Add cardinality support to BloomFilter.

src/main/java/com/clearspring/analytics/stream/membership/BloomFilter.java

@@ -83,6 +83,12 @@ public boolean isPresent(byte[] key) {
  return true;
  }
 
+ public long cardinality() {
+ int m = buckets();
+ double fractionOfBits = ((double) filter_.cardinality()) / m;
+ return Math.round(-m * Math.log1p(-fractionOfBits) / hashCount);
+ }
+
  /*
  @param key -- value whose hash is used to fill
  the filter_.

src/test/java/com/clearspring/analytics/stream/membership/BloomFilterTest.java

@@ -15,7 +15,7 @@
 * KIND, either express or implied. See the License for the
 * specific language governing permissions and limitations
 * under the License.
-* 
+*
 */
 package com.clearspring.analytics.stream.membership;
 
@@ -111,6 +111,27 @@ public void testSerialize() throws IOException {
  FilterTest.testSerialize(bf);
  }
 
+ @Test
+ public void testCardinalityOne() {
+ bf.add("a");
+ assertEquals(1, bf.cardinality());
+ }
+
+ @Test
+ public void testCardinalityTwo() {
+ bf.add("a");
+ bf.add("b");
+ assertEquals(2, bf.cardinality());
+ }
+
+ @Test
+ public void testCardinalityHundred() {
+ for (int i = 0; i < 100; ++i) {
+ bf.add(Integer.toString(i));
+ }
+ assertEquals(100, bf.cardinality());
+ }
+
  @Test
  public void testGetFalsePositiveProbability() {
  // These probabilities are taken from the bloom filter probability table at
@@ -204,7 +225,7 @@ public void testHashCount() {
 
  instance = new BloomFilter(1, 7);
  assertEquals(5, instance.getHashCount());
- 
+
  /*
  * Although technically 8*ln(2) = 5.545...
  * we round down here for speed