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Use jobId_timestamp_bucketSpan as ID for bucket (elastic/elasticsearch#375) 

Removes the reliance on ES autogenerated UUIDs and instead uses `{jobId}_{timestamp}_{bucketSpan}`

Original commit: elastic/x-pack-elasticsearch@3cd774edd8
This commit is contained in:
Zachary Tong 2016-11-28 13:59:47 -05:00 committed by GitHub
parent b526d7920d
commit 2b2307a82b
13 changed files with 85 additions and 136 deletions
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4
elasticsearch/src/main/java/org/elasticsearch/xpack/prelert/job/persistence/ElasticsearchBatchedBucketsIterator.java
View File

@ -32,8 +32,6 @@ class ElasticsearchBatchedBucketsIterator extends ElasticsearchBatchedResultsIte
} catch (IOException e) {
throw new ElasticsearchParseException("failed to parse bucket", e);
}
Bucket bucket = Bucket.PARSER.apply(parser, () -> parseFieldMatcher);
bucket.setId(hit.getId());
return bucket;
return Bucket.PARSER.apply(parser, () -> parseFieldMatcher);
}
}

2
elasticsearch/src/main/java/org/elasticsearch/xpack/prelert/job/persistence/ElasticsearchJobProvider.java
View File

@ -363,7 +363,6 @@ public class ElasticsearchJobProvider implements JobProvider {
throw new ElasticsearchParseException("failed to parser bucket", e);
}
Bucket bucket = Bucket.PARSER.apply(parser, () -> parseFieldMatcher);
bucket.setId(hit.getId());
if (includeInterim || bucket.isInterim() == false) {
results.add(bucket);
@ -412,7 +411,6 @@ public class ElasticsearchJobProvider implements JobProvider {
throw new ElasticsearchParseException("failed to parser bucket", e);
}
Bucket bucket = Bucket.PARSER.apply(parser, () -> parseFieldMatcher);
bucket.setId(hit.getId());
// don't return interim buckets if not requested
if (bucket.isInterim() && query.isIncludeInterim() == false) {

1
elasticsearch/src/main/java/org/elasticsearch/xpack/prelert/job/persistence/JobResultsPersister.java
View File

@ -79,7 +79,6 @@ public class JobResultsPersister extends AbstractComponent {
IndexResponse response = client.prepareIndex(indexName, Result.TYPE.getPreferredName())
.setSource(content)
.execute().actionGet();
bucket.setId(response.getId());
persistBucketInfluencersStandalone(jobId, bucket.getId(), bucket.getBucketInfluencers(), bucket.getTimestamp(),
bucket.isInterim());

55
elasticsearch/src/main/java/org/elasticsearch/xpack/prelert/job/results/Bucket.java
View File

