[ML] Remove record_count from bucket results (elastic/x-pack-elasticsearch#1568)

relates elastic/x-pack-elasticsearch#1564

Original commit: elastic/x-pack-elasticsearch@0caff1a735

docs/en/rest-api/ml/get-bucket.asciidoc

@@ -106,7 +106,6 @@ score and time constraints:
       "anomaly_score": 94.1706,
       "bucket_span": 300,
       "initial_anomaly_score": 94.1706,
-      "record_count": 1,
       "event_count": 153,
       "is_interim": false,
       "bucket_influencers": [

docs/en/rest-api/ml/resultsresource.asciidoc

@@ -96,9 +96,6 @@ A bucket resource has the following properties:
   (number) The amount of time, in milliseconds, that it took to analyze the
   bucket contents and calculate results.
 
-`record_count`::
-  (number) The number of anomaly records in this bucket.
-
 `result_type`::
   (string) Internal. This value is always set to `bucket`.
 

plugin/src/main/java/org/elasticsearch/xpack/ml/job/persistence/JobProvider.java

@@ -179,11 +179,7 @@ public class JobProvider {
                 throw new RuntimeException(e);
             }
         }
-        if (numFields + additionalFieldCount > fieldCountLimit) {
+        return numFields + additionalFieldCount > fieldCountLimit;
-            return true;
-        } else {
-            return false;
-        }
     }
 
     @SuppressWarnings("unchecked")
@@ -421,7 +417,7 @@ public class JobProvider {
 
             if (query.isExpand()) {
                 Iterator<Bucket> bucketsToExpand = buckets.results().stream()
-                        .filter(bucket -> bucket.getRecordCount() > 0).iterator();
+                        .filter(bucket -> bucket.getBucketInfluencers().size() > 0).iterator();
                 expandBuckets(jobId, query, buckets, bucketsToExpand, handler, errorHandler, client);
             } else {
                 handler.accept(buckets);

plugin/src/main/java/org/elasticsearch/xpack/ml/job/results/Bucket.java

@@ -24,7 +24,6 @@ import java.util.ArrayList;
 import java.util.Collections;
 import java.util.Date;
 import java.util.List;
-import java.util.Map;
 import java.util.Objects;
 import java.util.Optional;
 
@@ -74,13 +73,14 @@ public class Bucket extends ToXContentToBytes implements Writeable {
         PARSER.declareDouble(Bucket::setAnomalyScore, ANOMALY_SCORE);
         PARSER.declareDouble(Bucket::setInitialAnomalyScore, INITIAL_ANOMALY_SCORE);
         PARSER.declareBoolean(Bucket::setInterim, Result.IS_INTERIM);
-        PARSER.declareInt(Bucket::setRecordCount, RECORD_COUNT);
         PARSER.declareLong(Bucket::setEventCount, EVENT_COUNT);
         PARSER.declareObjectArray(Bucket::setRecords, AnomalyRecord.PARSER, RECORDS);
         PARSER.declareObjectArray(Bucket::setBucketInfluencers, BucketInfluencer.PARSER, BUCKET_INFLUENCERS);
         PARSER.declareLong(Bucket::setProcessingTimeMs, PROCESSING_TIME_MS);
         PARSER.declareObjectArray(Bucket::setPartitionScores, PartitionScore.PARSER, PARTITION_SCORES);
         PARSER.declareString((bucket, s) -> {}, Result.RESULT_TYPE);
+        // For bwc with 5.4
+        PARSER.declareInt((bucket, recordCount) -> {}, RECORD_COUNT);
     }
 
