Add an implementation for mutable bloom filters

algebird-benchmark/src/main/scala/com/twitter/algebird/benchmark/MutableBloomFilterCreateBenchmark.scala

@@ -0,0 +1,54 @@
+package com.twitter.algebird.benchmark
+
+import com.twitter.algebird.mutable.{BloomFilter, BloomFilterAggregator, MutableBF}
+import com.twitter.algebird.benchmark.BloomFilterCreateBenchmark.createRandomString
+import org.openjdk.jmh.annotations._
+
+object MutableBloomFilterCreateBenchmark {
+
+  @State(Scope.Benchmark)
+  class BloomFilterState {
+    @Param(Array("100", "1000", "10000"))
+    var nbrOfElements: Int = 0
+
+    @Param(Array("0.001", "0.01"))
+    var falsePositiveRate: Double = 0
+
+    var randomStrings: Seq[String] = _
+
+    @Setup(Level.Trial)
+    def setup(): Unit =
+      randomStrings = createRandomString(nbrOfElements, 10)
+
+  }
+}
+class MutableBloomFilterBenchmark {
+
+  import MutableBloomFilterCreateBenchmark._
+
+  @Benchmark
+  def createMutableBloomFilter(bloomFilterState: BloomFilterState): MutableBF[String] = {
+    val bfMonoid = BloomFilter[String](bloomFilterState.nbrOfElements, bloomFilterState.falsePositiveRate)
+    val bf = bfMonoid.create(bloomFilterState.randomStrings: _*)
+    bf
+  }
+
+  @Benchmark
+  def createMutableBloomFilterUsingFold(bloomFilterState: BloomFilterState): MutableBF[String] = {
+    val bfMonoid = BloomFilter[String](bloomFilterState.nbrOfElements, bloomFilterState.falsePositiveRate)
+    val bf = bloomFilterState.randomStrings.foldLeft(bfMonoid.zero) {
+      case (filter, string) => filter += string
+    }
+    bf
+  }
+
+  @Benchmark
+  def createMutableBloomFilterAggregator(bloomFilterState: BloomFilterState): MutableBF[String] = {
+    val bfMonoid = BloomFilter[String](bloomFilterState.nbrOfElements, bloomFilterState.falsePositiveRate)
+    val bfAggregator = BloomFilterAggregator(bfMonoid)
+
+    val bf = bloomFilterState.randomStrings.aggregate(bfAggregator.monoid.zero)(_ += _, _ ++= _)
+    bf
+  }
+
+}

algebird-benchmark/src/main/scala/com/twitter/algebird/benchmark/MutableBloomFilterQueryBenchmark.scala

@@ -0,0 +1,36 @@
+package com.twitter.algebird
+package benchmark
+
+import org.openjdk.jmh.annotations._
+
+object MutableBloomFilterQueryBenchmark {
+
+  @State(Scope.Benchmark)
+  class BloomFilterState {
+
+    @Param(Array("100", "1000", "10000"))
+    var nbrOfElements: Int = 0
+
+    @Param(Array("0.001", "0.01"))
+    var falsePositiveRate: Double = 0
+
+    var bf: mutable.MutableBF[String] = _
+
+    @Setup(Level.Trial)
+    def setup(): Unit = {
+      val randomStrings =
+        BloomFilterCreateBenchmark.createRandomString(nbrOfElements, 10)
+      bf = mutable
+        .BloomFilter[String](nbrOfElements, falsePositiveRate)
+        .create(randomStrings: _*)
+    }
+  }
+}
+
+class MutableBloomFilterQueryBenchmark {
+  import MutableBloomFilterQueryBenchmark._
+
+  @Benchmark
+  def queryBloomFilter(bloomFilterState: BloomFilterState): ApproximateBoolean =
+    bloomFilterState.bf.contains("1")
+}