@ -15,7 +15,10 @@ import org.elasticsearch.common.io.stream.Writeable;
import org.elasticsearch.common.xcontent.ConstructingObjectParser;
import org.elasticsearch.common.xcontent.ObjectParser.ValueType;
import org.elasticsearch.common.xcontent.XContentBuilder;
import org.elasticsearch.common.xcontent.ObjectParser.ValueType;
import org.elasticsearch.common.xcontent.XContentParser.Token;
import org.elasticsearch.xpack.prelert.job.Job;
import org.elasticsearch.xpack.prelert.utils.ExceptionsHelper;
import org.elasticsearch.xpack.prelert.utils.time.TimeUtils;
import java.io.IOException;
@ -36,7 +39,7 @@ public class Bucket extends ToXContentToBytes implements Writeable {
/*
* Field Names
*/
public static final ParseField JOB_ID = new ParseField("jobId");
public static final ParseField JOB_ID = Job.ID;
public static final ParseField TIMESTAMP = new ParseField("timestamp");
public static final ParseField ANOMALY_SCORE = new ParseField("anomalyScore");
public static final ParseField INITIAL_ANOMALY_SCORE = new ParseField("initialAnomalyScore");
@ -60,11 +63,11 @@ public class Bucket extends ToXContentToBytes implements Writeable {
public static final ParseField RESULT_TYPE_FIELD = new ParseField(RESULT_TYPE_VALUE);
public static final ConstructingObjectParser<Bucket, ParseFieldMatcherSupplier> PARSER =
new ConstructingObjectParser<>(RESULT_TYPE_VALUE, a -> new Bucket((String) a[0]));
new ConstructingObjectParser<>(RESULT_TYPE_VALUE, a -> new Bucket((String) a[0], (Date) a[1], (long) a[2]));
static {
PARSER.declareString(ConstructingObjectParser.constructorArg(), JOB_ID);
PARSER.declareField(Bucket::setTimestamp, p -> {
PARSER.declareField(ConstructingObjectParser.constructorArg(), p -> {
if (p.currentToken() == Token.VALUE_NUMBER) {
return new Date(p.longValue());
} else if (p.currentToken() == Token.VALUE_STRING) {
@ -72,6 +75,7 @@ public class Bucket extends ToXContentToBytes implements Writeable {
}
throw new IllegalArgumentException("unexpected token [" + p.currentToken() + "] for [" + TIMESTAMP.getPreferredName() + "]");
}, TIMESTAMP, ValueType.VALUE);
PARSER.declareLong(ConstructingObjectParser.constructorArg(), BUCKET_SPAN);
PARSER.declareDouble(Bucket::setAnomalyScore, ANOMALY_SCORE);
PARSER.declareDouble(Bucket::setInitialAnomalyScore, INITIAL_ANOMALY_SCORE);
PARSER.declareDouble(Bucket::setMaxNormalizedProbability, MAX_NORMALIZED_PROBABILITY);
@ -80,20 +84,16 @@ public class Bucket extends ToXContentToBytes implements Writeable {
PARSER.declareLong(Bucket::setEventCount, EVENT_COUNT);
PARSER.declareObjectArray(Bucket::setRecords, AnomalyRecord.PARSER, RECORDS);
PARSER.declareObjectArray(Bucket::setBucketInfluencers, BucketInfluencer.PARSER, BUCKET_INFLUENCERS);
PARSER.declareLong(Bucket::setBucketSpan, BUCKET_SPAN);
PARSER.declareLong(Bucket::setProcessingTimeMs, PROCESSING_TIME_MS);
PARSER.declareObjectArray(Bucket::setPartitionScores, PartitionScore.PARSER, PARTITION_SCORES);
PARSER.declareString((bucket, s) -> {}, Result.RESULT_TYPE);
}
private final String jobId;
private String id;
private Date timestamp;
private final Date timestamp;
private final long bucketSpan;
private double anomalyScore;
private long bucketSpan;
private double initialAnomalyScore;
private double maxNormalizedProbability;
private int recordCount;
private List<AnomalyRecord> records = Collections.emptyList();
@ -105,17 +105,16 @@ public class Bucket extends ToXContentToBytes implements Writeable {
private Map<String, Double> perPartitionMaxProbability = Collections.emptyMap();
private List<PartitionScore> partitionScores = Collections.emptyList();
public Bucket(String jobId) {
public Bucket(String jobId, Date timestamp, long bucketSpan) {
this.jobId = jobId;
this.timestamp = ExceptionsHelper.requireNonNull(timestamp, TIMESTAMP.getPreferredName());
this.bucketSpan = bucketSpan;
}
@SuppressWarnings("unchecked")
public Bucket(StreamInput in) throws IOException {
jobId = in.readString();
id = in.readOptionalString();
if (in.readBoolean()) {
timestamp = new Date(in.readLong());
}
timestamp = new Date(in.readLong());
anomalyScore = in.readDouble();
bucketSpan = in.readLong();
initialAnomalyScore = in.readDouble();
@ -134,12 +133,7 @@ public class Bucket extends ToXContentToBytes implements Writeable {
@Override
public void writeTo(StreamOutput out) throws IOException {
out.writeString(jobId);
out.writeOptionalString(id);
boolean hasTimestamp = timestamp != null;
out.writeBoolean(hasTimestamp);
if (hasTimestamp) {
out.writeLong(timestamp.getTime());
}
out.writeLong(timestamp.getTime());
out.writeDouble(anomalyScore);
out.writeLong(bucketSpan);
out.writeDouble(initialAnomalyScore);
@ -159,9 +153,7 @@ public class Bucket extends ToXContentToBytes implements Writeable {
public XContentBuilder toXContent(XContentBuilder builder, Params params) throws IOException {
builder.startObject();
builder.field(JOB_ID.getPreferredName(), jobId);
if (timestamp != null) {
builder.field(TIMESTAMP.getPreferredName(), timestamp.getTime());
}
builder.field(TIMESTAMP.getPreferredName(), timestamp.getTime());
builder.field(ANOMALY_SCORE.getPreferredName(), anomalyScore);
builder.field(BUCKET_SPAN.getPreferredName(), bucketSpan);
builder.field(INITIAL_ANOMALY_SCORE.getPreferredName(), initialAnomalyScore);
@ -186,11 +178,7 @@ public class Bucket extends ToXContentToBytes implements Writeable {
}
public String getId() {
return id;
}
public void setId(String id) {
this.id = id;
return jobId + "_" + timestamp.getTime() + "_" + bucketSpan;
}
/**
@ -205,10 +193,6 @@ public class Bucket extends ToXContentToBytes implements Writeable {
return timestamp;
}
public void setTimestamp(Date timestamp) {
this.timestamp = timestamp;
}
/**
* Bucketspan expressed in seconds
*/
@ -216,13 +200,6 @@ public class Bucket extends ToXContentToBytes implements Writeable {
return bucketSpan;
}
/**
* Bucketspan expressed in seconds
*/
public void setBucketSpan(long bucketSpan) {
this.bucketSpan = bucketSpan;
}
public double getAnomalyScore() {
return anomalyScore;
}