     private final String jobId;
@@ -88,7 +88,6 @@ public class Bucket extends ToXContentToBytes implements Writeable {
     private final long bucketSpan;
     private double anomalyScore;
     private double initialAnomalyScore;
-    private int recordCount;
     private List<AnomalyRecord> records = new ArrayList<>();
     private long eventCount;
     private boolean isInterim;
@@ -108,7 +107,6 @@ public class Bucket extends ToXContentToBytes implements Writeable {
         this.bucketSpan = other.bucketSpan;
         this.anomalyScore = other.anomalyScore;
         this.initialAnomalyScore = other.initialAnomalyScore;
-        this.recordCount = other.recordCount;
         this.records = new ArrayList<>(other.records);
         this.eventCount = other.eventCount;
         this.isInterim = other.isInterim;
@@ -123,7 +121,10 @@ public class Bucket extends ToXContentToBytes implements Writeable {
         anomalyScore = in.readDouble();
         bucketSpan = in.readLong();
         initialAnomalyScore = in.readDouble();
-        recordCount = in.readInt();
+        // bwc for recordCount
+        if (in.getVersion().before(Version.V_5_5_0_UNRELEASED)) {
+            in.readInt();
+        }
         records = in.readList(AnomalyRecord::new);
         eventCount = in.readLong();
         isInterim = in.readBoolean();
@@ -143,7 +144,10 @@ public class Bucket extends ToXContentToBytes implements Writeable {
         out.writeDouble(anomalyScore);
         out.writeLong(bucketSpan);
         out.writeDouble(initialAnomalyScore);
-        out.writeInt(recordCount);
+        // bwc for recordCount
+        if (out.getVersion().before(Version.V_5_5_0_UNRELEASED)) {
+            out.writeInt(0);
+        }
         out.writeList(records);
         out.writeLong(eventCount);
         out.writeBoolean(isInterim);
@@ -164,7 +168,6 @@ public class Bucket extends ToXContentToBytes implements Writeable {
         builder.field(ANOMALY_SCORE.getPreferredName(), anomalyScore);
         builder.field(BUCKET_SPAN.getPreferredName(), bucketSpan);
         builder.field(INITIAL_ANOMALY_SCORE.getPreferredName(), initialAnomalyScore);
-        builder.field(RECORD_COUNT.getPreferredName(), recordCount);
         if (records.isEmpty() == false) {
             builder.field(RECORDS.getPreferredName(), records);
         }
@@ -223,14 +226,6 @@ public class Bucket extends ToXContentToBytes implements Writeable {
         this.initialAnomalyScore = initialAnomalyScore;
     }
 
-    public int getRecordCount() {
-        return recordCount;
-    }
-
-    public void setRecordCount(int recordCount) {
-        this.recordCount = recordCount;
-    }
-
     /**
      * Get all the anomaly records associated with this bucket.
      * The records are not part of the bucket document. They will
@@ -310,7 +305,7 @@ public class Bucket extends ToXContentToBytes implements Writeable {
 
     @Override
     public int hashCode() {
-        return Objects.hash(jobId, timestamp, eventCount, initialAnomalyScore, anomalyScore, recordCount, records,
+        return Objects.hash(jobId, timestamp, eventCount, initialAnomalyScore, anomalyScore, records,
                 isInterim, bucketSpan, bucketInfluencers, partitionScores, processingTimeMs);
     }
 
@@ -331,7 +326,6 @@ public class Bucket extends ToXContentToBytes implements Writeable {
 
         return Objects.equals(this.jobId, that.jobId) && Objects.equals(this.timestamp, that.timestamp)
                 && (this.eventCount == that.eventCount) && (this.bucketSpan == that.bucketSpan)
-                && (this.recordCount == that.recordCount)
                 && (this.anomalyScore == that.anomalyScore) && (this.initialAnomalyScore == that.initialAnomalyScore)
                 && Objects.equals(this.records, that.records) && Objects.equals(this.isInterim, that.isInterim)
                 && Objects.equals(this.bucketInfluencers, that.bucketInfluencers)

plugin/src/test/java/org/elasticsearch/xpack/ml/action/GetBucketActionResponseTests.java

@@ -65,9 +65,6 @@ public class GetBucketActionResponseTests extends AbstractStreamableTestCase<Get
             if (randomBoolean()) {
                 bucket.setProcessingTimeMs(randomLong());
             }
-            if (randomBoolean()) {
-                bucket.setRecordCount(randomInt());
-            }
             if (randomBoolean()) {
                 int size = randomInt(10);
                 List<AnomalyRecord> records = new ArrayList<>(size);

plugin/src/test/java/org/elasticsearch/xpack/ml/integration/UpdateInterimResultsIT.java

@@ -15,7 +15,7 @@ import org.elasticsearch.xpack.ml.job.config.Job;
 import org.elasticsearch.xpack.ml.job.results.Bucket;
 import org.junit.After;
 
