorConfig.errorPath}/${appId}/${tagConfig.name}.${TaskContext.getPartitionId()}")
-      errorBuffer.clear()
-    }
+    writeErrorStatement(errorBuffer)
     LOG.info(s">>>>> tag ${tagConfig.name} import in spark partition ${TaskContext
       .getPartitionId()} cost ${System.currentTimeMillis() - startTime} ms")
     writer.close()
@@ -345,4 +340,14 @@ class VerticesProcessor(spark: SparkSession,
     val orphanVertexKey = codec.orphanVertexKey(spaceVidLen, partitionId, vidBytes)
     (orphanVertexKey, vertexKey, vertexValue)
   }
+
+  private def writeErrorStatement(errorBuffer: ArrayBuffer[String]): Unit = {
+    if (errorBuffer.nonEmpty) {
+      val appId = SparkEnv.get.blockManager.conf.getAppId
+      ErrorHandler.save(
+        errorBuffer,
+        s"${config.errorConfig.errorPath}/${appId}/${tagConfig.name}.${TaskContext.getPartitionId}")
+      errorBuffer.clear()
+    }
+  }
 }