11
elasticsearch/src/test/java/org/elasticsearch/xpack/prelert/action/GetBucketActionResponseTests.java
View File

@ -29,7 +29,7 @@ public class GetBucketActionResponseTests extends AbstractStreamableTestCase<Get
List<Bucket> hits = new ArrayList<>(listSize);
for (int j = 0; j < listSize; j++) {
String jobId = "foo";
Bucket bucket = new Bucket(jobId);
Bucket bucket = new Bucket(jobId, new Date(randomLong()), randomPositiveLong());
if (randomBoolean()) {
bucket.setAnomalyScore(randomDouble());
}
@ -47,15 +47,9 @@ public class GetBucketActionResponseTests extends AbstractStreamableTestCase<Get
}
bucket.setBucketInfluencers(bucketInfluencers);
}
if (randomBoolean()) {
bucket.setBucketSpan(randomPositiveLong());
}
if (randomBoolean()) {
bucket.setEventCount(randomPositiveLong());
}
if (randomBoolean()) {
bucket.setId(randomAsciiOfLengthBetween(1, 20));
}
if (randomBoolean()) {
bucket.setInitialAnomalyScore(randomDouble());
}
@ -104,9 +98,6 @@ public class GetBucketActionResponseTests extends AbstractStreamableTestCase<Get
}
bucket.setRecords(records);
}
if (randomBoolean()) {
bucket.setTimestamp(new Date(randomLong()));
}
hits.add(bucket);
}
QueryPage<Bucket> buckets = new QueryPage<>(hits, listSize, Bucket.RESULTS_FIELD);

17
elasticsearch/src/test/java/org/elasticsearch/xpack/prelert/integration/PrelertJobIT.java
View File

@ -189,9 +189,9 @@ public class PrelertJobIT extends ESRestTestCase {
assertThat(e.getResponse().getStatusLine().getStatusCode(), equalTo(404));
assertThat(e.getMessage(), containsString("No known job with id '1'"));
addBucketResult("1", "1234");
addBucketResult("1", "1235");
addBucketResult("1", "1236");
addBucketResult("1", "1234", 1);
addBucketResult("1", "1235", 1);
addBucketResult("1", "1236", 1);
Response response = client().performRequest("get", PrelertPlugin.BASE_PATH + "results/1/buckets", params);
assertThat(response.getStatusLine().getStatusCode(), equalTo(200));
String responseAsString = responseEntityToString(response);
@ -307,7 +307,7 @@ public class PrelertJobIT extends ESRestTestCase {
assertThat(e.getMessage(), containsString("Cannot resume job 'farequote' while its status is CLOSED"));
}
private Response addBucketResult(String jobId, String timestamp) throws Exception {
private Response addBucketResult(String jobId, String timestamp, long bucketSpan) throws Exception {
try {
client().performRequest("put", "prelertresults-" + jobId, Collections.emptyMap(), new StringEntity(RESULT_MAPPING));
} catch (ResponseException e) {
@ -316,9 +316,12 @@ public class PrelertJobIT extends ESRestTestCase {
assertThat(e.getResponse().getStatusLine().getStatusCode(), equalTo(400));
}
String bucketResult =
String.format(Locale.ROOT, "{\"jobId\":\"%s\", \"timestamp\": \"%s\", \"result_type\":\"bucket\"}", jobId, timestamp);
return client().performRequest("put", "prelertresults-" + jobId + "/result/" + timestamp,
String bucketResult = String.format(Locale.ROOT,
"{\"jobId\":\"%s\", \"timestamp\": \"%s\", \"result_type\":\"bucket\", \"bucketSpan\": \"%s\"}",
jobId, timestamp, bucketSpan);
String id = String.format(Locale.ROOT,
"%s_%s_%s", jobId, timestamp, bucketSpan);
return client().performRequest("put", "prelertresults-" + jobId + "/result/" + id,
Collections.singletonMap("refresh", "true"), new StringEntity(bucketResult));
}