-import java.util.Arrays;
+import java.util.Collections;
 import java.util.HashMap;
 import java.util.List;
 import java.util.Map;
@@ -43,7 +43,7 @@ public class UpdateInterimResultsIT extends MlNativeAutodetectIntegTestCase {
 
     public void test() throws Exception {
         AnalysisConfig.Builder analysisConfig = new AnalysisConfig.Builder(
-                Arrays.asList(new Detector.Builder("max", "value").build()));
+                Collections.singletonList(new Detector.Builder("max", "value").build()));
         analysisConfig.setBucketSpan(TimeValue.timeValueSeconds(BUCKET_SPAN_SECONDS));
         analysisConfig.setOverlappingBuckets(true);
         DataDescription.Builder dataDescription = new DataDescription.Builder();
@@ -83,9 +83,7 @@ public class UpdateInterimResultsIT extends MlNativeAutodetectIntegTestCase {
             List<Bucket> firstInterimBuckets = getInterimResults(job.getId());
             assertThat(firstInterimBuckets.size(), equalTo(2));
             assertThat(firstInterimBuckets.get(0).getTimestamp().getTime(), equalTo(1400039000000L));
-            assertThat(firstInterimBuckets.get(0).getRecordCount(), equalTo(0));
             assertThat(firstInterimBuckets.get(1).getTimestamp().getTime(), equalTo(1400040000000L));
-            assertThat(firstInterimBuckets.get(1).getRecordCount(), equalTo(1));
             assertThat(firstInterimBuckets.get(1).getRecords().get(0).getActual().get(0), equalTo(16.0));
         });
 
@@ -97,9 +95,7 @@ public class UpdateInterimResultsIT extends MlNativeAutodetectIntegTestCase {
         assertBusy(() -> {
             List<Bucket> secondInterimBuckets = getInterimResults(job.getId());
             assertThat(secondInterimBuckets.get(0).getTimestamp().getTime(), equalTo(1400039000000L));
-            assertThat(secondInterimBuckets.get(0).getRecordCount(), equalTo(0));
             assertThat(secondInterimBuckets.get(1).getTimestamp().getTime(), equalTo(1400040000000L));
-            assertThat(secondInterimBuckets.get(1).getRecordCount(), equalTo(1));
             assertThat(secondInterimBuckets.get(1).getRecords().get(0).getActual().get(0), equalTo(16.0));
         });
 
@@ -122,7 +118,7 @@ public class UpdateInterimResultsIT extends MlNativeAutodetectIntegTestCase {
         StringBuilder data = new StringBuilder();
         for (int i = 0; i < halfBuckets; i++) {
             int value = timeToValueMap.getOrDefault(time, randomIntBetween(1, 3));
-            data.append("{\"time\":" + time + ", \"value\":" + value + "}\n");
+            data.append("{\"time\":").append(time).append(", \"value\":").append(value).append("}\n");
             time += BUCKET_SPAN_SECONDS / 2;
         }
         return data.toString();
@@ -136,6 +132,6 @@ public class UpdateInterimResultsIT extends MlNativeAutodetectIntegTestCase {
         assertThat(response.getBuckets().count(), lessThan(1500L));
         List<Bucket> buckets = response.getBuckets().results();
         assertThat(buckets.size(), greaterThan(0));
-        return buckets.stream().filter(b -> b.isInterim()).collect(Collectors.toList());
+        return buckets.stream().filter(Bucket::isInterim).collect(Collectors.toList());
     }
 }

plugin/src/test/java/org/elasticsearch/xpack/ml/job/persistence/JobResultsPersisterTests.java

@@ -21,7 +21,7 @@ import org.mockito.ArgumentCaptor;
 
 import java.io.IOException;
 import java.util.ArrayList;
-import java.util.Arrays;
+import java.util.Collections;
 import java.util.Date;
 import java.util.List;
 
@@ -41,7 +41,6 @@ public class JobResultsPersisterTests extends ESTestCase {
         bucket.setEventCount(57);
         bucket.setInitialAnomalyScore(88.8);
         bucket.setProcessingTimeMs(8888);
-        bucket.setRecordCount(1);
 
         BucketInfluencer bi = new BucketInfluencer(JOB_ID, new Date(), 600);
         bi.setAnomalyScore(14.15);
@@ -53,7 +52,7 @@ public class JobResultsPersisterTests extends ESTestCase {
 
         // We are adding a record but it shouldn't be persisted as part of the bucket
         AnomalyRecord record = new AnomalyRecord(JOB_ID, new Date(), 600);
-        bucket.setRecords(Arrays.asList(record));
+        bucket.setRecords(Collections.singletonList(record));
 
