From 2b54d190b0c5d1c172f3a1c0baedab61839ec6b9 Mon Sep 17 00:00:00 2001
From: semyonsinchenko <ssinchenko@apache.org>
Date: Fri, 24 Oct 2025 11:25:44 +0200
Subject: [PATCH 1/2] maximal independent set

---
 connect/src/main/protobuf/graphframes.proto   |   8 +
 .../graphframes/GraphFramesConnectUtils.scala |  13 +
 .../scala/org/graphframes/GraphFrame.scala    |   9 +
 .../lib/MaximalIndependentSet.scala           | 225 ++++++++++++++++++
 .../lib/MaximalIndependentSetSuite.scala      | 121 ++++++++++
 python/graphframes/classic/graphframe.py      |  15 ++
 .../graphframes/connect/graphframes_client.py |  55 +++++
 .../connect/proto/graphframes_pb2.py          |  90 +++----
 .../connect/proto/graphframes_pb2.pyi         | 136 ++++-------
 python/graphframes/graphframe.py              |  42 ++++
 python/tests/test_graphframes.py              |  22 ++
 11 files changed, 597 insertions(+), 139 deletions(-)
 create mode 100644 core/src/main/scala/org/graphframes/lib/MaximalIndependentSet.scala
 create mode 100644 core/src/test/scala/org/graphframes/lib/MaximalIndependentSetSuite.scala

diff --git a/connect/src/main/protobuf/graphframes.proto b/connect/src/main/protobuf/graphframes.proto
index c22223941..42a0b3c27 100644
--- a/connect/src/main/protobuf/graphframes.proto
+++ b/connect/src/main/protobuf/graphframes.proto
@@ -35,6 +35,7 @@ message GraphFramesAPI {
     SVDPlusPlus svd_plus_plus = 18;
     TriangleCount triangle_count = 19;
     Triplets triplets = 20;
+    MaximalIndependentSet mis = 22;
   }
 }
 
@@ -186,3 +187,10 @@ message TriangleCount {
 }
 
 message Triplets {}
+
+message MaximalIndependentSet {
+  int32 checkpoint_interval = 1;
+  optional StorageLevel storage_level = 2;
+  bool use_local_checkpoints = 3;
+  int64 seed = 4;
+}
diff --git a/connect/src/main/scala/org/apache/spark/sql/graphframes/GraphFramesConnectUtils.scala b/connect/src/main/scala/org/apache/spark/sql/graphframes/GraphFramesConnectUtils.scala
index ea63ae281..bf7836925 100644
--- a/connect/src/main/scala/org/apache/spark/sql/graphframes/GraphFramesConnectUtils.scala
+++ b/connect/src/main/scala/org/apache/spark/sql/graphframes/GraphFramesConnectUtils.scala
@@ -399,6 +399,19 @@ object GraphFramesConnectUtils {
       case proto.GraphFramesAPI.MethodCase.TRIPLETS => {
         graphFrame.triplets
       }
+      case proto.GraphFramesAPI.MethodCase.MIS => {
+        val mis = graphFrame.maximalIndependentSet
+          .setCheckpointInterval(apiMessage.getMis.getCheckpointInterval)
+          .setUseLocalCheckpoints(apiMessage.getMis.getUseLocalCheckpoints)
+
+        if (apiMessage.getMis.hasStorageLevel) {
+          mis
+            .setIntermediateStorageLevel(parseStorageLevel(apiMessage.getMis.getStorageLevel))
+            .run(apiMessage.getMis.getSeed)
+        } else {
+          mis.run(apiMessage.getMis.getSeed)
+        }
+      }
       case _ => throw new GraphFramesUnreachableException() // Unreachable
     }
   }
diff --git a/core/src/main/scala/org/graphframes/GraphFrame.scala b/core/src/main/scala/org/graphframes/GraphFrame.scala
index af2a1ae1e..11df5018c 100644
--- a/core/src/main/scala/org/graphframes/GraphFrame.scala
+++ b/core/src/main/scala/org/graphframes/GraphFrame.scala
@@ -701,6 +701,15 @@ class GraphFrame private (
    */
   def detectingCycles: DetectingCycles = new DetectingCycles(this)
 
+  /**
+   * Maximal Independent Set algorithm.
+   *
+   * See [[org.graphframes.lib.MaximalIndependentSet]] for more details.
+   *
+   * @group stdlib
+   */
+  def maximalIndependentSet: MaximalIndependentSet = new MaximalIndependentSet(this)
+
   /**
    * Converts the directed graph into an undirected graph by ensuring that all directed edges are
    * bidirectional. For every directed edge (src, dst), a corresponding edge (dst, src) is added.
diff --git a/core/src/main/scala/org/graphframes/lib/MaximalIndependentSet.scala b/core/src/main/scala/org/graphframes/lib/MaximalIndependentSet.scala
new file mode 100644
index 000000000..41cca2d0c
--- /dev/null
+++ b/core/src/main/scala/org/graphframes/lib/MaximalIndependentSet.scala
@@ -0,0 +1,225 @@
+package org.graphframes.lib
+
+import org.apache.spark.sql.DataFrame
+import org.apache.spark.sql.functions.*
+import org.apache.spark.sql.types.DoubleType
+import org.apache.spark.storage.StorageLevel
+import org.graphframes.GraphFrame
+import org.graphframes.Logging
+import org.graphframes.WithCheckpointInterval
+import org.graphframes.WithIntermediateStorageLevel
+import org.graphframes.WithLocalCheckpoints
+
+import java.io.IOException
+
+/**
+ * This class implements a distributed algorithm for finding a Maximal Independent Set (MIS) in a
+ * graph.
+ *
+ * An MIS is a set of vertices such that no two vertices in the set are adjacent (i.e., there is
+ * no edge between any two vertices in the set), and the set is maximal, meaning that adding any
+ * other vertex to the set would violate the independence property. Note that this implementation
+ * finds a maximal (but not necessarily maximum) independent set; that is, it ensures no more
+ * vertices can be added to the set, but does not guarantee that the set has the largest possible
+ * number of vertices among all possible independent sets in the graph.
+ *
+ * The algorithm implemented here is based on the paper: Ghaffari, Mohsen. "An improved
+ * distributed algorithm for maximal independent set." Proceedings of the twenty-seventh annual
+ * ACM-SIAM symposium on Discrete algorithms. Society for Industrial and Applied Mathematics,
+ * 2016.
+ *
+ * Note: This is a randomized, non-deterministic algorithm. The result may vary between runs even
+ * if a fixed random seed is provided because how Apache Spark works.
+ *
+ * @param graph
+ */
+class MaximalIndependentSet private[graphframes] (private val graph: GraphFrame)
+    extends Serializable
+    with WithIntermediateStorageLevel
+    with WithCheckpointInterval
+    with WithLocalCheckpoints {
+  def run(seed: Long): DataFrame = {
+    MaximalIndependentSet.run(
+      graph,
+      checkpointInterval,
+      useLocalCheckpoints,
+      intermediateStorageLevel,
+      seed)
+  }
+}
+
+object MaximalIndependentSet extends Serializable with Logging {
+  private val probCol = "prob"
+  private val degCol = "effectiveDegree"
+  private val isNominated = "isNominated"
+  private val notJoinedMISCol = "notJoinMIS"
+  private val isMIS = "isMIS"
+
+  private def run(
+      graph: GraphFrame,
+      checkpointInterval: Int,
+      useLocalCheckpoints: Boolean,
+      storageLevel: StorageLevel,
+      seed: Long): DataFrame = {
+    // initial p = 1/2
+    var vertices =
+      graph.vertices
+        .select(col(GraphFrame.ID), lit(0.5).cast(DoubleType).alias(probCol))
+        .persist(storageLevel)
+
+    // make edges undirected and de-duplicate
+    // persist() for future usage
+    val edges = graph.edges
+      .select(GraphFrame.SRC, GraphFrame.DST)
+      .union(
+        graph.edges.select(
+          col(GraphFrame.DST).alias(GraphFrame.SRC),
+          col(GraphFrame.SRC).alias(GraphFrame.DST)))
+      .filter(col(GraphFrame.SRC) =!= col(GraphFrame.DST))
+      .distinct()
+      .persist(storageLevel)
+
+    var misDF = graph.vertices.select(col(GraphFrame.ID), lit(false).alias(isMIS))
+
+    var i = 0
+    var converged = false
+    val spark = graph.vertices.sparkSession
+
+    val shouldCheckpoint = checkpointInterval > 0
+    if (!useLocalCheckpoints && spark.sparkContext.getCheckpointDir.isEmpty) {
+      // Spark-Connect workaround
+      spark.sparkContext
+        .setCheckpointDir(spark.conf
+          .getOption("spark.checkpoint.dir") match {
+          case Some(d) => d
+          case None =>
+            throw new IOException(
+              "Checkpoint directory is not set. Please set it first using sc.setCheckpointDir()" +
+                "or by specifying the conf 'spark.checkpoint.dir'.")
+        })
+    }
+
+    val rng = new util.Random(seed)
+
+    // randomized algorithms are not working with AQE well
+    val originalAQE = spark.conf.get("spark.sql.adaptive.enabled")
+    try {
+      spark.conf.set("spark.sql.adaptive.enabled", "false")
+
+      while (!converged) {
+        val iterSeed = rng.nextLong()
+        // compute effective degree as a sum of nbrs p
+        val effectiveDegrees =
+          edges
+            .join(vertices, col(GraphFrame.ID) === col(GraphFrame.DST))
+            .groupBy(GraphFrame.SRC)
+            .agg(sum(col(probCol)).alias(degCol))
+
+        // update p per vertex by condition:
+        // if effective degree >= 2 then p / 2
+        // else min(2p, 1/2)
+        //
+        // + mark vertices based on p
+        val probs = vertices
+          .join(effectiveDegrees, col(GraphFrame.ID) === col(GraphFrame.SRC))
+          .drop(GraphFrame.SRC)
+          .withColumn(
+            probCol,
+            when(col(degCol) >= lit(2), col(probCol) / lit(2.0)).otherwise(
+              when(lit(2) * col(probCol) <= lit(0.5), lit(2) * col(probCol)).otherwise(lit(0.5))))
+          .withColumn(isNominated, col(probCol) >= rand(iterSeed))
+          .select(GraphFrame.ID, isNominated, probCol)
+          .persist(storageLevel)
+
+        val isolatedVertices =
+          vertices
+            .join(probs.select(col(GraphFrame.ID)), Seq(GraphFrame.ID), "left_anti")
+            .select(GraphFrame.ID)
+
+        // if no nbr of v is marked and v is marked,
+        // v is joined MIS and removed with all it's nbrs
+        val isJoinedMIS = probs
+          .join(
+            edges
+              .join(probs, col(GraphFrame.ID) === col(GraphFrame.DST))
+              .groupBy(GraphFrame.SRC)
+              .agg(bool_or(col(isNominated)).alias(notJoinedMISCol)),
+            col(GraphFrame.SRC) === col(GraphFrame.ID))
+          .select(GraphFrame.ID, probCol, isNominated, notJoinedMISCol)
+
+        val joinedMIS =
+          isJoinedMIS.filter((!col(notJoinedMISCol)) && col(isNominated)).select(GraphFrame.ID)
+
+        // update curent MIS
+        val updatedMIS = misDF
+          .join(
+            isolatedVertices.select(col(GraphFrame.ID), lit(true).alias("f")),
+            Seq(GraphFrame.ID),
+            "left")
+          .select(col(GraphFrame.ID), (col(isMIS) || col("f")).alias(isMIS))
+          .join(
+            joinedMIS.select(col(GraphFrame.ID), lit(true).alias("f")),
+            Seq(GraphFrame.ID),
+            "left")
+          .select(col(GraphFrame.ID), (col(isMIS) || col("f")).alias(isMIS))
+          .persist(storageLevel)
+
+        // We cannot not checkpoint current MIS, otherwise it is almost not working.
+        if (useLocalCheckpoints) {
+          val newMis = updatedMIS.localCheckpoint(eager = true)
+          newMis.count()
+          misDF.unpersist()
+          misDF = newMis
+        } else {
+          val newMis = updatedMIS.checkpoint(eager = true)
+          newMis.count()
+          misDF.unpersist()
+          misDF = newMis
+        }
+
+        val neighborsOfMIS = edges
+          .join(joinedMIS, col(GraphFrame.ID) === col(GraphFrame.DST))
+          .select(col(GraphFrame.SRC))
+
+        val updatedVertices = probs
+          .join(joinedMIS, Seq(GraphFrame.ID), "left_anti")
+          .join(neighborsOfMIS, col(GraphFrame.ID) === col(GraphFrame.SRC), "left_anti")
+          .select(GraphFrame.ID, probCol)
+
+        // checkpointing of vertices
+        if (shouldCheckpoint && (i % checkpointInterval == 0)) {
+          if (useLocalCheckpoints) {
+            vertices = updatedVertices.localCheckpoint(eager = true)
+          } else {
+            vertices = updatedVertices.checkpoint(eager = true)
+          }
+        } else {
+          vertices = updatedVertices
+        }
+
+        // algorithm stops if no more vertex left
+        converged = vertices.isEmpty
+
+        updatedVertices.unpersist()
+        probs.unpersist()
+
+        logInfo(s"iteration $i finished, vertices left: ${vertices.count()}")
+        i += 1
+      }
+
+      vertices.unpersist(true)
+      edges.unpersist(true)
+
+      val mis = misDF.filter(col(isMIS)).select(GraphFrame.ID).persist(storageLevel)
+      // materialize
+      mis.count()
+      resultIsPersistent()
+      misDF.unpersist(true)
+
+      mis
+    } finally {
+      // Restore original AQE setting
+      spark.conf.set("spark.sql.adaptive.enabled", originalAQE)
+    }
+  }
+}
diff --git a/core/src/test/scala/org/graphframes/lib/MaximalIndependentSetSuite.scala b/core/src/test/scala/org/graphframes/lib/MaximalIndependentSetSuite.scala
new file mode 100644
index 000000000..80c5416d4
--- /dev/null
+++ b/core/src/test/scala/org/graphframes/lib/MaximalIndependentSetSuite.scala
@@ -0,0 +1,121 @@
+package org.graphframes.lib
+
+import org.apache.spark.sql.DataFrame
+import org.apache.spark.sql.functions.col
+import org.graphframes.*
+import org.graphframes.examples.Graphs
+
+class MaximalIndependentSetSuite extends SparkFunSuite with GraphFrameTestSparkContext {
+  test("isolated vertices should be included in MIS") {
+    // Create a graph with isolated vertices
+    val vertices =
+      spark.createDataFrame(Seq((0L, "a"), (1L, "b"), (2L, "c"), (3L, "d"))).toDF("id", "name")
+
+    // Only connect vertices 0 and 1
+    val edges = spark.createDataFrame(Seq((0L, 1L, "edge1"))).toDF("src", "dst", "name")
+
+    val graph = GraphFrame(vertices, edges)
+    val mis = graph.maximalIndependentSet.run(seed = 12345L)
+
+    // Check that all vertices are in the MIS (since 2 and 3 are isolated)
+    val misIds = mis.select("id").collect().map(_.getLong(0)).toSet
+    assert(misIds.size == 3, "MIS should contain 2 isolated vertices and one of linked")
+    assert(misIds.contains(2L), "Isolated vertex 2 should be in MIS")
+    assert(misIds.contains(3L), "Isolated vertex 3 should be in MIS")
+
+    mis.unpersist()
+  }
+
+  def isIndependent(graph: GraphFrame, mis: DataFrame): Boolean = {
+    graph.edges
+      .join(mis, col(GraphFrame.SRC) === col(GraphFrame.ID))
+      .select(col(GraphFrame.DST))
+      .join(mis, col(GraphFrame.DST) === col(GraphFrame.ID))
+      .count() == 0
+  }
+
+  def isMaximal(graph: GraphFrame, mis: DataFrame): Boolean = {
+    val undirectedG = graph.asUndirected()
+    val verticesNotInMIS = undirectedG.vertices.join(mis, Seq(GraphFrame.ID), "left_anti")
+
+    val verticesWithEdgesToMIS = undirectedG.edges
+      .join(mis, col(GraphFrame.ID) === col(GraphFrame.DST))
+      .select(GraphFrame.SRC)
+      .distinct()
+
+    val countVerticesNotInMIS = verticesNotInMIS.count()
+    val countVerticesWithEdgesToMIS = verticesWithEdgesToMIS.count()
+
+    countVerticesNotInMIS == countVerticesWithEdgesToMIS
+  }
+
+  test("correct MIS, seed 12345") {
+    val graph = Graphs.friends
+
+    val mis = graph.maximalIndependentSet.run(seed = 12345L)
+
+    assert(isIndependent(graph, mis))
+    assert(isMaximal(graph, mis))
+
+    mis.unpersist()
+  }
+
+  test("correct MIS, seed 23456") {
+    val graph = Graphs.friends
+
+    val mis = graph.maximalIndependentSet.run(seed = 23456L)
+
+    assert(isIndependent(graph, mis))
+    assert(isMaximal(graph, mis))
+
+    mis.unpersist()
+  }
+
+  test("MIS on empty graph") {
+    val emptyGraph = Graphs.empty[Long]
+    val mis = emptyGraph.maximalIndependentSet.run(seed = 12345L)
+    assert(mis.count() == 0, "MIS of empty graph should be empty")
+    mis.unpersist()
+  }
+
+  test("MIS on single vertex graph") {
+    val vertices = spark.createDataFrame(Seq((0L, "vertex"))).toDF("id", "name")
+    val edges = spark.createDataFrame(Seq.empty[(Long, Long)]).toDF("src", "dst")
+    val graph = GraphFrame(vertices, edges)
+
+    val mis = graph.maximalIndependentSet.run(seed = 12345L)
+    assert(mis.count() == 1, "MIS of single vertex graph should contain one vertex")
+
+    val misId = mis.select("id").collect()(0).getLong(0)
+    assert(misId == 0L, "MIS should contain vertex with id 0")
+
+    mis.unpersist()
+  }
+
+  test("MIS on disconnected vertices") {
+    val n = 5L
+    val vertices = spark.range(n).toDF("id")
+    val edges = spark.createDataFrame(Seq.empty[(Long, Long)]).toDF("src", "dst")
+    val graph = GraphFrame(vertices, edges)
+
+    val mis = graph.maximalIndependentSet.run(seed = 12345L)
+    assert(mis.count() == n, s"MIS should contain all $n vertices for disconnected graph")
+
+    mis.unpersist()
+  }
+
+  test("MIS on complete graph of 5 vertices") {
+    val vertices = spark.range(5).toDF("id")
+    val edges = for {
+      i <- 0L until 5L
+      j <- (i + 1L) until 5L
+    } yield (i, j)
+    val edgeDF = spark.createDataFrame(edges).toDF("src", "dst")
+    val graph = GraphFrame(vertices, edgeDF)
+
+    val mis = graph.maximalIndependentSet.run(seed = 12345L)
+    assert(mis.count() == 1, "MIS of complete graph should contain exactly one vertex")
+
+    mis.unpersist()
+  }
+}
diff --git a/python/graphframes/classic/graphframe.py b/python/graphframes/classic/graphframe.py
index ab9618906..b9a7fcf1e 100644
--- a/python/graphframes/classic/graphframe.py
+++ b/python/graphframes/classic/graphframe.py
@@ -341,3 +341,18 @@ def powerIterationClustering(
             weightCol = self._spark._jvm.scala.Option.empty()
         jdf = self._jvm_graph.powerIterationClustering(k, maxIter, weightCol)
         return DataFrame(jdf, self._spark)
+
+    def maximal_independent_set(
+        self,
+        checkpoint_interval: int,
+        storage_level: StorageLevel,
+        use_local_checkpoints: bool,
+        seed: int,
+    ) -> DataFrame:
+        builder = self._jvm_graph.maximalIndependentSet()
+        builder.setCheckpointInterval(checkpoint_interval)
+        builder.setIntermediateStorageLevel(storage_level_to_jvm(storage_level, self._spark))
+        builder.setUseLocalCheckpoints(use_local_checkpoints)
+
+        jdf = builder.run(seed)
+        return DataFrame(jdf, self._spark)
diff --git a/python/graphframes/connect/graphframes_client.py b/python/graphframes/connect/graphframes_client.py
index 2e64d7a41..2ea77cee8 100644
--- a/python/graphframes/connect/graphframes_client.py
+++ b/python/graphframes/connect/graphframes_client.py
@@ -1064,3 +1064,58 @@ def plan(self, session: SparkConnectClient) -> proto.Relation:
         return _dataframe_from_plan(
             TriangleCount(self._vertices, self._edges, storage_level), self._spark
         )
+
+    def maximal_independent_set(
+        self,
+        checkpoint_interval: int,
+        storage_level: StorageLevel,
+        use_local_checkpoints: bool,
+        seed: int,
+    ) -> DataFrame:
+        @final
+        class MaximalIndependentSet(LogicalPlan):
+            def __init__(
+                self,
+                v: DataFrame,
+                e: DataFrame,
+                checkpoint_interval: int,
+                storage_level: StorageLevel,
+                use_local_checkpoints: bool,
+                seed: int,
+            ) -> None:
+                super().__init__(None)
+                self.v = v
+                self.e = e
+                self.checkpoint_interval = checkpoint_interval
+                self.storage_level = (storage_level,)
+                self.use_local_checkpoints = use_local_checkpoints
+                self.seed = seed
+
+            @override
+            def plan(self, session: SparkConnectClient) -> proto.Relation:
+                graphframes_api_call = GraphFrameConnect._get_pb_api_message(
+                    self.v, self.e, session
+                )
+                graphframes_api_call.mis.CopyFrom(
+                    pb.MaximalIndependentSet(
+                        checkpoint_interval=self.checkpoint_interval,
+                        storage_level=storage_level_to_proto(self.storage_level),
+                        use_local_checkpoints=self.use_local_checkpoints,
+                        seed=self.seed,
+                    )
+                )
+                plan = self._create_proto_relation()
+                plan.extension.Pack(graphframes_api_call)
+                return plan
+
+        return _dataframe_from_plan(
+            MaximalIndependentSet(
+                self._vertices,
+                self._edges,
+                checkpoint_interval,
+                storage_level,
+                use_local_checkpoints,
+                seed,
+            ),
+            self._spark,
+        )
diff --git a/python/graphframes/connect/proto/graphframes_pb2.py b/python/graphframes/connect/proto/graphframes_pb2.py
index a34f42a42..cf3731ba9 100644
--- a/python/graphframes/connect/proto/graphframes_pb2.py
+++ b/python/graphframes/connect/proto/graphframes_pb2.py
@@ -19,7 +19,7 @@
 
 
 DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(
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\x01(\x05R\x07maxIter"v\n\x18PowerIterationClustering\x12\x0c\n\x01k\x18\x01 \x01(\x05R\x01k\x12\x19\n\x08max_iter\x18\x02 \x01(\x05R\x07maxIter\x12"\n\nweight_col\x18\x03 \x01(\tH\x00R\tweightCol\x88\x01\x01\x42\r\n\x0b_weight_col"\xe6\t\n\x06Pregel\x12L\n\x08\x61gg_msgs\x18\x01 \x01(\x0b\x32\x31.org.graphframes.connect.proto.ColumnOrExpressionR\x07\x61ggMsgs\x12X\n\x0fsend_msg_to_dst\x18\x02 \x03(\x0b\x32\x31.org.graphframes.connect.proto.ColumnOrExpressionR\x0csendMsgToDst\x12X\n\x0fsend_msg_to_src\x18\x03 \x03(\x0b\x32\x31.org.graphframes.connect.proto.ColumnOrExpressionR\x0csendMsgToSrc\x12/\n\x13\x63heckpoint_interval\x18\x04 \x01(\x05R\x12\x63heckpointInterval\x12\x19\n\x08max_iter\x18\x05 \x01(\x05R\x07maxIter\x12.\n\x13\x61\x64\x64itional_col_name\x18\x06 \x01(\tR\x11\x61\x64\x64itionalColName\x12g\n\x16\x61\x64\x64itional_col_initial\x18\x07 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\x01(\x03R\x04seedB\x10\n\x0e_storage_levelB\xd2\x01\n!com.org.graphframes.connect.protoB\x10GraphframesProtoH\x01P\x01\xa0\x01\x01\xa2\x02\x04OGCP\xaa\x02\x1dOrg.Graphframes.Connect.Proto\xca\x02\x1dOrg\\Graphframes\\Connect\\Proto\xe2\x02)Org\\Graphframes\\Connect\\Proto\\GPBMetadata\xea\x02 Org::Graphframes::Connect::Protob\x06proto3'
 )
 
 _globals = globals()
@@ -31,47 +31,49 @@
         "DESCRIPTOR"
     ]._serialized_options = b"\n!com.org.graphframes.connect.protoB\020GraphframesProtoH\001P\001\240\001\001\242\002\004OGCP\252\002\035Org.Graphframes.Connect.Proto\312\002\035Org\\Graphframes\\Connect\\Proto\342\002)Org\\Graphframes\\Connect\\Proto\\GPBMetadata\352\002 Org::Graphframes::Connect::Proto"
     _globals["_GRAPHFRAMESAPI"]._serialized_start = 53
-    _globals["_GRAPHFRAMESAPI"]._serialized_end = 1768
-    _globals["_STORAGELEVEL"]._serialized_start = 1771
-    _globals["_STORAGELEVEL"]._serialized_end = 2114
-    _globals["_COLUMNOREXPRESSION"]._serialized_start = 2116
-    _globals["_COLUMNOREXPRESSION"]._serialized_end = 2193
-    _globals["_STRINGORLONGID"]._serialized_start = 2195
-    _globals["_STRINGORLONGID"]._serialized_end = 2275
-    _globals["_AGGREGATEMESSAGES"]._serialized_start = 2278
-    _globals["_AGGREGATEMESSAGES"]._serialized_end = 2644
-    _globals["_BFS"]._serialized_start = 2647
-    _globals["_BFS"]._serialized_end = 2932
-    _globals["_CONNECTEDCOMPONENTS"]._serialized_start = 2935
-    _globals["_CONNECTEDCOMPONENTS"]._serialized_end = 3325
-    _globals["_DETECTINGCYCLES"]._serialized_start = 3328
-    _globals["_DETECTINGCYCLES"]._serialized_end = 3551
-    _globals["_DROPISOLATEDVERTICES"]._serialized_start = 3553
-    _globals["_DROPISOLATEDVERTICES"]._serialized_end = 3575
-    _globals["_FILTEREDGES"]._serialized_start = 3577
-    _globals["_FILTEREDGES"]._serialized_end = 3671
-    _globals["_FILTERVERTICES"]._serialized_start = 3673
-    _globals["_FILTERVERTICES"]._serialized_end = 3770
-    _globals["_FIND"]._serialized_start = 3772
-    _globals["_FIND"]._serialized_end = 3804
-    _globals["_LABELPROPAGATION"]._serialized_start = 3807
-    _globals["_LABELPROPAGATION"]._serialized_end = 4088
-    _globals["_PAGERANK"]._serialized_start = 4091
-    _globals["_PAGERANK"]._serialized_end = 4317
-    _globals["_PARALLELPERSONALIZEDPAGERANK"]._serialized_start = 4320
-    _globals["_PARALLELPERSONALIZEDPAGERANK"]._serialized_end = 4500
-    _globals["_POWERITERATIONCLUSTERING"]._serialized_start = 4502
-    _globals["_POWERITERATIONCLUSTERING"]._serialized_end = 4620
-    _globals["_PREGEL"]._serialized_start = 4623
-    _globals["_PREGEL"]._serialized_end = 5877
-    _globals["_SHORTESTPATHS"]._serialized_start = 5880
-    _globals["_SHORTESTPATHS"]._serialized_end = 6208
-    _globals["_STRONGLYCONNECTEDCOMPONENTS"]._serialized_start = 6210
-    _globals["_STRONGLYCONNECTEDCOMPONENTS"]._serialized_end = 6266
-    _globals["_SVDPLUSPLUS"]._serialized_start = 6269
-    _globals["_SVDPLUSPLUS"]._serialized_end = 6483
-    _globals["_TRIANGLECOUNT"]._serialized_start = 6485
-    _globals["_TRIANGLECOUNT"]._serialized_end = 6605
-    _globals["_TRIPLETS"]._serialized_start = 6607
-    _globals["_TRIPLETS"]._serialized_end = 6617
+    _globals["_GRAPHFRAMESAPI"]._serialized_end = 1842
+    _globals["_STORAGELEVEL"]._serialized_start = 1845
+    _globals["_STORAGELEVEL"]._serialized_end = 2188
+    _globals["_COLUMNOREXPRESSION"]._serialized_start = 2190
+    _globals["_COLUMNOREXPRESSION"]._serialized_end = 2267
+    _globals["_STRINGORLONGID"]._serialized_start = 2269
+    _globals["_STRINGORLONGID"]._serialized_end = 2349
+    _globals["_AGGREGATEMESSAGES"]._serialized_start = 2352
+    _globals["_AGGREGATEMESSAGES"]._serialized_end = 2718
+    _globals["_BFS"]._serialized_start = 2721
+    _globals["_BFS"]._serialized_end = 3006
+    _globals["_CONNECTEDCOMPONENTS"]._serialized_start = 3009
+    _globals["_CONNECTEDCOMPONENTS"]._serialized_end = 3399
+    _globals["_DETECTINGCYCLES"]._serialized_start = 3402
+    _globals["_DETECTINGCYCLES"]._serialized_end = 3625
+    _globals["_DROPISOLATEDVERTICES"]._serialized_start = 3627
+    _globals["_DROPISOLATEDVERTICES"]._serialized_end = 3649
+    _globals["_FILTEREDGES"]._serialized_start = 3651
+    _globals["_FILTEREDGES"]._serialized_end = 3745
+    _globals["_FILTERVERTICES"]._serialized_start = 3747
+    _globals["_FILTERVERTICES"]._serialized_end = 3844
+    _globals["_FIND"]._serialized_start = 3846
+    _globals["_FIND"]._serialized_end = 3878
+    _globals["_LABELPROPAGATION"]._serialized_start = 3881
+    _globals["_LABELPROPAGATION"]._serialized_end = 4162
+    _globals["_PAGERANK"]._serialized_start = 4165
+    _globals["_PAGERANK"]._serialized_end = 4391
+    _globals["_PARALLELPERSONALIZEDPAGERANK"]._serialized_start = 4394
+    _globals["_PARALLELPERSONALIZEDPAGERANK"]._serialized_end = 4574
+    _globals["_POWERITERATIONCLUSTERING"]._serialized_start = 4576
+    _globals["_POWERITERATIONCLUSTERING"]._serialized_end = 4694
+    _globals["_PREGEL"]._serialized_start = 4697
+    _globals["_PREGEL"]._serialized_end = 5951
+    _globals["_SHORTESTPATHS"]._serialized_start = 5954
+    _globals["_SHORTESTPATHS"]._serialized_end = 6282
+    _globals["_STRONGLYCONNECTEDCOMPONENTS"]._serialized_start = 6284
+    _globals["_STRONGLYCONNECTEDCOMPONENTS"]._serialized_end = 6340
+    _globals["_SVDPLUSPLUS"]._serialized_start = 6343
+    _globals["_SVDPLUSPLUS"]._serialized_end = 6557
+    _globals["_TRIANGLECOUNT"]._serialized_start = 6559
+    _globals["_TRIANGLECOUNT"]._serialized_end = 6679
+    _globals["_TRIPLETS"]._serialized_start = 6681
+    _globals["_TRIPLETS"]._serialized_end = 6691
+    _globals["_MAXIMALINDEPENDENTSET"]._serialized_start = 6694
+    _globals["_MAXIMALINDEPENDENTSET"]._serialized_end = 6943
 # @@protoc_insertion_point(module_scope)
diff --git a/python/graphframes/connect/proto/graphframes_pb2.pyi b/python/graphframes/connect/proto/graphframes_pb2.pyi
index ffe59932d..6544824da 100644
--- a/python/graphframes/connect/proto/graphframes_pb2.pyi
+++ b/python/graphframes/connect/proto/graphframes_pb2.pyi
@@ -11,28 +11,7 @@ from google.protobuf.internal import containers as _containers
 DESCRIPTOR: _descriptor.FileDescriptor
 
 class GraphFramesAPI(_message.Message):
-    __slots__ = (
-        "vertices",
-        "edges",
-        "aggregate_messages",
-        "bfs",
-        "connected_components",
-        "drop_isolated_vertices",
-        "detecting_cycles",
-        "filter_edges",
-        "filter_vertices",
-        "find",
-        "label_propagation",
-        "page_rank",
-        "parallel_personalized_page_rank",
-        "power_iteration_clustering",
-        "pregel",
-        "shortest_paths",
-        "strongly_connected_components",
-        "svd_plus_plus",
-        "triangle_count",
-        "triplets",
-    )
+    __slots__ = ()
     VERTICES_FIELD_NUMBER: _ClassVar[int]
     EDGES_FIELD_NUMBER: _ClassVar[int]
     AGGREGATE_MESSAGES_FIELD_NUMBER: _ClassVar[int]
@@ -53,6 +32,7 @@ class GraphFramesAPI(_message.Message):
     SVD_PLUS_PLUS_FIELD_NUMBER: _ClassVar[int]
     TRIANGLE_COUNT_FIELD_NUMBER: _ClassVar[int]
     TRIPLETS_FIELD_NUMBER: _ClassVar[int]
+    MIS_FIELD_NUMBER: _ClassVar[int]
     vertices: bytes
     edges: bytes
     aggregate_messages: AggregateMessages
@@ -73,6 +53,7 @@ class GraphFramesAPI(_message.Message):
     svd_plus_plus: SVDPlusPlus
     triangle_count: TriangleCount
     triplets: Triplets
+    mis: MaximalIndependentSet
     def __init__(
         self,
         vertices: _Optional[bytes] = ...,
@@ -99,19 +80,11 @@ class GraphFramesAPI(_message.Message):
         svd_plus_plus: _Optional[_Union[SVDPlusPlus, _Mapping]] = ...,
         triangle_count: _Optional[_Union[TriangleCount, _Mapping]] = ...,
         triplets: _Optional[_Union[Triplets, _Mapping]] = ...,
+        mis: _Optional[_Union[MaximalIndependentSet, _Mapping]] = ...,
     ) -> None: ...
 
 class StorageLevel(_message.Message):
-    __slots__ = (
-        "disk_only",
-        "disk_only_2",
-        "disk_only_3",
-        "memory_and_disk",
-        "memory_and_disk_2",
-        "memory_and_disk_deser",
-        "memory_only",
-        "memory_only_2",
-    )
+    __slots__ = ()
     DISK_ONLY_FIELD_NUMBER: _ClassVar[int]
     DISK_ONLY_2_FIELD_NUMBER: _ClassVar[int]
     DISK_ONLY_3_FIELD_NUMBER: _ClassVar[int]
@@ -141,7 +114,7 @@ class StorageLevel(_message.Message):
     ) -> None: ...
 
 class ColumnOrExpression(_message.Message):
-    __slots__ = ("col", "expr")
+    __slots__ = ()
     COL_FIELD_NUMBER: _ClassVar[int]
     EXPR_FIELD_NUMBER: _ClassVar[int]
     col: bytes
@@ -149,7 +122,7 @@ class ColumnOrExpression(_message.Message):
     def __init__(self, col: _Optional[bytes] = ..., expr: _Optional[str] = ...) -> None: ...
 
 class StringOrLongID(_message.Message):
-    __slots__ = ("long_id", "string_id")
+    __slots__ = ()
     LONG_ID_FIELD_NUMBER: _ClassVar[int]
     STRING_ID_FIELD_NUMBER: _ClassVar[int]
     long_id: int
@@ -157,7 +130,7 @@ class StringOrLongID(_message.Message):
     def __init__(self, long_id: _Optional[int] = ..., string_id: _Optional[str] = ...) -> None: ...
 
 class AggregateMessages(_message.Message):
-    __slots__ = ("agg_col", "send_to_src", "send_to_dst", "storage_level")
+    __slots__ = ()
     AGG_COL_FIELD_NUMBER: _ClassVar[int]
     SEND_TO_SRC_FIELD_NUMBER: _ClassVar[int]
     SEND_TO_DST_FIELD_NUMBER: _ClassVar[int]
@@ -175,7 +148,7 @@ class AggregateMessages(_message.Message):
     ) -> None: ...
 
 class BFS(_message.Message):
-    __slots__ = ("from_expr", "to_expr", "edge_filter", "max_path_length")
+    __slots__ = ()
     FROM_EXPR_FIELD_NUMBER: _ClassVar[int]
     TO_EXPR_FIELD_NUMBER: _ClassVar[int]
     EDGE_FILTER_FIELD_NUMBER: _ClassVar[int]
@@ -193,15 +166,7 @@ class BFS(_message.Message):
     ) -> None: ...
 
 class ConnectedComponents(_message.Message):
-    __slots__ = (
-        "algorithm",
-        "checkpoint_interval",
-        "broadcast_threshold",
-        "use_labels_as_components",
-        "use_local_checkpoints",
-        "max_iter",
-        "storage_level",
-    )
+    __slots__ = ()
     ALGORITHM_FIELD_NUMBER: _ClassVar[int]
     CHECKPOINT_INTERVAL_FIELD_NUMBER: _ClassVar[int]
     BROADCAST_THRESHOLD_FIELD_NUMBER: _ClassVar[int]
@@ -228,7 +193,7 @@ class ConnectedComponents(_message.Message):
     ) -> None: ...
 
 class DetectingCycles(_message.Message):
-    __slots__ = ("use_local_checkpoints", "checkpoint_interval", "storage_level")
+    __slots__ = ()
     USE_LOCAL_CHECKPOINTS_FIELD_NUMBER: _ClassVar[int]
     CHECKPOINT_INTERVAL_FIELD_NUMBER: _ClassVar[int]
     STORAGE_LEVEL_FIELD_NUMBER: _ClassVar[int]
@@ -247,7 +212,7 @@ class DropIsolatedVertices(_message.Message):
     def __init__(self) -> None: ...
 
 class FilterEdges(_message.Message):
-    __slots__ = ("condition",)
+    __slots__ = ()
     CONDITION_FIELD_NUMBER: _ClassVar[int]
     condition: ColumnOrExpression
     def __init__(
@@ -255,7 +220,7 @@ class FilterEdges(_message.Message):
     ) -> None: ...
 
 class FilterVertices(_message.Message):
-    __slots__ = ("condition",)
+    __slots__ = ()
     CONDITION_FIELD_NUMBER: _ClassVar[int]
     condition: ColumnOrExpression
     def __init__(
@@ -263,19 +228,13 @@ class FilterVertices(_message.Message):
     ) -> None: ...
 
 class Find(_message.Message):
-    __slots__ = ("pattern",)
+    __slots__ = ()
     PATTERN_FIELD_NUMBER: _ClassVar[int]
     pattern: str
     def __init__(self, pattern: _Optional[str] = ...) -> None: ...
 
 class LabelPropagation(_message.Message):
-    __slots__ = (
-        "algorithm",
-        "max_iter",
-        "use_local_checkpoints",
-        "checkpoint_interval",
-        "storage_level",
-    )
+    __slots__ = ()
     ALGORITHM_FIELD_NUMBER: _ClassVar[int]
     MAX_ITER_FIELD_NUMBER: _ClassVar[int]
     USE_LOCAL_CHECKPOINTS_FIELD_NUMBER: _ClassVar[int]
@@ -296,7 +255,7 @@ class LabelPropagation(_message.Message):
     ) -> None: ...
 
 class PageRank(_message.Message):
-    __slots__ = ("reset_probability", "source_id", "max_iter", "tol")
+    __slots__ = ()
     RESET_PROBABILITY_FIELD_NUMBER: _ClassVar[int]
     SOURCE_ID_FIELD_NUMBER: _ClassVar[int]
     MAX_ITER_FIELD_NUMBER: _ClassVar[int]
@@ -314,7 +273,7 @@ class PageRank(_message.Message):
     ) -> None: ...
 
 class ParallelPersonalizedPageRank(_message.Message):
-    __slots__ = ("reset_probability", "source_ids", "max_iter")
+    __slots__ = ()
     RESET_PROBABILITY_FIELD_NUMBER: _ClassVar[int]
     SOURCE_IDS_FIELD_NUMBER: _ClassVar[int]
     MAX_ITER_FIELD_NUMBER: _ClassVar[int]
@@ -329,7 +288,7 @@ class ParallelPersonalizedPageRank(_message.Message):
     ) -> None: ...
 
 class PowerIterationClustering(_message.Message):
-    __slots__ = ("k", "max_iter", "weight_col")
+    __slots__ = ()
     K_FIELD_NUMBER: _ClassVar[int]
     MAX_ITER_FIELD_NUMBER: _ClassVar[int]
     WEIGHT_COL_FIELD_NUMBER: _ClassVar[int]
@@ -344,23 +303,7 @@ class PowerIterationClustering(_message.Message):
     ) -> None: ...
 
 class Pregel(_message.Message):
-    __slots__ = (
-        "agg_msgs",
-        "send_msg_to_dst",
-        "send_msg_to_src",
-        "checkpoint_interval",
-        "max_iter",
-        "additional_col_name",
-        "additional_col_initial",
-        "additional_col_upd",
-        "early_stopping",
-        "use_local_checkpoints",
-        "storage_level",
-        "stop_if_all_non_active",
-        "initial_active_expr",
-        "update_active_expr",
-        "skip_messages_from_non_active",
-    )
+    __slots__ = ()
     AGG_MSGS_FIELD_NUMBER: _ClassVar[int]
     SEND_MSG_TO_DST_FIELD_NUMBER: _ClassVar[int]
     SEND_MSG_TO_SRC_FIELD_NUMBER: _ClassVar[int]
@@ -411,13 +354,7 @@ class Pregel(_message.Message):
     ) -> None: ...
 
 class ShortestPaths(_message.Message):
-    __slots__ = (
-        "landmarks",
-        "algorithm",
-        "use_local_checkpoints",
-        "checkpoint_interval",
-        "storage_level",
-    )
+    __slots__ = ()
     LANDMARKS_FIELD_NUMBER: _ClassVar[int]
     ALGORITHM_FIELD_NUMBER: _ClassVar[int]
     USE_LOCAL_CHECKPOINTS_FIELD_NUMBER: _ClassVar[int]
@@ -438,22 +375,13 @@ class ShortestPaths(_message.Message):
     ) -> None: ...
 
 class StronglyConnectedComponents(_message.Message):
-    __slots__ = ("max_iter",)
+    __slots__ = ()
     MAX_ITER_FIELD_NUMBER: _ClassVar[int]
     max_iter: int
     def __init__(self, max_iter: _Optional[int] = ...) -> None: ...
 
 class SVDPlusPlus(_message.Message):
-    __slots__ = (
-        "rank",
-        "max_iter",
-        "min_value",
-        "max_value",
-        "gamma1",
-        "gamma2",
-        "gamma6",
-        "gamma7",
-    )
+    __slots__ = ()
     RANK_FIELD_NUMBER: _ClassVar[int]
     MAX_ITER_FIELD_NUMBER: _ClassVar[int]
     MIN_VALUE_FIELD_NUMBER: _ClassVar[int]
@@ -483,7 +411,7 @@ class SVDPlusPlus(_message.Message):
     ) -> None: ...
 
 class TriangleCount(_message.Message):
-    __slots__ = ("storage_level",)
+    __slots__ = ()
     STORAGE_LEVEL_FIELD_NUMBER: _ClassVar[int]
     storage_level: StorageLevel
     def __init__(self, storage_level: _Optional[_Union[StorageLevel, _Mapping]] = ...) -> None: ...
@@ -491,3 +419,21 @@ class TriangleCount(_message.Message):
 class Triplets(_message.Message):
     __slots__ = ()
     def __init__(self) -> None: ...
+
+class MaximalIndependentSet(_message.Message):
+    __slots__ = ()
+    CHECKPOINT_INTERVAL_FIELD_NUMBER: _ClassVar[int]
+    STORAGE_LEVEL_FIELD_NUMBER: _ClassVar[int]
+    USE_LOCAL_CHECKPOINTS_FIELD_NUMBER: _ClassVar[int]
+    SEED_FIELD_NUMBER: _ClassVar[int]
+    checkpoint_interval: int
+    storage_level: StorageLevel
+    use_local_checkpoints: bool
+    seed: int
+    def __init__(
+        self,
+        checkpoint_interval: _Optional[int] = ...,
+        storage_level: _Optional[_Union[StorageLevel, _Mapping]] = ...,
+        use_local_checkpoints: _Optional[bool] = ...,
+        seed: _Optional[int] = ...,
+    ) -> None: ...
diff --git a/python/graphframes/graphframe.py b/python/graphframes/graphframe.py
index d2cae7b9e..18d65886c 100644
--- a/python/graphframes/graphframe.py
+++ b/python/graphframes/graphframe.py
@@ -456,6 +456,48 @@ def connectedComponents(
             storage_level=storage_level,
         )
 
+    def maximal_independent_set(
+        self,
+        seed: int = 42,
+        checkpoint_interval: int = 2,
+        use_local_checkpoints: bool = False,
+        storage_level: StorageLevel = StorageLevel.MEMORY_AND_DISK_DESER,
+    ) -> DataFrame:
+        """
+        This method implements a distributed algorithm for finding a Maximal Independent Set (MIS)
+        in a graph.
+
+        An MIS is a set of vertices such that no two vertices in the set are adjacent (i.e., there
+        is no edge between any two vertices in the set), and the set is maximal, meaning that adding
+        any other vertex to the set would violate the independence property. Note that this
+        implementation finds a maximal (but not necessarily maximum) independent set; that is, it
+        ensures no more vertices can be added to the set, but does not guarantee that the set has
+        the largest possible number of vertices among all possible independent sets in the graph.
+
+        The algorithm implemented here is based on the paper: Ghaffari, Mohsen. "An improved
+        distributed algorithm for maximal independent set." Proceedings of the twenty-seventh annual
+        ACM-SIAM symposium on Discrete algorithms. Society for Industrial and Applied Mathematics,
+        2016.
+
+        Note: This is a randomized, non-deterministic algorithm. The result may vary between runs
+        even if a fixed random seed is provided because of how Apache Spark works.
+
+        :param seed: random seed used for tie-breaking in the algorithm (default: 42)
+        :param checkpoint_interval: checkpoint interval in terms of number of iterations (default: 2)
+        :param use_local_checkpoints: whether to use local checkpoints (default: False);
+                                      local checkpoints are faster and do not require setting
+                                      a persistent checkpoint directory; however, they are less
+                                      reliable and require executors to have sufficient local disk space.
+        :param storage_level: storage level for both intermediate and final DataFrames
+                              (default: MEMORY_AND_DISK_DESER)
+
+        :return: DataFrame with new vertex column "selected", where "true" indicates the vertex
+                 is part of the Maximal Independent Set
+        """  # noqa: E501
+        return self._impl.maximal_independent_set(
+            checkpoint_interval, storage_level, use_local_checkpoints, seed
+        )
+
     def labelPropagation(
         self,
         maxIter: int,
diff --git a/python/tests/test_graphframes.py b/python/tests/test_graphframes.py
index f5aa0eace..73eadf856 100644
--- a/python/tests/test_graphframes.py
+++ b/python/tests/test_graphframes.py
@@ -487,6 +487,28 @@ def test_cycles_finding(spark: SparkSession, args: PregelArguments) -> None:
     _ = res.unpersist()
 
 
+@pytest.mark.parametrize("storage_level", STORAGE_LEVELS, ids=STORAGE_LEVELS_IDS)
+def test_mis(spark: SparkSession, storage_level: StorageLevel) -> None:
+    # Create a graph with isolated vertices
+    vertices = spark.createDataFrame(
+        [(0, "a"), (1, "b"), (2, "c"), (3, "d")], ["id", "name"]
+    )
+
+    # Only connect vertices 0 and 1
+    edges = spark.createDataFrame([(0, 1, "edge1")], ["src", "dst", "name"])
+
+    graph = GraphFrame(vertices, edges)
+    mis = graph.maximal_independent_set(storage_level=storage_level, seed=12345)
+
+    # Check that all vertices are in the MIS (since 2 and 3 are isolated)
+    mis_ids = set(row[0] for row in mis.select("id").collect())
+    assert len(mis_ids) == 3, "MIS should contain 2 isolated vertices and one of linked"
+    assert 2 in mis_ids, "Isolated vertex 2 should be in MIS"
+    assert 3 in mis_ids, "Isolated vertex 3 should be in MIS"
+
+    _ = mis.unpersist()
+
+
 @pytest.mark.skipif(is_remote(), reason="DISABLE FOR CONNECT")
 def test_svd_plus_plus(examples, spark: SparkSession):
     g = _from_java_gf(getattr(examples, "ALSSyntheticData")(), spark)

From 0bf76f27c35fb1c4ae81664da944c860ea7ab256 Mon Sep 17 00:00:00 2001
From: semyonsinchenko <ssinchenko@apache.org>
Date: Fri, 24 Oct 2025 14:30:06 +0200
Subject: [PATCH 2/2] fix connect

---
 python/graphframes/connect/graphframes_client.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/python/graphframes/connect/graphframes_client.py b/python/graphframes/connect/graphframes_client.py
index 2ea77cee8..0a7078f45 100644
--- a/python/graphframes/connect/graphframes_client.py
+++ b/python/graphframes/connect/graphframes_client.py
@@ -1087,7 +1087,7 @@ def __init__(
                 self.v = v
                 self.e = e
                 self.checkpoint_interval = checkpoint_interval
-                self.storage_level = (storage_level,)
+                self.storage_level = storage_level
                 self.use_local_checkpoints = use_local_checkpoints
                 self.seed = seed