14
elasticsearch/src/test/java/org/elasticsearch/xpack/prelert/job/persistence/ElasticsearchJobProviderTests.java
View File

@ -212,6 +212,7 @@ public class ElasticsearchJobProviderTests extends ESTestCase {
Map<String, Object> map = new HashMap<>();
map.put("jobId", "foo");
map.put("timestamp", now.getTime());
map.put("bucketSpan", 22);
source.add(map);
ArgumentCaptor<QueryBuilder> queryBuilder = ArgumentCaptor.forClass(QueryBuilder.class);
@ -245,6 +246,7 @@ public class ElasticsearchJobProviderTests extends ESTestCase {
Map<String, Object> map = new HashMap<>();
map.put("jobId", "foo");
map.put("timestamp", now.getTime());
map.put("bucketSpan", 22);
source.add(map);
ArgumentCaptor<QueryBuilder> queryBuilder = ArgumentCaptor.forClass(QueryBuilder.class);
@ -279,6 +281,7 @@ public class ElasticsearchJobProviderTests extends ESTestCase {
Map<String, Object> map = new HashMap<>();
map.put("jobId", "foo");
map.put("timestamp", now.getTime());
map.put("bucketSpan", 22);
source.add(map);
ArgumentCaptor<QueryBuilder> queryBuilder = ArgumentCaptor.forClass(QueryBuilder.class);
@ -343,6 +346,7 @@ public class ElasticsearchJobProviderTests extends ESTestCase {
Map<String, Object> map = new HashMap<>();
map.put("jobId", "foo");
map.put("timestamp", now.getTime());
map.put("bucketSpan", 22);
source.add(map);
ArgumentCaptor<QueryBuilder> queryBuilder = ArgumentCaptor.forClass(QueryBuilder.class);
@ -371,6 +375,7 @@ public class ElasticsearchJobProviderTests extends ESTestCase {
Map<String, Object> map = new HashMap<>();
map.put("jobId", "foo");
map.put("timestamp", now.getTime());
map.put("bucketSpan", 22);
map.put("isInterim", true);
source.add(map);
@ -545,8 +550,7 @@ public class ElasticsearchJobProviderTests extends ESTestCase {
public void testexpandBucket() throws InterruptedException, ExecutionException, IOException {
String jobId = "TestJobIdentification";
Date now = new Date();
Bucket bucket = new Bucket("foo");
bucket.setTimestamp(now);
Bucket bucket = new Bucket("foo", now, 22);
List<Map<String, Object>> source = new ArrayList<>();
for (int i = 0; i < 400; i++) {
@ -577,8 +581,7 @@ public class ElasticsearchJobProviderTests extends ESTestCase {
throws InterruptedException, ExecutionException, IOException {
String jobId = "TestJobIdentification";
Date now = new Date();
Bucket bucket = new Bucket("foo");
bucket.setTimestamp(now);
Bucket bucket = new Bucket("foo", now, 22);
List<Map<String, Object>> source = new ArrayList<>();
for (int i = 0; i < 600; i++) {
@ -998,8 +1001,7 @@ public class ElasticsearchJobProviderTests extends ESTestCase {
}
private Bucket createBucketAtEpochTime(long epoch) {
Bucket b = new Bucket("foo");
b.setTimestamp(new Date(epoch));
Bucket b = new Bucket("foo", new Date(epoch), 123);
b.setMaxNormalizedProbability(10.0);
return b;
}

6
elasticsearch/src/test/java/org/elasticsearch/xpack/prelert/job/persistence/JobResultsPersisterTests.java
View File

@ -42,12 +42,8 @@ public class JobResultsPersisterTests extends ESTestCase {
.prepareBulk(response);
Client client = clientBuilder.build();
Bucket bucket = new Bucket("foo");
bucket.setId("1");
bucket.setTimestamp(new Date());
bucket.setId(responseId);
Bucket bucket = new Bucket("foo", new Date(), 123456);
bucket.setAnomalyScore(99.9);
bucket.setBucketSpan(123456);
bucket.setEventCount(57);
bucket.setInitialAnomalyScore(88.8);
bucket.setMaxNormalizedProbability(42.0);