         JobResultsPersister persister = new JobResultsPersister(Settings.EMPTY, client);
         persister.bulkPersisterBuilder(JOB_ID).persistBucket(bucket).executeRequest();
@@ -63,7 +62,6 @@ public class JobResultsPersisterTests extends ESTestCase {
         String s = ((IndexRequest)bulkRequest.requests().get(0)).source().utf8ToString();
         assertTrue(s.matches(".*anomaly_score.:99\\.9.*"));
         assertTrue(s.matches(".*initial_anomaly_score.:88\\.8.*"));
-        assertTrue(s.matches(".*record_count.:1.*"));
         assertTrue(s.matches(".*event_count.:57.*"));
         assertTrue(s.matches(".*bucket_span.:123456.*"));
         assertTrue(s.matches(".*processing_time_ms.:8888.*"));

plugin/src/test/java/org/elasticsearch/xpack/ml/job/process/autodetect/output/AutodetectResultsParserTests.java

@@ -34,9 +34,9 @@ import static org.mockito.Mockito.when;
 public class AutodetectResultsParserTests extends ESTestCase {
     private static final double EPSILON = 0.000001;
 
-    public static final String METRIC_OUTPUT_SAMPLE = "[{\"bucket\": {\"job_id\":\"foo\",\"timestamp\":1359450000000,"
+    private static final String METRIC_OUTPUT_SAMPLE = "[{\"bucket\": {\"job_id\":\"foo\",\"timestamp\":1359450000000,"
             + "\"bucket_span\":22, \"records\":[],"
-            + "\"anomaly_score\":0,\"record_count\":0,\"event_count\":806,\"bucket_influencers\":["
+            + "\"anomaly_score\":0,\"event_count\":806,\"bucket_influencers\":["
             + "{\"timestamp\":1359450000000,\"bucket_span\":22,\"job_id\":\"foo\",\"anomaly_score\":0,"
             + "\"probability\":0.0, \"influencer_field_name\":\"bucket_time\","
             + "\"initial_anomaly_score\":0.0}]}},{\"quantiles\": {\"job_id\":\"foo\", \"quantile_state\":\"[normalizer 1.1, normalizer 2" +
@@ -56,7 +56,7 @@ public class AutodetectResultsParserTests extends ESTestCase {
             + "\"probability\":0.0473552,\"by_field_name\":\"airline\",\"by_field_value\":\"SWA\", \"typical\":[152.148],"
             + "\"actual\":[96.6425],\"field_name\":\"responsetime\",\"function\":\"min\",\"partition_field_name\":\"\","
             + "\"partition_field_value\":\"\"}],"
-            + "\"initial_anomaly_score\":0.0140005, \"anomaly_score\":20.22688, \"record_count\":4,"
+            + "\"initial_anomaly_score\":0.0140005, \"anomaly_score\":20.22688,"
             + "\"event_count\":820,\"bucket_influencers\":[{\"timestamp\":1359453600000,\"bucket_span\":22,"
             + "\"job_id\":\"foo\", \"raw_anomaly_score\":0.0140005, \"probability\":0.01,\"influencer_field_name\":\"bucket_time\","
             + "\"initial_anomaly_score\":20.22688,\"anomaly_score\":20.22688} ,{\"timestamp\":1359453600000,\"bucket_span\":22,"
@@ -66,7 +66,7 @@ public class AutodetectResultsParserTests extends ESTestCase {
             + "\"quantile_state\":\"[normalizer 1.2, normalizer 2.2]\"}} ,{\"flush\": {\"id\":\"testing1\"}} ,"
             + "{\"quantiles\": {\"job_id\":\"foo\",\"timestamp\":1359453600000,\"quantile_state\":\"[normalizer 1.3, normalizer 2.3]\"}} ]";
 
