diff --git a/mllib/src/main/scala/org/apache/spark/mllib/fpm/LocalPrefixSpan.scala b/mllib/src/main/scala/org/apache/spark/mllib/fpm/LocalPrefixSpan.scala
index 0ea792081086d..45c19f521eadc 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/fpm/LocalPrefixSpan.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/fpm/LocalPrefixSpan.scala
@@ -41,54 +41,166 @@ private[fpm] object LocalPrefixSpan extends Logging with Serializable {
       maxPatternLength: Int,
       prefixes: List[Int],
       database: Iterable[Array[Int]]): Iterator[(List[Int], Long)] = {
-    if (prefixes.length == maxPatternLength || database.isEmpty) return Iterator.empty
-    val frequentItemAndCounts = getFreqItemAndCounts(minCount, database)
-    val filteredDatabase = database.map(x => x.filter(frequentItemAndCounts.contains))
-    frequentItemAndCounts.iterator.flatMap { case (item, count) =>
-      val newPrefixes = item :: prefixes
-      val newProjected = project(filteredDatabase, item)
-      Iterator.single((newPrefixes, count)) ++
-        run(minCount, maxPatternLength, newPrefixes, newProjected)
+    if (prefixes.count(_ != -1) == maxPatternLength || database.isEmpty) return Iterator.empty
+    val frequentPrefixAndCounts = getFreqPrefixAndCounts(minCount, prefixes, database)
+    frequentPrefixAndCounts.iterator.flatMap { case (prefix, count) =>
+      val newProjected = project(database, prefix)
+      Iterator.single((prefix, count)) ++
+        run(minCount, maxPatternLength, prefix, newProjected)
     }
   }
 
   /**
-   * Calculate suffix sequence immediately after the first occurrence of an item.
-   * @param item item to get suffix after
+   * Calculate suffix sequence immediately after the first occurrence of a prefix.
+   * @param prefix prefix to get suffix after
    * @param sequence sequence to extract suffix from
    * @return suffix sequence
    */
-  def getSuffix(item: Int, sequence: Array[Int]): Array[Int] = {
-    val index = sequence.indexOf(item)
+  def getSuffix(prefix: List[Int], sequence: Array[Int]): (Boolean, Array[Int]) = {
+    val element = getLastElement(prefix)
+    if (sequence.apply(0) != -3) {
+      if (element.length == 1) {
+        getSingleItemElementSuffix(element, sequence)
+      } else {
+        getMultiItemsElementSuffix(element, sequence)
+      }
+    } else {
+      if (element.length == 1) {
+        val firstElemPos = sequence.indexOf(-1)
+        if (firstElemPos == -1) {
+          (false, Array())
+        } else {
+          getSingleItemElementSuffix(element, sequence.drop(firstElemPos + 1))
+        }
+      } else {
+        val newSequence = element.take(element.length - 1) ++ sequence.drop(1)
+        getMultiItemsElementSuffix(element, newSequence)
+      }
+    }
+  }
+
+  private def getLastElement(prefix: List[Int]): Array[Int] = {
+    val pos = prefix.indexOf(-1)
+    if (pos == -1) {
+      prefix.reverse.toArray
+    } else {
+      prefix.take(pos).reverse.toArray
+    }
+  }
+
+  private def getSingleItemElementSuffix(
+      element: Array[Int],
+      sequence: Array[Int]): (Boolean, Array[Int]) = {
+    val index = sequence.indexOf(element.apply(0))
     if (index == -1) {
-      Array()
+      (false, Array())
+    } else if (index == sequence.length - 1) {
+      (true, Array())
+    } else if (sequence.apply(index + 1) == -1) {
+      (true, sequence.drop(index + 2))
+    } else {
+      (true, -3 +: sequence.drop(index + 1))
+    }
+  }
+
+  private def getMultiItemsElementSuffix(
+      element: Array[Int],
+      sequence: Array[Int]): (Boolean, Array[Int]) = {
+    var seqPos = 0
+    var found = false
+    while (seqPos < sequence.length && !found) {
+      var elemPos = 0
+      while (!found && elemPos < element.length &&
+        seqPos < sequence.length && sequence.apply(seqPos) != -1 ) {
+        if (element.apply(elemPos) == sequence.apply(seqPos)) {
+          elemPos += 1
+          seqPos += 1
+        } else {
+          seqPos += 1
+        }
+        found = elemPos == element.length
+      }
+      if (!found) seqPos += 1
+    }
+    if (found) {
+      if (sequence.apply(seqPos) == -1) {
+        (true, sequence.drop(seqPos + 1))
+      } else {
+        (true, -3 +: sequence.drop(seqPos))
+      }
     } else {
-      sequence.drop(index + 1)
+      (false, Array())
     }
   }
 