6
elasticsearch/src/test/java/org/elasticsearch/xpack/prelert/job/process/autodetect/output/AutodetectResultsParserTests.java
View File

@ -29,11 +29,13 @@ import java.util.stream.Collectors;
public class AutodetectResultsParserTests extends ESTestCase {
private static final double EPSILON = 0.000001;
public static final String METRIC_OUTPUT_SAMPLE = "[{\"bucket\": {\"jobId\":\"foo\",\"timestamp\":1359450000000,\"records\":[],"
public static final String METRIC_OUTPUT_SAMPLE = "[{\"bucket\": {\"jobId\":\"foo\",\"timestamp\":1359450000000,"
+ "\"bucketSpan\":22, \"records\":[],"
+ "\"maxNormalizedProbability\":0, \"anomalyScore\":0,\"recordCount\":0,\"eventCount\":806,\"bucketInfluencers\":["
+ "{\"jobId\":\"foo\",\"anomalyScore\":0, \"probability\":0.0, \"influencerFieldName\":\"bucketTime\","
+ "\"initialAnomalyScore\":0.0}]}},{\"quantiles\": {\"jobId\":\"foo\", \"quantileState\":\"[normaliser 1.1, normaliser 2.1]\"}}"
+ ",{\"bucket\": {\"jobId\":\"foo\",\"timestamp\":1359453600000,\"records\":[{\"jobId\":\"foo\",\"probability\":0.0637541,"
+ ",{\"bucket\": {\"jobId\":\"foo\",\"timestamp\":1359453600000,\"bucketSpan\":22,"
+ "\"records\":[{\"jobId\":\"foo\",\"probability\":0.0637541,"
+ "\"byFieldName\":\"airline\",\"byFieldValue\":\"JZA\", \"typical\":[1020.08],\"actual\":[1042.14],"
+ "\"fieldName\":\"responsetime\",\"function\":\"max\",\"partitionFieldName\":\"\",\"partitionFieldValue\":\"\"},"
+ "{\"jobId\":\"foo\",\"probability\":0.00748292,\"byFieldName\":\"airline\",\"byFieldValue\":\"AMX\", "

3
elasticsearch/src/test/java/org/elasticsearch/xpack/prelert/job/results/AutodetectResultTests.java
View File

@ -38,8 +38,7 @@ public class AutodetectResultTests extends AbstractSerializingTestCase<Autodetec
FlushAcknowledgement flushAcknowledgement;
String jobId = "foo";
if (randomBoolean()) {
bucket = new Bucket(jobId);
bucket.setId(randomAsciiOfLengthBetween(1, 20));
bucket = new Bucket(jobId, new Date(randomLong()), randomPositiveLong());
} else {
bucket = null;
}

86
elasticsearch/src/test/java/org/elasticsearch/xpack/prelert/job/results/BucketTests.java
View File