-    public static final String POPULATION_OUTPUT_SAMPLE = "[{\"timestamp\":1379590200,\"records\":[{\"probability\":1.38951e-08,"
+    private static final String POPULATION_OUTPUT_SAMPLE = "[{\"timestamp\":1379590200,\"records\":[{\"probability\":1.38951e-08,"
             + "\"field_name\":\"sum_cs_bytes_\",\"over_field_name\":\"cs_host\",\"over_field_value\":\"mail.google.com\","
             + "\"function\":\"max\","
             + "\"causes\":[{\"probability\":1.38951e-08,\"field_name\":\"sum_cs_bytes_\",\"over_field_name\":\"cs_host\","
@@ -84,7 +84,7 @@ public class AutodetectResultsParserTests extends ESTestCase {
             + "\"probability\":0.0152333,\"field_name\":\"sum_cs_bytes_\",\"over_field_name\":\"cs_host\","
             + "\"over_field_value\":\"emea.salesforce.com\",\"function\":\"max\",\"typical\":[101534],\"actual\":[5.36373e+06]}],"
             + "\"record_score\":0.303996,\"anomaly_score\":44.7324}],\"raw_anomaly_score\":1.30397,\"anomaly_score\":44.7324,"
-            + "\"record_count\":4,\"event_count\":1235}" + ",{\"flush\":\"testing2\"}"
+            + "\"event_count\":1235}" + ",{\"flush\":\"testing2\"}"
             + ",{\"timestamp\":1379590800,\"records\":[{\"probability\":1.9008e-08,\"field_name\":\"sum_cs_bytes_\","
             + "\"over_field_name\":\"cs_host\",\"over_field_value\":\"mail.google.com\",\"function\":\"max\",\"causes\":[{"
             + "\"probability\":1.9008e-08,\"field_name\":\"sum_cs_bytes_\",\"over_field_name\":\"cs_host\","
@@ -233,7 +233,7 @@ public class AutodetectResultsParserTests extends ESTestCase {
             + "\"field_name\":\"sum_cs_bytes_\",\"over_field_name\":\"cs_host\",\"over_field_value\":\"googleads.g.doubleclick.net\","
             + "\"function\":\"max\",\"typical\":[31356],\"actual\":[210926]}],\"record_score\":0.00237509,"
             + "\"anomaly_score\":1.19192}],\"raw_anomaly_score\":1.26918,\"anomaly_score\":1.19192,"
-            + "\"record_count\":34,\"event_count\":1159}" + "]";
+            + "\"event_count\":1159}" + "]";
 
     public void testParser() throws IOException {
         InputStream inputStream = new ByteArrayInputStream(METRIC_OUTPUT_SAMPLE.getBytes(StandardCharsets.UTF_8));
@@ -246,7 +246,6 @@ public class AutodetectResultsParserTests extends ESTestCase {
 
         assertEquals(2, buckets.size());
         assertEquals(new Date(1359450000000L), buckets.get(0).getTimestamp());
-        assertEquals(0, buckets.get(0).getRecordCount());
 
         assertEquals(buckets.get(0).getEventCount(), 806);
 
@@ -258,7 +257,6 @@ public class AutodetectResultsParserTests extends ESTestCase {
         assertEquals("bucket_time", bucketInfluencers.get(0).getInfluencerFieldName());
 
         assertEquals(new Date(1359453600000L), buckets.get(1).getTimestamp());
-        assertEquals(4, buckets.get(1).getRecordCount());
 
         assertEquals(buckets.get(1).getEventCount(), 820);
         bucketInfluencers = buckets.get(1).getBucketInfluencers();
@@ -341,7 +339,6 @@ public class AutodetectResultsParserTests extends ESTestCase {
 
         assertEquals(2, buckets.size());
         assertEquals(new Date(1379590200000L), buckets.get(0).getTimestamp());
-        assertEquals(4, buckets.get(0).getRecordCount());
         assertEquals(buckets.get(0).getEventCount(), 1235);
 
         Bucket firstBucket = buckets.get(0);
@@ -353,7 +350,6 @@ public class AutodetectResultsParserTests extends ESTestCase {
         assertNotNull(firstBucket.getRecords().get(0).getCauses());
 
         assertEquals(new Date(1379590800000L), buckets.get(1).getTimestamp());
-        assertEquals(34, buckets.get(1).getRecordCount());
         assertEquals(buckets.get(1).getEventCount(), 1159);
     }
 

plugin/src/test/java/org/elasticsearch/xpack/ml/job/results/BucketTests.java

@@ -62,9 +62,6 @@ public class BucketTests extends AbstractSerializingTestCase<Bucket> {
         if (randomBoolean()) {
             bucket.setProcessingTimeMs(randomLong());
         }
-        if (randomBoolean()) {
-            bucket.setRecordCount(randomInt());
-        }
         if (randomBoolean()) {
             int size = randomInt(10);
             List<AnomalyRecord> records = new ArrayList<>(size);
@@ -126,19 +123,9 @@ public class BucketTests extends AbstractSerializingTestCase<Bucket> {
         assertFalse(bucket2.equals(bucket1));
     }
 
-    public void testEquals_GivenDifferentRecordCount() {
-        Bucket bucket1 = new Bucket("foo", new Date(123), 123);
-        bucket1.setRecordCount(300);
-        Bucket bucket2 = new Bucket("foo", new Date(123), 123);
-        bucket2.setRecordCount(400);
-
-        assertFalse(bucket1.equals(bucket2));
-        assertFalse(bucket2.equals(bucket1));
-    }
-
     public void testEquals_GivenOneHasRecordsAndTheOtherDoesNot() {
         Bucket bucket1 = new Bucket("foo", new Date(123), 123);
-        bucket1.setRecords(Arrays.asList(new AnomalyRecord("foo", new Date(123), 123)));
+        bucket1.setRecords(Collections.singletonList(new AnomalyRecord("foo", new Date(123), 123)));
         Bucket bucket2 = new Bucket("foo", new Date(123), 123);
         bucket2.setRecords(Collections.emptyList());
 
@@ -148,7 +135,7 @@ public class BucketTests extends AbstractSerializingTestCase<Bucket> {
 
     public void testEquals_GivenDifferentNumberOfRecords() {
         Bucket bucket1 = new Bucket("foo", new Date(123), 123);
-        bucket1.setRecords(Arrays.asList(new AnomalyRecord("foo", new Date(123), 123)));
+        bucket1.setRecords(Collections.singletonList(new AnomalyRecord("foo", new Date(123), 123)));
         Bucket bucket2 = new Bucket("foo", new Date(123), 123);
         bucket2.setRecords(Arrays.asList(new AnomalyRecord("foo", new Date(123), 123),
                 new AnomalyRecord("foo", new Date(123), 123)));
@@ -164,9 +151,9 @@ public class BucketTests extends AbstractSerializingTestCase<Bucket> {
         anomalyRecord1.setRecordScore(2.0);
 
         Bucket bucket1 = new Bucket("foo", new Date(123), 123);
-        bucket1.setRecords(Arrays.asList(anomalyRecord1));
+        bucket1.setRecords(Collections.singletonList(anomalyRecord1));
         Bucket bucket2 = new Bucket("foo", new Date(123), 123);
-        bucket2.setRecords(Arrays.asList(anomalyRecord2));
+        bucket2.setRecords(Collections.singletonList(anomalyRecord2));
 
         assertFalse(bucket1.equals(bucket2));
         assertFalse(bucket2.equals(bucket1));
@@ -207,8 +194,7 @@ public class BucketTests extends AbstractSerializingTestCase<Bucket> {
         bucket1.setInitialAnomalyScore(92.0);
         bucket1.setEventCount(134);
         bucket1.setInterim(true);
-        bucket1.setRecordCount(4);
+        bucket1.setRecords(Collections.singletonList(record));
-        bucket1.setRecords(Arrays.asList(record));
         bucket1.addBucketInfluencer(bucketInfluencer);
 
         Bucket bucket2 = new Bucket("foo", date, 123);
@@ -216,8 +202,7 @@ public class BucketTests extends AbstractSerializingTestCase<Bucket> {
         bucket2.setInitialAnomalyScore(92.0);
         bucket2.setEventCount(134);
         bucket2.setInterim(true);
-        bucket2.setRecordCount(4);
+        bucket2.setRecords(Collections.singletonList(record));
-        bucket2.setRecords(Arrays.asList(record));
         bucket2.addBucketInfluencer(bucketInfluencer);
 
         assertTrue(bucket1.equals(bucket2));
@@ -229,7 +214,6 @@ public class BucketTests extends AbstractSerializingTestCase<Bucket> {
         Bucket bucket = new Bucket("foo", new Date(123), 123);
         bucket.addBucketInfluencer(new BucketInfluencer("foo", new Date(123), 123));
         bucket.setAnomalyScore(0.0);
-        bucket.setRecordCount(0);
 
         assertFalse(bucket.isNormalizable());
     }
@@ -247,7 +231,6 @@ public class BucketTests extends AbstractSerializingTestCase<Bucket> {
         Bucket bucket = new Bucket("foo", new Date(123), 123);
         bucket.addBucketInfluencer(new BucketInfluencer("foo", new Date(123), 123));
         bucket.setAnomalyScore(1.0);
-        bucket.setRecordCount(0);
 
         assertTrue(bucket.isNormalizable());
     }
@@ -256,7 +239,6 @@ public class BucketTests extends AbstractSerializingTestCase<Bucket> {
         Bucket bucket = new Bucket("foo", new Date(123), 123);
         bucket.addBucketInfluencer(new BucketInfluencer("foo", new Date(123), 123));
         bucket.setAnomalyScore(1.0);
-        bucket.setRecordCount(1);
 
         assertTrue(bucket.isNormalizable());
     }