-  def project(database: Iterable[Array[Int]], prefix: Int): Iterable[Array[Int]] = {
+  def project(database: Iterable[Array[Int]], prefix: List[Int]): Iterable[Array[Int]] = {
     database
-      .map(getSuffix(prefix, _))
+      .map(getSuffix(prefix, _)._2)
       .filter(_.nonEmpty)
   }
 
   /**
-   * Generates frequent items by filtering the input data using minimal count level.
+   * Generates frequent prefix by filtering the input data using minimal count level.
    * @param minCount the minimum count for an item to be frequent
+   * @param prefix the minimum count for an item to be frequent
    * @param database database of sequences
    * @return freq item to count map
    */
-  private def getFreqItemAndCounts(
+  private def getFreqPrefixAndCounts(
       minCount: Long,
-      database: Iterable[Array[Int]]): mutable.Map[Int, Long] = {
+      prefix: List[Int],
+      database: Iterable[Array[Int]]): mutable.Map[List[Int], Long] = {
     // TODO: use PrimitiveKeyOpenHashMap
-    val counts = mutable.Map[Int, Long]().withDefaultValue(0L)
+
+    // get frequent items
+    val freqItems = database
+      .flatMap(_.distinct.filter(x => x != -1 && x != -3))
+      .groupBy(x => x)
+      .mapValues(_.size)
+      .filter(_._2 >= minCount)
+      .map(_._1)
+    if (freqItems.isEmpty) return mutable.Map[List[Int], Long]()
+
+    // get prefixes and counts
+    val singleItemCounts = mutable.Map[Int, Long]().withDefaultValue(0L)
+    val multiItemsCounts = mutable.Map[Int, Long]().withDefaultValue(0L)
+    val prefixLastElement = getLastElement(prefix)
     database.foreach { sequence =>
-      sequence.distinct.foreach { item =>
-        counts(item) += 1L
+      if (sequence.apply(0) != -3) {
+        freqItems.foreach { item =>
+          if (getSingleItemElementSuffix(Array(item), sequence)._1) {
+            singleItemCounts(item) += 1
+          }
+          if (prefixLastElement.nonEmpty &&
+            getMultiItemsElementSuffix(prefixLastElement :+ item, sequence)._1) {
+            multiItemsCounts(item) += 1
+          }
+        }
+      } else {
+        val firstElemPos = sequence.indexOf(-1)
+        if (firstElemPos != -1) {
+          val newSequence = sequence.drop(firstElemPos + 1)
+          freqItems.foreach { item =>
+            if (getSingleItemElementSuffix(Array(item), newSequence)._1) {
+              singleItemCounts(item) += 1
+            }
+          }
+        }
+        val newSequence = prefixLastElement ++ sequence.drop(1)
+        freqItems.foreach { item =>
+          if (prefixLastElement.nonEmpty &&
+            getMultiItemsElementSuffix(prefixLastElement :+ item, newSequence)._1) {
+            multiItemsCounts(item) += 1
+          }
+        }
       }
     }
-    counts.filter(_._2 >= minCount)
+
+    if (prefix.nonEmpty) {
+      singleItemCounts.filter(_._2 >= minCount).map(x => (x._1 :: (-1 :: prefix), x._2)) ++
+        multiItemsCounts.filter(_._2 >= minCount).map(x => (x._1 :: prefix, x._2))
+    } else {
+      singleItemCounts.filter(_._2 >= minCount).map(x => (List(x._1), x._2))
+    }
   }
 }
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/fpm/PrefixSpan.scala b/mllib/src/main/scala/org/apache/spark/mllib/fpm/PrefixSpan.scala
index e6752332cdeeb..3c48c6a0e5be9 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/fpm/PrefixSpan.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/fpm/PrefixSpan.scala
@@ -17,8 +17,6 @@
 