@ -23,7 +23,7 @@ public class BucketTests extends AbstractSerializingTestCase<Bucket> {
@Override
protected Bucket createTestInstance() {
String jobId = "foo";
Bucket bucket = new Bucket(jobId);
Bucket bucket = new Bucket(jobId, new Date(randomLong()), randomPositiveLong());
if (randomBoolean()) {
bucket.setAnomalyScore(randomDouble());
@ -42,15 +42,9 @@ public class BucketTests extends AbstractSerializingTestCase<Bucket> {
}
bucket.setBucketInfluencers(bucketInfluencers);
}
if (randomBoolean()) {
bucket.setBucketSpan(randomPositiveLong());
}
if (randomBoolean()) {
bucket.setEventCount(randomPositiveLong());
}
if (randomBoolean()) {
bucket.setId(randomAsciiOfLengthBetween(1, 20));
}
if (randomBoolean()) {
bucket.setInitialAnomalyScore(randomDouble());
}
@ -99,9 +93,6 @@ public class BucketTests extends AbstractSerializingTestCase<Bucket> {
}
bucket.setRecords(records);
}
if (randomBoolean()) {
bucket.setTimestamp(new Date(randomLong()));
}
return bucket;
}
@ -116,22 +107,22 @@ public class BucketTests extends AbstractSerializingTestCase<Bucket> {
}
public void testEquals_GivenDifferentClass() {
Bucket bucket = new Bucket("foo");
Bucket bucket = new Bucket("foo", new Date(randomLong()), randomPositiveLong());
assertFalse(bucket.equals("a string"));
}
public void testEquals_GivenTwoDefaultBuckets() {
Bucket bucket1 = new Bucket("foo");
Bucket bucket2 = new Bucket("foo");
Bucket bucket1 = new Bucket("foo", new Date(123), 123);
Bucket bucket2 = new Bucket("foo", new Date(123), 123);
assertTrue(bucket1.equals(bucket2));
assertTrue(bucket2.equals(bucket1));
}
public void testEquals_GivenDifferentAnomalyScore() {
Bucket bucket1 = new Bucket("foo");
Bucket bucket1 = new Bucket("foo", new Date(123), 123);
bucket1.setAnomalyScore(3.0);
Bucket bucket2 = new Bucket("foo");
Bucket bucket2 = new Bucket("foo", new Date(123), 123);
bucket2.setAnomalyScore(2.0);
assertFalse(bucket1.equals(bucket2));
@ -139,17 +130,15 @@ public class BucketTests extends AbstractSerializingTestCase<Bucket> {
}
public void testEquals_GivenSameDates() {
Bucket b1 = new Bucket("foo");
b1.setTimestamp(new Date(1234567890L));
Bucket b2 = new Bucket("foo");
b2.setTimestamp(new Date(1234567890L));
Bucket b1 = new Bucket("foo", new Date(1234567890L), 123);
Bucket b2 = new Bucket("foo", new Date(1234567890L), 123);
assertTrue(b1.equals(b2));
}
public void testEquals_GivenDifferentMaxNormalizedProbability() {
Bucket bucket1 = new Bucket("foo");
Bucket bucket1 = new Bucket("foo", new Date(123), 123);
bucket1.setMaxNormalizedProbability(55.0);
Bucket bucket2 = new Bucket("foo");
Bucket bucket2 = new Bucket("foo", new Date(123), 123);
bucket2.setMaxNormalizedProbability(55.1);
assertFalse(bucket1.equals(bucket2));
@ -157,9 +146,9 @@ public class BucketTests extends AbstractSerializingTestCase<Bucket> {
}
public void testEquals_GivenDifferentEventCount() {
Bucket bucket1 = new Bucket("foo");
Bucket bucket1 = new Bucket("foo", new Date(123), 123);
bucket1.setEventCount(3);
Bucket bucket2 = new Bucket("foo");
Bucket bucket2 = new Bucket("foo", new Date(123), 123);
bucket2.setEventCount(100);
assertFalse(bucket1.equals(bucket2));
@ -167,9 +156,9 @@ public class BucketTests extends AbstractSerializingTestCase<Bucket> {
}
public void testEquals_GivenDifferentRecordCount() {
Bucket bucket1 = new Bucket("foo");
Bucket bucket1 = new Bucket("foo", new Date(123), 123);
bucket1.setRecordCount(300);
Bucket bucket2 = new Bucket("foo");
Bucket bucket2 = new Bucket("foo", new Date(123), 123);
bucket2.setRecordCount(400);
assertFalse(bucket1.equals(bucket2));
@ -177,10 +166,9 @@ public class BucketTests extends AbstractSerializingTestCase<Bucket> {
}
public void testEquals_GivenOneHasRecordsAndTheOtherDoesNot() {
Bucket bucket1 = new Bucket("foo");
bucket1.setId("1");
Bucket bucket1 = new Bucket("foo", new Date(123), 123);
bucket1.setRecords(Arrays.asList(new AnomalyRecord("foo")));
Bucket bucket2 = new Bucket("foo");
Bucket bucket2 = new Bucket("foo", new Date(123), 123);
bucket2.setRecords(null);
assertFalse(bucket1.equals(bucket2));
@ -188,9 +176,9 @@ public class BucketTests extends AbstractSerializingTestCase<Bucket> {
}
public void testEquals_GivenDifferentNumberOfRecords() {
Bucket bucket1 = new Bucket("foo");
Bucket bucket1 = new Bucket("foo", new Date(123), 123);
bucket1.setRecords(Arrays.asList(new AnomalyRecord("foo")));
Bucket bucket2 = new Bucket("foo");
Bucket bucket2 = new Bucket("foo", new Date(123), 123);
bucket2.setRecords(Arrays.asList(new AnomalyRecord("foo"), new AnomalyRecord("foo")));
assertFalse(bucket1.equals(bucket2));
@ -203,9 +191,9 @@ public class BucketTests extends AbstractSerializingTestCase<Bucket> {
AnomalyRecord anomalyRecord2 = new AnomalyRecord("foo");
anomalyRecord1.setAnomalyScore(2.0);
Bucket bucket1 = new Bucket("foo");
Bucket bucket1 = new Bucket("foo", new Date(123), 123);
bucket1.setRecords(Arrays.asList(anomalyRecord1));
Bucket bucket2 = new Bucket("foo");
Bucket bucket2 = new Bucket("foo", new Date(123), 123);
bucket2.setRecords(Arrays.asList(anomalyRecord2));
assertFalse(bucket1.equals(bucket2));
