diff --git a/README-CN.md b/README-CN.md
index b83a3ac..f8e3768 100644
--- a/README-CN.md
+++ b/README-CN.md
@@ -51,9 +51,6 @@ nebula-algorithm 是一款基于 [GraphX](https://spark.apache.org/graphx/) 的
     ```
     ${SPARK_HOME}/bin/spark-submit --master <mode> --class com.vesoft.nebula.algorithm.Main nebula-algorithm-3.0-SNAPSHOT.jar -p application.conf
     ```
-    * 使用限制
-    
-    Nebula Algorithm 算法包未自动对字符串 id 进行编码，因此采用第一种方式执行图算法时，边的源点和目标点必须是整数（Nebula Space 的 vid_type 可以是 String 类型，但数据必须是整数）。
 * 使用方法2：调用 nebula-algorithm 算法接口
 
    在 `nebula-algorithm` 的 `lib` 库中提供了10+种常用图计算算法，可通过编程调用的形式调用算法。
@@ -75,7 +72,8 @@ nebula-algorithm 是一款基于 [GraphX](https://spark.apache.org/graphx/) 的
    val prConfig = new PRConfig(5, 1.0)
    val prResult = PageRankAlgo.apply(spark, data, prConfig, false)
    ```
-   * 如果你的节点 id 是 String 类型，可以参考 PageRank 的 [Example](https://github.com/vesoft-inc/nebula-algorithm/blob/master/example/src/main/scala/com/vesoft/nebula/algorithm/PageRankExample.scala) 。 
+   * 如果你的节点 id 是 String 类型，可以参考 [examples](https://github.com/vesoft-inc/nebula-algorithm/tree/master/example/src/main/scala/com/vesoft/nebula/algorithm/DegreeStaticExample.scala).
+                                    
    该 Example 进行了 id 转换，将 String 类型 id 编码为 Long 类型的 id ， 并在算法结果中将 Long 类型 id 解码为原始的 String 类型 id 。
    
     其他算法的调用方法见[测试示例](https://github.com/vesoft-inc/nebula-algorithm/tree/master/nebula-algorithm/src/test/scala/com/vesoft/nebula/algorithm/lib) 。
diff --git a/README.md b/README.md
index ba4370e..a9f8795 100644
--- a/README.md
+++ b/README.md
@@ -60,10 +60,6 @@ You could submit the entire spark application or invoke algorithms in `lib` libr
     ${SPARK_HOME}/bin/spark-submit --master <mode> --class com.vesoft.nebula.algorithm.Main nebula-algorithm-3.0—SNAPSHOT.jar -p application.conf
     ```
    
-   * Limitation
-    
-    Due to Nebula Algorithm jar does not encode string id, thus during the algorithm execution, the source and target of edges must be in Type Int (The `vid_type` in Nebula Space could be String, while data must be in Type Int).
-
 * Option2: Call nebula-algorithm interface
 
    Now there are 10+ algorithms provided in `lib` from `nebula-algorithm`, which could be invoked in a programming fashion as below:
@@ -87,7 +83,7 @@ You could submit the entire spark application or invoke algorithms in `lib` libr
    val prResult = PageRankAlgo.apply(spark, data, prConfig, false)
    ```
    
-   If your vertex ids are Strings, see [Pagerank Example](https://github.com/vesoft-inc/nebula-algorithm/blob/master/example/src/main/scala/com/vesoft/nebula/algorithm/PageRankExample.scala) for how to encoding and decoding them.
+   If your vertex ids are Strings, please set the algo config with encodeId = true. see [examples](https://github.com/vesoft-inc/nebula-algorithm/tree/master/example/src/main/scala/com/vesoft/nebula/algorithm/DegreeStaticExample.scala)
     
     For examples of other algorithms, see [examples](https://github.com/vesoft-inc/nebula-algorithm/tree/master/example/src/main/scala/com/vesoft/nebula/algorithm)
    > Note: The first column of DataFrame in the application represents the source vertices, the second represents the target vertices and the third represents edges' weight.
diff --git a/example/pom.xml b/example/pom.xml
index beda679..f3956c6 100644
--- a/example/pom.xml
+++ b/example/pom.xml
@@ -182,7 +182,7 @@
         <dependency>
             <groupId>com.vesoft</groupId>
             <artifactId>nebula-algorithm</artifactId>
-            <version>3.0.0</version>
+            <version>3.0-SNAPSHOT</version>
         </dependency>
     </dependencies>
 </project>
diff --git a/example/src/main/scala/com/vesoft/nebula/algorithm/DegreeStaticExample.scala b/example/src/main/scala/com/vesoft/nebula/algorithm/DegreeStaticExample.scala
index 6badb57..19d799d 100644
--- a/example/src/main/scala/com/vesoft/nebula/algorithm/DegreeStaticExample.scala
+++ b/example/src/main/scala/com/vesoft/nebula/algorithm/DegreeStaticExample.scala
@@ -6,7 +6,8 @@
 package com.vesoft.nebula.algorithm
 
 import com.facebook.thrift.protocol.TCompactProtocol
-import com.vesoft.nebula.algorithm.lib.{DegreeStaticAlgo}
+import com.vesoft.nebula.algorithm.config.DegreeStaticConfig
+import com.vesoft.nebula.algorithm.lib.DegreeStaticAlgo
 import org.apache.spark.SparkConf
 import org.apache.spark.sql.{DataFrame, SparkSession}
 
@@ -22,15 +23,22 @@ object DegreeStaticExample {
       .config(sparkConf)
       .getOrCreate()
 
-    // val csvDF     = ReadData.readCsvData(spark)
     // val nebulaDF  = ReadData.readNebulaData(spark)
     val journalDF = ReadData.readLiveJournalData(spark)
-
     degree(spark, journalDF)
+
+    val csvDF = ReadData.readStringCsvData(spark)
+    degreeForStringId(spark, csvDF)
   }
 
   def degree(spark: SparkSession, df: DataFrame): Unit = {
     val degree = DegreeStaticAlgo.apply(spark, df)
     degree.show()
   }
+
+  def degreeForStringId(spark: SparkSession, df: DataFrame): Unit = {
+    val degreeConfig = new DegreeStaticConfig(true)
+    val degree       = DegreeStaticAlgo.apply(spark, df, degreeConfig)
+    degree.show()
+  }
 }
diff --git a/nebula-algorithm/src/main/resources/application.conf b/nebula-algorithm/src/main/resources/application.conf
index f10ad45..40ebe75 100644
--- a/nebula-algorithm/src/main/resources/application.conf
+++ b/nebula-algorithm/src/main/resources/application.conf
@@ -113,7 +113,9 @@
    }
 
     # Vertex degree statistics parameter
-    degreestatic: {}
+    degreestatic: {
+        encodeId:false
+    }
 
    # KCore parameter
    kcore:{
@@ -123,7 +125,9 @@
    }
 
    # Trianglecount parameter
-   trianglecount:{}
+   trianglecount:{
+        encodeId:false
+   }
 
    # graphTriangleCount parameter
    graphtrianglecount:{}
@@ -189,6 +193,7 @@
    # JaccardAlgo parameter
    jaccard:{
        tol: 1.0
+       encodeId:false
    }
  }
 }
diff --git a/nebula-algorithm/src/main/scala/com/vesoft/nebula/algorithm/config/AlgoConfig.scala b/nebula-algorithm/src/main/scala/com/vesoft/nebula/algorithm/config/AlgoConfig.scala
index 9844e07..9811185 100644
--- a/nebula-algorithm/src/main/scala/com/vesoft/nebula/algorithm/config/AlgoConfig.scala
+++ b/nebula-algorithm/src/main/scala/com/vesoft/nebula/algorithm/config/AlgoConfig.scala
@@ -5,6 +5,7 @@
 
 package com.vesoft.nebula.algorithm.config
 
+import com.vesoft.nebula.algorithm.config.JaccardConfig.encodeId
 import org.apache.spark.graphx.VertexId
 
 case class PRConfig(maxIter: Int, resetProb: Double, encodeId: Boolean = false)
@@ -110,24 +111,30 @@ object LouvainConfig {
 /**
   * degree static
   */
-case class DegreeStaticConfig(degree: Boolean,
-                              inDegree: Boolean,
-                              outDegree: Boolean,
-                              encodeId: Boolean = false)
+case class DegreeStaticConfig(encodeId: Boolean = false)
 
 object DegreeStaticConfig {
-  var degree: Boolean    = false
-  var inDegree: Boolean  = false
-  var outDegree: Boolean = false
-  var encodeId: Boolean  = false
+  var encodeId: Boolean = false
 
   def getDegreeStaticConfig(configs: Configs): DegreeStaticConfig = {
     val degreeConfig = configs.algorithmConfig.map
-    degree = ConfigUtil.getOrElseBoolean(degreeConfig, "algorithm.degreestatic.degree", false)
-    inDegree = ConfigUtil.getOrElseBoolean(degreeConfig, "algorithm.degreestatic.indegree", false)
-    outDegree = ConfigUtil.getOrElseBoolean(degreeConfig, "algorithm.degreestatic.outdegree", false)
     encodeId = ConfigUtil.getOrElseBoolean(degreeConfig, "algorithm.degreestatic.encodeId", false)
-    DegreeStaticConfig(degree, inDegree, outDegree, encodeId)
+    DegreeStaticConfig(encodeId)
+  }
+}
+
+/**
+  * graph triangle count
+  */
+case class TriangleConfig(encodeId: Boolean = false)
+
+object TriangleConfig {
+  var encodeId: Boolean = false
+  def getTriangleConfig(configs: Configs): TriangleConfig = {
+    val triangleConfig = configs.algorithmConfig.map
+    encodeId =
+      ConfigUtil.getOrElseBoolean(triangleConfig, "algorithm.trianglecount.encodeId", false)
+    TriangleConfig(encodeId)
   }
 }
 
@@ -321,14 +328,16 @@ object Node2vecConfig {
 /**
   * Jaccard
   */
-case class JaccardConfig(tol: Double)
+case class JaccardConfig(tol: Double, encodeId: Boolean = false)
 
 object JaccardConfig {
-  var tol: Double = _
+  var tol: Double       = _
+  var encodeId: Boolean = false
   def getJaccardConfig(configs: Configs): JaccardConfig = {
     val jaccardConfig = configs.algorithmConfig.map
     tol = jaccardConfig("algorithm.jaccard.tol").toDouble
-    JaccardConfig(tol)
+    encodeId = ConfigUtil.getOrElseBoolean(jaccardConfig, "algorithm.jaccard.encodeId", false)
+    JaccardConfig(tol, encodeId)
   }
 }
 
diff --git a/nebula-algorithm/src/main/scala/com/vesoft/nebula/algorithm/lib/BfsAlgo.scala b/nebula-algorithm/src/main/scala/com/vesoft/nebula/algorithm/lib/BfsAlgo.scala
index ce639c5..8765f93 100644
--- a/nebula-algorithm/src/main/scala/com/vesoft/nebula/algorithm/lib/BfsAlgo.scala
+++ b/nebula-algorithm/src/main/scala/com/vesoft/nebula/algorithm/lib/BfsAlgo.scala
@@ -50,9 +50,9 @@ object BfsAlgo {
       .orderBy(col(AlgoConstants.BFS_RESULT_COL))
 
     if (bfsConfig.encodeId) {
-      DecodeUtil.convertAlgoId2StringId(algoResult, encodeIdDf)
+      DecodeUtil.convertAlgoId2StringId(algoResult, encodeIdDf).coalesce(1)
     } else {
-      algoResult
+      algoResult.coalesce(1)
     }
   }
 
diff --git a/nebula-algorithm/src/main/scala/com/vesoft/nebula/algorithm/lib/DegreeStaticAlgo.scala b/nebula-algorithm/src/main/scala/com/vesoft/nebula/algorithm/lib/DegreeStaticAlgo.scala
index 3a63c71..7721ecc 100644
--- a/nebula-algorithm/src/main/scala/com/vesoft/nebula/algorithm/lib/DegreeStaticAlgo.scala
+++ b/nebula-algorithm/src/main/scala/com/vesoft/nebula/algorithm/lib/DegreeStaticAlgo.scala
@@ -5,8 +5,8 @@
 
 package com.vesoft.nebula.algorithm.lib
 
-import com.vesoft.nebula.algorithm.config.AlgoConstants
-import com.vesoft.nebula.algorithm.utils.NebulaUtil
+import com.vesoft.nebula.algorithm.config.{AlgoConstants, DegreeStaticConfig}
+import com.vesoft.nebula.algorithm.utils.{DecodeUtil, NebulaUtil}
 import org.apache.log4j.Logger
 import org.apache.spark.graphx.{Graph, VertexRDD}
 import org.apache.spark.rdd.RDD
@@ -22,9 +22,18 @@ object DegreeStaticAlgo {
   /**
     * run the pagerank algorithm for nebula graph
     */
-  def apply(spark: SparkSession, dataset: Dataset[Row]): DataFrame = {
+  def apply(spark: SparkSession,
+            dataset: Dataset[Row],
+            degreeConfig: DegreeStaticConfig = new DegreeStaticConfig): DataFrame = {
+    var encodeIdDf: DataFrame = null
 
-    val graph: Graph[None.type, Double] = NebulaUtil.loadInitGraph(dataset, false)
+    val graph: Graph[None.type, Double] = if (degreeConfig.encodeId) {
+      val (data, encodeId) = DecodeUtil.convertStringId2LongId(dataset, false)
+      encodeIdDf = encodeId
+      NebulaUtil.loadInitGraph(data, false)
+    } else {
+      NebulaUtil.loadInitGraph(dataset, false)
+    }
 
     val degreeResultRDD = execute(graph)
 
@@ -38,7 +47,11 @@ object DegreeStaticAlgo {
     val algoResult = spark.sqlContext
       .createDataFrame(degreeResultRDD, schema)
 
-    algoResult
+    if (degreeConfig.encodeId) {
+      DecodeUtil.convertAlgoId2StringId(algoResult, encodeIdDf)
+    } else {
+      algoResult
+    }
   }
 
   def execute(graph: Graph[None.type, Double]): RDD[Row] = {
diff --git a/nebula-algorithm/src/main/scala/com/vesoft/nebula/algorithm/lib/JaccardAlgo.scala b/nebula-algorithm/src/main/scala/com/vesoft/nebula/algorithm/lib/JaccardAlgo.scala
index 01c1351..8339d70 100644
--- a/nebula-algorithm/src/main/scala/com/vesoft/nebula/algorithm/lib/JaccardAlgo.scala
+++ b/nebula-algorithm/src/main/scala/com/vesoft/nebula/algorithm/lib/JaccardAlgo.scala
@@ -6,7 +6,9 @@
 package com.vesoft.nebula.algorithm.lib
 
 import com.vesoft.nebula.algorithm.config.JaccardConfig
+import com.vesoft.nebula.algorithm.utils.{DecodeUtil, NebulaUtil}
 import org.apache.log4j.Logger
+import org.apache.spark.graphx.Graph
 import org.apache.spark.ml.feature.{
   CountVectorizer,
   CountVectorizerModel,
@@ -29,7 +31,16 @@ object JaccardAlgo {
     */
   def apply(spark: SparkSession, dataset: Dataset[Row], jaccardConfig: JaccardConfig): DataFrame = {
 
-    val jaccardResult: RDD[Row] = execute(spark, dataset, jaccardConfig.tol)
+    var encodeIdDf: DataFrame = null
+    var data: DataFrame       = dataset
+
+    if (jaccardConfig.encodeId) {
+      val (encodeData, encodeId) = DecodeUtil.convertStringId2LongId(dataset, false)
+      encodeIdDf = encodeId
+      data = encodeData
+    }
+
+    val jaccardResult: RDD[Row] = execute(spark, data, jaccardConfig.tol)
 
     val schema = StructType(
       List(
@@ -38,7 +49,13 @@ object JaccardAlgo {
         StructField("similarity", DoubleType, nullable = true)
       ))
     val algoResult = spark.sqlContext.createDataFrame(jaccardResult, schema)
-    algoResult
+
+    if (jaccardConfig.encodeId) {
+      DecodeUtil.convertIds2String(algoResult, encodeIdDf, "srcId", "dstId")
+    } else {
+      algoResult
+    }
+
   }
 
   def execute(spark: SparkSession, dataset: Dataset[Row], tol: Double): RDD[Row] = {
diff --git a/nebula-algorithm/src/main/scala/com/vesoft/nebula/algorithm/lib/TriangleCountAlgo.scala b/nebula-algorithm/src/main/scala/com/vesoft/nebula/algorithm/lib/TriangleCountAlgo.scala
index 47b9b8a..377c5a7 100644
--- a/nebula-algorithm/src/main/scala/com/vesoft/nebula/algorithm/lib/TriangleCountAlgo.scala
+++ b/nebula-algorithm/src/main/scala/com/vesoft/nebula/algorithm/lib/TriangleCountAlgo.scala
@@ -5,8 +5,8 @@
 
 package com.vesoft.nebula.algorithm.lib
 
-import com.vesoft.nebula.algorithm.config.AlgoConstants
-import com.vesoft.nebula.algorithm.utils.NebulaUtil
+import com.vesoft.nebula.algorithm.config.{AlgoConstants, TriangleConfig}
+import com.vesoft.nebula.algorithm.utils.{DecodeUtil, NebulaUtil}
 import org.apache.log4j.Logger
 import org.apache.spark.graphx.{Graph, VertexRDD}
 import org.apache.spark.graphx.lib.TriangleCount
@@ -24,9 +24,19 @@ object TriangleCountAlgo {
     *
     * compute each vertex's triangle count
     */
-  def apply(spark: SparkSession, dataset: Dataset[Row]): DataFrame = {
+  def apply(spark: SparkSession,
+            dataset: Dataset[Row],
+            triangleConfig: TriangleConfig = new TriangleConfig): DataFrame = {
 
-    val graph: Graph[None.type, Double] = NebulaUtil.loadInitGraph(dataset, false)
+    var encodeIdDf: DataFrame = null
+
+    val graph: Graph[None.type, Double] = if (triangleConfig.encodeId) {
+      val (data, encodeId) = DecodeUtil.convertStringId2LongId(dataset, false)
+      encodeIdDf = encodeId
+      NebulaUtil.loadInitGraph(data, false)
+    } else {
+      NebulaUtil.loadInitGraph(dataset, false)
+    }
 
     val triangleResultRDD = execute(graph)
 
@@ -38,7 +48,11 @@ object TriangleCountAlgo {
     val algoResult = spark.sqlContext
       .createDataFrame(triangleResultRDD, schema)
 
-    algoResult
+    if (triangleConfig.encodeId) {
+      DecodeUtil.convertAlgoId2StringId(algoResult, encodeIdDf)
+    } else {
+      algoResult
+    }
   }
 
   def execute(graph: Graph[None.type, Double]): RDD[Row] = {
diff --git a/nebula-algorithm/src/main/scala/com/vesoft/nebula/algorithm/utils/DecodeUtil.scala b/nebula-algorithm/src/main/scala/com/vesoft/nebula/algorithm/utils/DecodeUtil.scala
index 9343a24..f540240 100644
--- a/nebula-algorithm/src/main/scala/com/vesoft/nebula/algorithm/utils/DecodeUtil.scala
+++ b/nebula-algorithm/src/main/scala/com/vesoft/nebula/algorithm/utils/DecodeUtil.scala
@@ -73,4 +73,21 @@ object DecodeUtil {
       .drop(algoProp)
       .withColumnRenamed(ORIGIN_ID_COL, algoProp)
   }
+
+  def convertIds2String(dataframe: DataFrame,
+                        encodeId: DataFrame,
+                        srcCol: String,
+                        dstCol: String): DataFrame = {
+    encodeId
+      .join(dataframe)
+      .where(col(ENCODE_ID_COL) === col(srcCol))
+      .drop(ENCODE_ID_COL)
+      .drop(srcCol)
+      .withColumnRenamed(ORIGIN_ID_COL, srcCol)
+      .join(encodeId)
+      .where(col(dstCol) === col(ENCODE_ID_COL))
+      .drop(ENCODE_ID_COL)
+      .drop(dstCol)
+      .withColumnRenamed(ORIGIN_ID_COL, dstCol)
+  }
 }
diff --git a/nebula-algorithm/src/test/scala/com/vesoft/nebula/algorithm/lib/DegreeStaticAlgoSuite.scala b/nebula-algorithm/src/test/scala/com/vesoft/nebula/algorithm/lib/DegreeStaticAlgoSuite.scala
index bcf5b8f..29cf6f3 100644
--- a/nebula-algorithm/src/test/scala/com/vesoft/nebula/algorithm/lib/DegreeStaticAlgoSuite.scala
+++ b/nebula-algorithm/src/test/scala/com/vesoft/nebula/algorithm/lib/DegreeStaticAlgoSuite.scala
@@ -5,13 +5,15 @@
 
 package com.vesoft.nebula.algorithm.lib
 
+import com.vesoft.nebula.algorithm.config.DegreeStaticConfig
 import org.apache.spark.sql.SparkSession
 import org.junit.Test
 
 class DegreeStaticAlgoSuite {
   @Test
   def degreeStaticAlgoSuite(): Unit = {
-    val spark  = SparkSession.builder().master("local").getOrCreate()
+    val spark =
+      SparkSession.builder().master("local").config("spark.sql.shuffle.partitions", 5).getOrCreate()
     val data   = spark.read.option("header", true).csv("src/test/resources/edge.csv")
     val result = DegreeStaticAlgo.apply(spark, data)
     assert(result.count() == 4)
@@ -20,5 +22,9 @@ class DegreeStaticAlgoSuite {
       assert(row.get(2).toString.toInt == 4)
       assert(row.get(3).toString.toInt == 4)
     })
+
+    val config       = DegreeStaticConfig(true)
+    val encodeResult = DegreeStaticAlgo.apply(spark, data, config)
+    assert(result.count() == 4)
   }
 }
diff --git a/nebula-algorithm/src/test/scala/com/vesoft/nebula/algorithm/lib/HanpSuite.scala b/nebula-algorithm/src/test/scala/com/vesoft/nebula/algorithm/lib/HanpSuite.scala
index ed4bbfc..9a4acf1 100644
--- a/nebula-algorithm/src/test/scala/com/vesoft/nebula/algorithm/lib/HanpSuite.scala
+++ b/nebula-algorithm/src/test/scala/com/vesoft/nebula/algorithm/lib/HanpSuite.scala
@@ -14,10 +14,14 @@ import org.junit.Test
 class HanpSuite {
   @Test
   def hanpSuite() = {
-    val spark      = SparkSession.builder().master("local").getOrCreate()
+    val spark =
+      SparkSession.builder().master("local").config("spark.sql.shuffle.partitions", 5).getOrCreate()
     val data       = spark.read.option("header", true).csv("src/test/resources/edge.csv")
     val hanpConfig = new HanpConfig(0.1, 10, 1.0)
     val result     = HanpAlgo.apply(spark, data, hanpConfig, false)
     assert(result.count() == 4)
+
+    val encodeHanpConfig = new HanpConfig(0.1, 10, 1.0, true)
+    assert(HanpAlgo.apply(spark, data, encodeHanpConfig, false).count() == 4)
   }
 }
diff --git a/nebula-algorithm/src/test/scala/com/vesoft/nebula/algorithm/lib/JaccardAlgoSuite.scala b/nebula-algorithm/src/test/scala/com/vesoft/nebula/algorithm/lib/JaccardAlgoSuite.scala
index e4a7a52..2e2ab35 100644
--- a/nebula-algorithm/src/test/scala/com/vesoft/nebula/algorithm/lib/JaccardAlgoSuite.scala
+++ b/nebula-algorithm/src/test/scala/com/vesoft/nebula/algorithm/lib/JaccardAlgoSuite.scala
@@ -12,11 +12,16 @@ import org.junit.Test
 class JaccardAlgoSuite {
   @Test
   def kcoreSuite(): Unit = {
-    val spark         = SparkSession.builder().master("local").getOrCreate()
+    val spark =
+      SparkSession.builder().master("local").config("spark.sql.shuffle.partitions", 5).getOrCreate()
     val data          = spark.read.option("header", true).csv("src/test/resources/edge.csv")
     val jaccardConfig = new JaccardConfig(0.01)
     val jaccardResult = JaccardAlgo.apply(spark, data, jaccardConfig)
     jaccardResult.show()
     assert(jaccardResult.count() == 6)
+
+    val encodeJaccardConfig = new JaccardConfig(0.01, true)
+    val encodeJaccardResult = JaccardAlgo.apply(spark, data, encodeJaccardConfig)
+    assert(encodeJaccardResult.count() == 6)
   }
 }
diff --git a/nebula-algorithm/src/test/scala/com/vesoft/nebula/algorithm/lib/KCoreAlgoSuite.scala b/nebula-algorithm/src/test/scala/com/vesoft/nebula/algorithm/lib/KCoreAlgoSuite.scala
index feabe70..1a4370f 100644
--- a/nebula-algorithm/src/test/scala/com/vesoft/nebula/algorithm/lib/KCoreAlgoSuite.scala
+++ b/nebula-algorithm/src/test/scala/com/vesoft/nebula/algorithm/lib/KCoreAlgoSuite.scala
@@ -12,10 +12,14 @@ import org.junit.Test
 class KCoreAlgoSuite {
   @Test
   def kcoreSuite(): Unit = {
-    val spark       = SparkSession.builder().master("local").getOrCreate()
+    val spark =
+      SparkSession.builder().master("local").config("spark.sql.shuffle.partitions", 5).getOrCreate()
     val data        = spark.read.option("header", true).csv("src/test/resources/edge.csv")
     val kcoreConfig = new KCoreConfig(10, 3)
     val kcoreResult = KCoreAlgo.apply(spark, data, kcoreConfig)
     assert(kcoreResult.count() == 4)
+
+    val encodeKcoreConfig = new KCoreConfig(10, 3, true)
+    assert(KCoreAlgo.apply(spark, data, encodeKcoreConfig).count() == 4)
   }
 }
diff --git a/nebula-algorithm/src/test/scala/com/vesoft/nebula/algorithm/lib/LabelPropagationAlgoSuite.scala b/nebula-algorithm/src/test/scala/com/vesoft/nebula/algorithm/lib/LabelPropagationAlgoSuite.scala
index 8b7d585..7d27cf4 100644
--- a/nebula-algorithm/src/test/scala/com/vesoft/nebula/algorithm/lib/LabelPropagationAlgoSuite.scala
+++ b/nebula-algorithm/src/test/scala/com/vesoft/nebula/algorithm/lib/LabelPropagationAlgoSuite.scala
@@ -12,7 +12,8 @@ import org.junit.Test
 class LabelPropagationAlgoSuite {
   @Test
   def lpaAlgoSuite(): Unit = {
-    val spark     = SparkSession.builder().master("local").getOrCreate()
+    val spark =
+      SparkSession.builder().master("local").config("spark.sql.shuffle.partitions", 5).getOrCreate()
     val data      = spark.read.option("header", true).csv("src/test/resources/edge.csv")
     val lpaConfig = new LPAConfig(5)
     val result    = LabelPropagationAlgo.apply(spark, data, lpaConfig, false)
@@ -20,5 +21,8 @@ class LabelPropagationAlgoSuite {
     result.foreach(row => {
       assert(row.get(1).toString.toInt == 1)
     })
+
+    val encodeLpaConfig = new LPAConfig(5)
+    assert(LabelPropagationAlgo.apply(spark, data, encodeLpaConfig, false).count() == 4)
   }
 }
diff --git a/nebula-algorithm/src/test/scala/com/vesoft/nebula/algorithm/lib/PageRankAlgoSuite.scala b/nebula-algorithm/src/test/scala/com/vesoft/nebula/algorithm/lib/PageRankAlgoSuite.scala
index 54ec0dc..6808fdc 100644
--- a/nebula-algorithm/src/test/scala/com/vesoft/nebula/algorithm/lib/PageRankAlgoSuite.scala
+++ b/nebula-algorithm/src/test/scala/com/vesoft/nebula/algorithm/lib/PageRankAlgoSuite.scala
@@ -12,10 +12,14 @@ import org.junit.Test
 class PageRankAlgoSuite {
   @Test
   def pageRankSuite(): Unit = {
-    val spark    = SparkSession.builder().master("local").getOrCreate()
+    val spark =
+      SparkSession.builder().master("local").config("spark.sql.shuffle.partitions", 5).getOrCreate()
     val data     = spark.read.option("header", true).csv("src/test/resources/edge.csv")
     val prConfig = new PRConfig(5, 1.0)
     val prResult = PageRankAlgo.apply(spark, data, prConfig, false)
     assert(prResult.count() == 4)
+
+    val encodePrConfig = new PRConfig(5, 1.0, true)
+    assert(PageRankAlgo.apply(spark, data, encodePrConfig, false).count() == 5)
   }
 }
diff --git a/nebula-algorithm/src/test/scala/com/vesoft/nebula/algorithm/lib/SCCAlgoSuite.scala b/nebula-algorithm/src/test/scala/com/vesoft/nebula/algorithm/lib/SCCAlgoSuite.scala
index a55fb5d..fcdfe7b 100644
--- a/nebula-algorithm/src/test/scala/com/vesoft/nebula/algorithm/lib/SCCAlgoSuite.scala
+++ b/nebula-algorithm/src/test/scala/com/vesoft/nebula/algorithm/lib/SCCAlgoSuite.scala
@@ -12,10 +12,14 @@ import org.junit.Test
 class SCCAlgoSuite {
   @Test
   def sccAlgoSuite(): Unit = {
-    val spark     = SparkSession.builder().master("local").getOrCreate()
+    val spark =
+      SparkSession.builder().master("local").config("spark.sql.shuffle.partitions", 5).getOrCreate()
     val data      = spark.read.option("header", true).csv("src/test/resources/edge.csv")
     val sccConfig = new CcConfig(5)
     val sccResult = StronglyConnectedComponentsAlgo.apply(spark, data, sccConfig, true)
     assert(sccResult.count() == 4)
+
+    val encodeSccConfig = new CcConfig(5, true)
+    StronglyConnectedComponentsAlgo.apply(spark, data, encodeSccConfig, true)
   }
 }
diff --git a/nebula-algorithm/src/test/scala/com/vesoft/nebula/algorithm/lib/TrangleCountSuite.scala b/nebula-algorithm/src/test/scala/com/vesoft/nebula/algorithm/lib/TrangleCountSuite.scala
index b93f8d9..9068c30 100644
--- a/nebula-algorithm/src/test/scala/com/vesoft/nebula/algorithm/lib/TrangleCountSuite.scala
+++ b/nebula-algorithm/src/test/scala/com/vesoft/nebula/algorithm/lib/TrangleCountSuite.scala
@@ -5,13 +5,15 @@
 
 package com.vesoft.nebula.algorithm.lib
 
+import com.vesoft.nebula.algorithm.config.TriangleConfig
 import org.apache.spark.sql.SparkSession
 import org.junit.Test
 
 class TrangleCountSuite {
   @Test
   def trangleCountSuite(): Unit = {
-    val spark              = SparkSession.builder().master("local").getOrCreate()
+    val spark =
+      SparkSession.builder().master("local").config("spark.sql.shuffle.partitions", 5).getOrCreate()
     val data               = spark.read.option("header", true).csv("src/test/resources/edge.csv")
     val trangleCountResult = TriangleCountAlgo.apply(spark, data)
     assert(trangleCountResult.count() == 4)
@@ -19,5 +21,8 @@ class TrangleCountSuite {
     trangleCountResult.foreach(row => {
       assert(row.get(1) == 3)
     })
+
+    val triangleConfig = TriangleConfig(true)
+    assert(TriangleCountAlgo.apply(spark, data, triangleConfig).count() == 4)
   }
 }