 package org.apache.spark.mllib.fpm
 
-import scala.collection.mutable.ArrayBuffer
-
 import org.apache.spark.Logging
 import org.apache.spark.annotation.Experimental
 import org.apache.spark.rdd.RDD
@@ -50,7 +48,7 @@ class PrefixSpan private (
    * projected database exceeds this size, another iteration of distributed PrefixSpan is run.
    */
   // TODO: make configurable with a better default value, 10000 may be too small
-  private val maxLocalProjDBSize: Long = 10000
+  private val maxLocalProjDBSize: Long = 32000000L
 
   /**
    * Constructs a default instance with default parameters
@@ -108,20 +106,20 @@ class PrefixSpan private (
 
     // (Frequent items -> number of occurrences, all items here satisfy the `minSupport` threshold
     val freqItemCounts = sequences
-      .flatMap(seq => seq.distinct.map(item => (item, 1L)))
+      .flatMap(seq => seq.distinct.filter(_ != -1).map(item => (item, 1L)))
       .reduceByKey(_ + _)
       .filter(_._2 >= minCount)
       .collect()
 
     // Pairs of (length 1 prefix, suffix consisting of frequent items)
-    val itemSuffixPairs = {
+    val prefixSuffixPairs = {
       val freqItems = freqItemCounts.map(_._1).toSet
       sequences.flatMap { seq =>
-        val filteredSeq = seq.filter(freqItems.contains(_))
+        val filteredSeq = seq.filter(item => freqItems.contains(item) || item == -1)
         freqItems.flatMap { item =>
-          val candidateSuffix = LocalPrefixSpan.getSuffix(item, filteredSeq)
+          val candidateSuffix = LocalPrefixSpan.getSuffix(List(item), filteredSeq)._2
           candidateSuffix match {
-            case suffix if !suffix.isEmpty => Some((List(item), suffix))
+            case suffix if suffix.nonEmpty => Some((List(item), suffix))
             case _ => None
           }
         }
@@ -133,11 +131,13 @@ class PrefixSpan private (
     var resultsAccumulator = freqItemCounts.map(x => (List(x._1), x._2))
 
     // Remaining work to be locally and distributively processed respectfully
-    var (pairsForLocal, pairsForDistributed) = partitionByProjDBSize(itemSuffixPairs)
+    var (pairsForLocal, pairsForDistributed) = partitionByProjDBSize(prefixSuffixPairs)
 
     // Continue processing until no pairs for distributed processing remain (i.e. all prefixes have
     // projected database sizes <= `maxLocalProjDBSize`)
-    while (pairsForDistributed.count() != 0) {
+    var patternLength = 1
+    while (pairsForDistributed.count() != 0 && patternLength < maxPatternLength) {
+      patternLength += 1
       val (nextPatternAndCounts, nextPrefixSuffixPairs) =
         extendPrefixes(minCount, pairsForDistributed)
       pairsForDistributed.unpersist()
@@ -153,7 +153,7 @@ class PrefixSpan private (
       minCount, sc.parallelize(pairsForLocal, 1).groupByKey())
 
     (sc.parallelize(resultsAccumulator, 1) ++ remainingResults)
-      .map { case (pattern, count) => (pattern.toArray, count) }
+      .map { case (pattern, count) => (pattern.reverse.toArray, count) }
   }
 
 
@@ -195,36 +195,41 @@ class PrefixSpan private (
     // (length N prefix, item from suffix) pairs and their corresponding number of occurrences
     // Every (prefix :+ suffix) is guaranteed to have support exceeding `minSupport`
     val prefixItemPairAndCounts = prefixSuffixPairs
-      .flatMap { case (prefix, suffix) => suffix.distinct.map(y => ((prefix, y), 1L)) }
+      .flatMap { case (prefix, suffix) =>
+      suffix.distinct.filter(item => item != -1 && item != -3).map(y => ((prefix, y), 1L)) }
       .reduceByKey(_ + _)
       .filter(_._2 >= minCount)
 
-    // Map from prefix to set of possible next items from suffix
-    val prefixToNextItems = prefixItemPairAndCounts
+   // Map from prefix to set of possible next prefix from suffix
+    val prefixToNextPrefixes = prefixItemPairAndCounts
       .keys
       .groupByKey()
-      .mapValues(_.toSet)
+      .map { case (prefix, items) =>
+      (prefix, items.flatMap(item => Array(item :: (-1 :: prefix), item :: prefix)).toSet) }
       .collect()
       .toMap
 
-
-    // Frequent patterns with length N+1 and their corresponding counts
-    val extendedPrefixAndCounts = prefixItemPairAndCounts
-      .map { case ((prefix, item), count) => (item :: prefix, count) }
-
     // Remaining work, all prefixes will have length N+1
-    val extendedPrefixAndSuffix = prefixSuffixPairs
-      .filter(x => prefixToNextItems.contains(x._1))
+    val extendedPrefixAndSuffixWithFlags = prefixSuffixPairs
       .flatMap { case (prefix, suffix) =>
-        val frequentNextItems = prefixToNextItems(prefix)
-        val filteredSuffix = suffix.filter(frequentNextItems.contains(_))
-        frequentNextItems.flatMap { item =>
-          LocalPrefixSpan.getSuffix(item, filteredSuffix) match {
-            case suffix if !suffix.isEmpty => Some(item :: prefix, suffix)
-            case _ => None
+        if (prefixToNextPrefixes.contains(prefix)) {
+          val frequentNextPrefixes = prefixToNextPrefixes(prefix)
+          frequentNextPrefixes.map { nextPrefix =>
+            val suffixWithFlag = LocalPrefixSpan.getSuffix(nextPrefix, suffix)
+            (nextPrefix, if (suffixWithFlag._1) 1L else 0L, suffixWithFlag._2)
           }
+        } else {
+          None
         }
-      }
+      }.persist(StorageLevel.MEMORY_AND_DISK)
+    val extendedPrefixAndCounts = extendedPrefixAndSuffixWithFlags
+      .map(x => (x._1, x._2))
+      .reduceByKey(_ + _)
+      .filter(_._2 >= minCount)
+    val extendedPrefixAndSuffix = extendedPrefixAndSuffixWithFlags
+      .map(x => (x._1, x._3))
+      .filter(_._2.nonEmpty)
+    extendedPrefixAndSuffixWithFlags.unpersist()
 
     (extendedPrefixAndCounts, extendedPrefixAndSuffix)
   }
@@ -240,9 +245,9 @@ class PrefixSpan private (
       data: RDD[(List[Int], Iterable[Array[Int]])]): RDD[(List[Int], Long)] = {
     data.flatMap {
       case (prefix, projDB) =>
-        LocalPrefixSpan.run(minCount, maxPatternLength, prefix.toList.reverse, projDB)
+        LocalPrefixSpan.run(minCount, maxPatternLength, prefix, projDB)
           .map { case (pattern: List[Int], count: Long) =>
-          (pattern.reverse, count)
+          (pattern, count)
         }
     }
   }
diff --git a/mllib/src/test/scala/org/apache/spark/mllib/fpm/PrefixSpanSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/fpm/PrefixSpanSuite.scala
index 6dd2dc926acc5..2b7d779bd5ddb 100644
--- a/mllib/src/test/scala/org/apache/spark/mllib/fpm/PrefixSpanSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/mllib/fpm/PrefixSpanSuite.scala
@@ -21,7 +21,7 @@ import org.apache.spark.mllib.util.MLlibTestSparkContext
 
 class PrefixSpanSuite extends SparkFunSuite with MLlibTestSparkContext {
 
-  test("PrefixSpan using Integer type") {
+  test("PrefixSpan using Integer type (An element contains only one item)") {
 
     /*
       library("arulesSequences")
@@ -35,12 +35,12 @@ class PrefixSpanSuite extends SparkFunSuite with MLlibTestSparkContext {
     */
 
     val sequences = Array(
-      Array(1, 3, 4, 5),
-      Array(2, 3, 1),
-      Array(2, 4, 1),
-      Array(3, 1, 3, 4, 5),
-      Array(3, 4, 4, 3),
-      Array(6, 5, 3))
+      Array(1, -1, 3, -1, 4, -1, 5),
+      Array(2, -1, 3, -1, 1),
+      Array(2, -1, 4, -1, 1),
+      Array(3, -1, 1, -1, 3, -1, 4, -1, 5),
+      Array(3, -1, 4, -1, 4, -1, 3),
+      Array(6, -1, 5, -1, 3))
 
     val rdd = sc.parallelize(sequences, 2).cache()
 
@@ -50,23 +50,23 @@ class PrefixSpanSuite extends SparkFunSuite with MLlibTestSparkContext {
     val result1 = prefixspan.run(rdd)
     val expectedValue1 = Array(
       (Array(1), 4L),
-      (Array(1, 3), 2L),
-      (Array(1, 3, 4), 2L),
-      (Array(1, 3, 4, 5), 2L),
-      (Array(1, 3, 5), 2L),
-      (Array(1, 4), 2L),
-      (Array(1, 4, 5), 2L),
-      (Array(1, 5), 2L),
+      (Array(1, -1, 3), 2L),
+      (Array(1, -1, 3, -1, 4), 2L),
+      (Array(1, -1, 3, -1, 4, -1, 5), 2L),
+      (Array(1, -1, 3, -1, 5), 2L),
+      (Array(1, -1, 4), 2L),
+      (Array(1, -1, 4, -1, 5), 2L),
+      (Array(1, -1, 5), 2L),
       (Array(2), 2L),
-      (Array(2, 1), 2L),
+      (Array(2, -1, 1), 2L),
       (Array(3), 5L),
-      (Array(3, 1), 2L),
-      (Array(3, 3), 2L),
-      (Array(3, 4), 3L),
-      (Array(3, 4, 5), 2L),
-      (Array(3, 5), 2L),
+      (Array(3, -1, 1), 2L),
+      (Array(3, -1, 3), 2L),
+      (Array(3, -1, 4), 3L),
+      (Array(3, -1, 4, -1, 5), 2L),
+      (Array(3, -1, 5), 2L),
       (Array(4), 4L),
-      (Array(4, 5), 2L),
+      (Array(4, -1, 5), 2L),
       (Array(5), 3L)
     )
     assert(compareResults(expectedValue1, result1.collect()))
@@ -76,7 +76,7 @@ class PrefixSpanSuite extends SparkFunSuite with MLlibTestSparkContext {
     val expectedValue2 = Array(
       (Array(1), 4L),
       (Array(3), 5L),
-      (Array(3, 4), 3L),
+      (Array(3, -1, 4), 3L),
       (Array(4), 4L),
       (Array(5), 3L)
     )
@@ -86,23 +86,89 @@ class PrefixSpanSuite extends SparkFunSuite with MLlibTestSparkContext {
     val result3 = prefixspan.run(rdd)
     val expectedValue3 = Array(
       (Array(1), 4L),
-      (Array(1, 3), 2L),
-      (Array(1, 4), 2L),
-      (Array(1, 5), 2L),
-      (Array(2, 1), 2L),
+      (Array(1, -1, 3), 2L),
+      (Array(1, -1, 4), 2L),
+      (Array(1, -1, 5), 2L),
+      (Array(2, -1, 1), 2L),
       (Array(2), 2L),
       (Array(3), 5L),
-      (Array(3, 1), 2L),
-      (Array(3, 3), 2L),
-      (Array(3, 4), 3L),
-      (Array(3, 5), 2L),
+      (Array(3, -1, 1), 2L),
+      (Array(3, -1, 3), 2L),
+      (Array(3, -1, 4), 3L),
+      (Array(3, -1, 5), 2L),
       (Array(4), 4L),
-      (Array(4, 5), 2L),
+      (Array(4, -1, 5), 2L),
       (Array(5), 3L)
     )
     assert(compareResults(expectedValue3, result3.collect()))
   }
 
+  test("PrefixSpan using Integer type (An element contains multiple items)") {
+    val sequences = Array(
+      Array(1, -1, 1, 2, 3, -1, 1, 3, -1, 4, -1, 3, 6),
+      Array(1, 4, -1, 3, -1, 2, 3, -1, 1, 5),
+      Array(5, 6, -1, 1, 2, -1, 4, 6, -1, 3, -1, 2),
+      Array(5, -1, 7, -1, 1, 6, -1, 3, -1, 2, -1, 3))
+    val rdd = sc.parallelize(sequences, 2).cache()
+    val prefixspan = new PrefixSpan().setMinSupport(0.5).setMaxPatternLength(5)
+    val result = prefixspan.run(rdd)
+    val expectedValue = Array(
+      (Array(1), 4L),
+      (Array(1, -1, 6), 2L),
+      (Array(1, -1, 1), 2L),
+      (Array(1, -1, 3), 4L),
+      (Array(1, -1, 3, -1, 1), 2L),
+      (Array(1, -1, 3, -1, 3), 3L),
+      (Array(1, -1, 3, -1, 2), 3L),
+      (Array(1, -1, 2), 4L),
+      (Array(1, -1, 2, -1, 1), 2L),
+      (Array(1, -1, 2, -1, 3), 2L),
+      (Array(1, -1, 2, 3), 2L),
+      (Array(1, -1, 2, 3, -1, 1), 2L),
+      (Array(1, 2), 2L),
+      (Array(1, 2, -1, 6), 2L),
+      (Array(1, 2, -1, 3), 2L),
+      (Array(1, 2, -1, 4), 2L),
+      (Array(1, 2, -1, 4, -1, 3), 2L),
+      (Array(1, -1, 4), 2L),
+      (Array(1, -1, 4, -1, 3), 2L),
+      (Array(2), 4L),
+      (Array(2, -1, 6), 2L),
+      (Array(2, -1, 1), 2L),
+      (Array(2, -1, 3), 3L),
+      (Array(2, 3), 2L),
+      (Array(2, 3, -1, 1), 2L),
+      (Array(2, -1, 4), 2L),
+      (Array(2, -1, 4, -1, 3), 2L),
+      (Array(3), 4L),
+      (Array(3, -1, 1), 2L),
+      (Array(3, -1, 3), 3L),
+      (Array(3, -1, 2), 3L),
+      (Array(4), 3L),
+      (Array(4, -1, 3), 3L),
+      (Array(4, -1, 3, -1, 2), 2L),
+      (Array(4, -1, 2), 2L),
+      (Array(5), 3L),
+      (Array(5, -1, 6), 2L),
+      (Array(5, -1, 6, -1, 3), 2L),
+      (Array(5, -1, 6, -1, 3, -1, 2), 2L),
+      (Array(5, -1, 6, -1, 2), 2L),
+      (Array(5, -1, 1), 2L),
+      (Array(5, -1, 1, -1, 3), 2L),
+      (Array(5, -1, 1, -1, 3, -1, 2), 2L),
+      (Array(5, -1, 1, -1, 2), 2L),
+      (Array(5, -1, 3), 2L),
+      (Array(5, -1, 3, -1, 2), 2L),
+      (Array(5, -1, 2), 2L),
+      (Array(5, -1, 2, -1, 3), 2L),
+      (Array(6), 3L),
+      (Array(6, -1, 3), 2L),
+      (Array(6, -1, 3, -1, 2), 2L),
+      (Array(6, -1, 2), 2L),
+      (Array(6, -1, 2, -1, 3), 2L))
+    assert(compareResults(expectedValue, result.collect()))
+  }
+
   private def compareResults(
     expectedValue: Array[(Array[Int], Long)],
     actualValue: Array[(Array[Int], Long)]): Boolean = {