@ -213,9 +201,9 @@ public class BucketTests extends AbstractSerializingTestCase<Bucket> {
}
public void testEquals_GivenDifferentIsInterim() {
Bucket bucket1 = new Bucket("foo");
Bucket bucket1 = new Bucket("foo", new Date(123), 123);
bucket1.setInterim(true);
Bucket bucket2 = new Bucket("foo");
Bucket bucket2 = new Bucket("foo", new Date(123), 123);
bucket2.setInterim(false);
assertFalse(bucket1.equals(bucket2));
@ -223,13 +211,13 @@ public class BucketTests extends AbstractSerializingTestCase<Bucket> {
}
public void testEquals_GivenDifferentBucketInfluencers() {
Bucket bucket1 = new Bucket("foo");
Bucket bucket1 = new Bucket("foo", new Date(123), 123);
BucketInfluencer influencer1 = new BucketInfluencer("foo");
influencer1.setInfluencerFieldName("foo");
bucket1.addBucketInfluencer(influencer1);
;
Bucket bucket2 = new Bucket("foo");
Bucket bucket2 = new Bucket("foo", new Date(123), 123);
BucketInfluencer influencer2 = new BucketInfluencer("foo");
influencer2.setInfluencerFieldName("bar");
bucket2.addBucketInfluencer(influencer2);
@ -243,29 +231,25 @@ public class BucketTests extends AbstractSerializingTestCase<Bucket> {
BucketInfluencer bucketInfluencer = new BucketInfluencer("foo");
Date date = new Date();
Bucket bucket1 = new Bucket("foo");
Bucket bucket1 = new Bucket("foo", date, 123);
bucket1.setAnomalyScore(42.0);
bucket1.setInitialAnomalyScore(92.0);
bucket1.setEventCount(134);
bucket1.setId("13546461");
bucket1.setInterim(true);
bucket1.setMaxNormalizedProbability(33.3);
bucket1.setRecordCount(4);
bucket1.setRecords(Arrays.asList(record));
bucket1.addBucketInfluencer(bucketInfluencer);
bucket1.setTimestamp(date);
Bucket bucket2 = new Bucket("foo");
Bucket bucket2 = new Bucket("foo", date, 123);
bucket2.setAnomalyScore(42.0);
bucket2.setInitialAnomalyScore(92.0);
bucket2.setEventCount(134);
bucket2.setId("13546461");
bucket2.setInterim(true);
bucket2.setMaxNormalizedProbability(33.3);
bucket2.setRecordCount(4);
bucket2.setRecords(Arrays.asList(record));
bucket2.addBucketInfluencer(bucketInfluencer);
bucket2.setTimestamp(date);
assertTrue(bucket1.equals(bucket2));
assertTrue(bucket2.equals(bucket1));
@ -273,7 +257,7 @@ public class BucketTests extends AbstractSerializingTestCase<Bucket> {
}
public void testIsNormalisable_GivenNullBucketInfluencers() {
Bucket bucket = new Bucket("foo");
Bucket bucket = new Bucket("foo", new Date(123), 123);
bucket.setBucketInfluencers(null);
bucket.setAnomalyScore(90.0);
@ -281,7 +265,7 @@ public class BucketTests extends AbstractSerializingTestCase<Bucket> {
}
public void testIsNormalisable_GivenEmptyBucketInfluencers() {
Bucket bucket = new Bucket("foo");
Bucket bucket = new Bucket("foo", new Date(123), 123);
bucket.setBucketInfluencers(Collections.emptyList());
bucket.setAnomalyScore(90.0);
@ -289,7 +273,7 @@ public class BucketTests extends AbstractSerializingTestCase<Bucket> {
}
public void testIsNormalisable_GivenAnomalyScoreIsZeroAndRecordCountIsZero() {
Bucket bucket = new Bucket("foo");
Bucket bucket = new Bucket("foo", new Date(123), 123);
bucket.addBucketInfluencer(new BucketInfluencer("foo"));
bucket.setAnomalyScore(0.0);
bucket.setRecordCount(0);
@ -298,7 +282,7 @@ public class BucketTests extends AbstractSerializingTestCase<Bucket> {
}
public void testIsNormalisable_GivenAnomalyScoreIsZeroAndRecordCountIsNonZero() {
Bucket bucket = new Bucket("foo");
Bucket bucket = new Bucket("foo", new Date(123), 123);
bucket.addBucketInfluencer(new BucketInfluencer("foo"));
bucket.setAnomalyScore(0.0);
bucket.setRecordCount(1);
@ -307,7 +291,7 @@ public class BucketTests extends AbstractSerializingTestCase<Bucket> {
}
public void testIsNormalisable_GivenAnomalyScoreIsNonZeroAndRecordCountIsZero() {
Bucket bucket = new Bucket("foo");
Bucket bucket = new Bucket("foo", new Date(123), 123);
bucket.addBucketInfluencer(new BucketInfluencer("foo"));
bucket.setAnomalyScore(1.0);
bucket.setRecordCount(0);
@ -316,7 +300,7 @@ public class BucketTests extends AbstractSerializingTestCase<Bucket> {
}
public void testIsNormalisable_GivenAnomalyScoreIsNonZeroAndRecordCountIsNonZero() {
Bucket bucket = new Bucket("foo");
Bucket bucket = new Bucket("foo", new Date(123), 123);
bucket.addBucketInfluencer(new BucketInfluencer("foo"));
bucket.setAnomalyScore(1.0);
bucket.setRecordCount(1);
@ -332,7 +316,7 @@ public class BucketTests extends AbstractSerializingTestCase<Bucket> {
records.add(createAnomalyRecord("B", 15.0));
records.add(createAnomalyRecord("B", 45.0));
Bucket bucket = new Bucket("foo");
Bucket bucket = new Bucket("foo", new Date(123), 123);
bucket.setRecords(records);
Map<String, Double> ppProb = bucket.calcMaxNormalizedProbabilityPerPartition();
@ -354,7 +338,7 @@ public class BucketTests extends AbstractSerializingTestCase<Bucket> {
pScore.add(new PartitionScore("pf", "pv4", 60, 0.1));
pScore.add(new PartitionScore("pf", "pv2", 40, 0.1));
Bucket bucket = new Bucket("foo");
Bucket bucket = new Bucket("foo", new Date(123), 123);
bucket.setPartitionScores(pScore);
double anomalyScore = bucket.partitionAnomalyScore("pv1");

4
elasticsearch/src/test/resources/rest-api-spec/test/jobs_get_result_buckets.yaml
View File

@ -17,8 +17,8 @@ setup:
index:
index: prelertresults-farequote
type: result
id: 1
body: { "jobId": "farequote", "result_type": "bucket", "timestamp": "2016-06-01T00:00:00Z" }
id: "farequote_1464739200000_1"
body: { "jobId": "farequote", "result_type": "bucket", "timestamp": "2016-06-01T00:00:00Z", "bucketSpan":1 }
- do:
indices.refresh:

12
elasticsearch/src/test/resources/rest-api-spec/test/revert_model_snapshot.yaml
View File

@ -51,22 +51,22 @@ setup:
index:
index: prelertresults-foo
type: result
id: 1
body: { "jobId": "foo", "result_type": "bucket", "timestamp": "2016-06-02T00:00:00Z" }
id: "foo_1464825600000_1"
body: { "jobId": "foo", "result_type": "bucket", "timestamp": "2016-06-02T00:00:00Z", "bucketSpan":1 }
- do:
index:
index: prelertresults-foo
type: result
id: 2
body: { "jobId": "foo", "result_type": "bucket", "timestamp": "2016-06-01T12:00:00Z" }
id: "foo_1464782400000_1"
body: { "jobId": "foo", "result_type": "bucket", "timestamp": "2016-06-01T12:00:00Z", "bucketSpan":1 }
- do:
index:
index: prelertresults-foo
type: result
id: 3
body: { "jobId": "foo", "result_type": "bucket", "timestamp": "2016-05-01T00:00:00Z" }
id: "foo_1462060800000_1"
body: { "jobId": "foo", "result_type": "bucket", "timestamp": "2016-05-01T00:00:00Z", "bucketSpan":1 }
- do:
indices.refresh: