Store input fields for anomaly records and influencers (elastic/elasticsearch#799)

* Store input fields for anomaly records and influencers

* Address review comments

* Remove DotNotationReverser

* Remove duplicated constants

* Can’t use the same date for all records as they will have equivalent Ids

Original commit: elastic/x-pack-elasticsearch@40796b5efc

elasticsearch/src/main/java/org/elasticsearch/xpack/ml/job/persistence/ElasticsearchDotNotationReverser.java

@@ -1,137 +0,0 @@
-/*
- * Copyright Elasticsearch B.V. and/or licensed to Elasticsearch B.V. under one
- * or more contributor license agreements. Licensed under the Elastic License;
- * you may not use this file except in compliance with the Elastic License.
- */
-package org.elasticsearch.xpack.ml.job.persistence;
-
-import java.util.Locale;
-import java.util.Map;
-import java.util.TreeMap;
-import java.util.regex.Pattern;
-
-import org.elasticsearch.xpack.ml.job.results.ReservedFieldNames;
-
-/**
- * Interprets field names containing dots as nested JSON structures.
- * This matches what Elasticsearch does.
- */
-class ElasticsearchDotNotationReverser {
-    private static final char DOT = '.';
-    private static final Pattern DOT_PATTERN = Pattern.compile("\\.");
-
-    private final Map<String, Object> resultsMap;
-
-    public ElasticsearchDotNotationReverser() {
-        resultsMap = new TreeMap<>();
-    }
-
-    // TODO - could handle values of all types Elasticsearch does, e.g. date,
-    // long, int, double, etc.  However, at the moment field values in our
-    // results are only strings, so it's not "minimum viable product" right
-    // now.  Hence this method only takes fieldValue as a String and there are
-    // no overloads.
-
-    /**
-     * Given a field name and value, convert it to a map representation of the
-     * (potentially nested) JSON structure Elasticsearch would use to store it.
-     * For example:
-     * <code>foo = x</code> goes to <code>{ "foo" : "x" }</code> and
-     * <code>foo.bar = y</code> goes to <code>{ "foo" : { "bar" : "y" } }</code>
-     */
-    @SuppressWarnings("unchecked")
-    public void add(String fieldName, String fieldValue) {
-        if (fieldName == null || fieldValue == null) {
-            return;
-        }
-
-        // Minimise processing in the simple case of no dots in the field name.
-        if (fieldName.indexOf(DOT) == -1) {
-            if (ReservedFieldNames.RESERVED_FIELD_NAMES.contains(fieldName)) {
-                return;
-            }
-            resultsMap.put(fieldName, fieldValue);
-            return;
-        }
-
-        String[] segments = DOT_PATTERN.split(fieldName);
-
-        // If any segment created by the split is a reserved word then ignore
-        // the whole field.
-        for (String segment : segments) {
-            if (ReservedFieldNames.RESERVED_FIELD_NAMES.contains(segment)) {
-                return;
-            }
-        }
-
-        Map<String, Object> layerMap = resultsMap;
-        for (int i = 0; i < segments.length; ++i) {
-            String segment = segments[i];
-            if (i == segments.length - 1) {
-                layerMap.put(segment, fieldValue);
-            } else {
-                Object existingLayerValue = layerMap.get(segment);
-                if (existingLayerValue == null) {
-                    Map<String, Object> nextLayerMap = new TreeMap<>();
-                    layerMap.put(segment, nextLayerMap);
-                    layerMap = nextLayerMap;
-                } else {
-                    if (existingLayerValue instanceof Map) {
-                        layerMap = (Map<String, Object>) existingLayerValue;
-                    } else {
-                        // This implies an inconsistency - different additions
-                        // imply the same path leads to both an object and a
-                        // value.  For example:
-                        // foo.bar = x
-                        // foo.bar.baz = y
-                        return;
-                    }
-                }
-            }
-        }
-    }
-
-    public Map<String, Object> getResultsMap() {
-        return resultsMap;
-    }
-
-    /**
-     * Mappings for a given hierarchical structure are more complex than the
-     * basic results.
-     */
-    public Map<String, Object> getMappingsMap() {
-        Map<String, Object> mappingsMap = new TreeMap<>();
-        recurseMappingsLevel(resultsMap, mappingsMap);
-        return mappingsMap;
-    }
-
-    @SuppressWarnings("unchecked")
-    private void recurseMappingsLevel(Map<String, Object> resultsMap, Map<String, Object> mappingsMap) {
-        for (Map.Entry<String, Object> entry : resultsMap.entrySet()) {
-            Map<String, Object> typeMap = new TreeMap<>();
-
-            String name = entry.getKey();
-            Object value = entry.getValue();
-            if (value instanceof Map) {
-                Map<String, Object> propertiesMap = new TreeMap<>();
-                recurseMappingsLevel((Map<String, Object>) value, propertiesMap);
-
-                typeMap.put(ElasticsearchMappings.TYPE, ElasticsearchMappings.OBJECT);
-                typeMap.put(ElasticsearchMappings.PROPERTIES, propertiesMap);
-                mappingsMap.put(name, typeMap);
-            } else {
-                String fieldType = value.getClass().getSimpleName().toLowerCase(Locale.ROOT);
-                if ("string".equals(fieldType)) {
-                    fieldType = "keyword";
-                }
-                typeMap.put(ElasticsearchMappings.TYPE,
-                        // Even though the add() method currently only supports
-                        // strings, this way of getting the type would work for
-                        // many Elasticsearch types, e.g. date, int, long,
-                        // double and boolean
-                        fieldType);
-                mappingsMap.put(name, typeMap);
-            }
-        }
-    }
-}

elasticsearch/src/main/java/org/elasticsearch/xpack/ml/job/persistence/ElasticsearchMappings.java

@@ -12,6 +12,7 @@ import org.elasticsearch.xpack.ml.job.config.Job;
 import org.elasticsearch.xpack.ml.job.process.autodetect.state.ModelSizeStats;
 import org.elasticsearch.xpack.ml.job.process.autodetect.state.ModelSnapshot;
 import org.elasticsearch.xpack.ml.job.process.autodetect.state.ModelState;
+import org.elasticsearch.xpack.ml.job.results.ReservedFieldNames;
 import org.elasticsearch.xpack.ml.notifications.AuditActivity;
 import org.elasticsearch.xpack.ml.notifications.AuditMessage;
 import org.elasticsearch.xpack.ml.job.process.autodetect.state.Quantiles;
@@ -226,13 +227,9 @@ public class ElasticsearchMappings {
         addInfluencerFieldsToMapping(builder);
         addModelSizeStatsFieldsToMapping(builder);
 
-        if (termFieldNames != null) {
-            ElasticsearchDotNotationReverser reverser = new ElasticsearchDotNotationReverser();
         for (String fieldName : termFieldNames) {
-                reverser.add(fieldName, "");
+            if (ReservedFieldNames.isValidFieldName(fieldName)) {
-            }
+                builder.startObject(fieldName).field(TYPE, KEYWORD).endObject();
-            for (Map.Entry<String, Object> entry : reverser.getMappingsMap().entrySet()) {
-                builder.field(entry.getKey(), entry.getValue());
             }
         }
 

elasticsearch/src/main/java/org/elasticsearch/xpack/ml/job/results/AnomalyRecord.java

@@ -7,6 +7,7 @@ package org.elasticsearch.xpack.ml.job.results;
 
 import org.elasticsearch.action.support.ToXContentToBytes;
 import org.elasticsearch.common.ParseField;
+import org.elasticsearch.common.Strings;
 import org.elasticsearch.common.io.stream.StreamInput;
 import org.elasticsearch.common.io.stream.StreamOutput;
 import org.elasticsearch.common.io.stream.Writeable;
@@ -21,8 +22,12 @@ import org.elasticsearch.xpack.ml.utils.time.TimeUtils;
 import java.io.IOException;
 import java.util.ArrayList;
 import java.util.Date;
+import java.util.HashMap;
+import java.util.HashSet;
 import java.util.List;
+import java.util.Map;
 import java.util.Objects;
+import java.util.Set;
 
 /**
  * Anomaly Record POJO.
@@ -78,7 +83,8 @@ public class AnomalyRecord extends ToXContentToBytes implements Writeable {
     public static final ParseField INITIAL_NORMALIZED_PROBABILITY = new ParseField("initial_normalized_probability");
 
     public static final ConstructingObjectParser<AnomalyRecord, Void> PARSER =
-            new ConstructingObjectParser<>(RESULT_TYPE_VALUE, a -> new AnomalyRecord((String) a[0], (Date) a[1], (long) a[2], (int) a[3]));
+            new ConstructingObjectParser<>(RESULT_TYPE_VALUE, true,
+                    a -> new AnomalyRecord((String) a[0], (Date) a[1], (long) a[2], (int) a[3]));
 
     static {
         PARSER.declareString(ConstructingObjectParser.constructorArg(), Job.ID);
@@ -144,7 +150,7 @@ public class AnomalyRecord extends ToXContentToBytes implements Writeable {
     private final Date timestamp;
     private final long bucketSpan;
 
-    private List<Influence> influencers;
+    private List<Influence> influences;
 
     public AnomalyRecord(String jobId, Date timestamp, long bucketSpan, int sequenceNum) {
         this.jobId = jobId;
@@ -185,7 +191,7 @@ public class AnomalyRecord extends ToXContentToBytes implements Writeable {
         timestamp = new Date(in.readLong());
         bucketSpan = in.readLong();
         if (in.readBoolean()) {
-            influencers = in.readList(Influence::new);
+            influences = in.readList(Influence::new);
         }
     }
 
@@ -226,10 +232,10 @@ public class AnomalyRecord extends ToXContentToBytes implements Writeable {
         out.writeDouble(initialNormalizedProbability);
         out.writeLong(timestamp.getTime());
         out.writeLong(bucketSpan);
-        boolean hasInfluencers = influencers != null;
+        boolean hasInfluencers = influences != null;
         out.writeBoolean(hasInfluencers);
         if (hasInfluencers) {
-            out.writeList(influencers);
+            out.writeList(influences);
         }
     }
 
@@ -286,13 +292,45 @@ public class AnomalyRecord extends ToXContentToBytes implements Writeable {
         if (causes != null) {
             builder.field(CAUSES.getPreferredName(), causes);
         }
-        if (influencers != null) {
+        if (influences != null) {
-            builder.field(INFLUENCERS.getPreferredName(), influencers);
+            builder.field(INFLUENCERS.getPreferredName(), influences);
         }
+
+        Map<String, Set<String>> inputFields = inputFieldMap();
+        for (String fieldName : inputFields.keySet()) {
+            builder.field(fieldName, inputFields.get(fieldName));
+        }
+
         builder.endObject();
         return builder;
     }
 
+    private Map<String, Set<String>> inputFieldMap() {
+        Map<String, Set<String>> result = new HashMap<>();
+
+        addInputFieldsToMap(result, byFieldName, byFieldValue);
+        addInputFieldsToMap(result, overFieldName, overFieldValue);
+        addInputFieldsToMap(result, partitionFieldName, partitionFieldValue);
+
+        if (influences != null) {
+            for (Influence inf : influences) {
+                String fieldName = inf.getInfluencerFieldName();
+                for (String fieldValue : inf.getInfluencerFieldValues()) {
+                    addInputFieldsToMap(result, fieldName, fieldValue);
+                }
+            }
+        }
+        return result;
+    }
+
+    private void addInputFieldsToMap(Map<String, Set<String>> inputFields, String fieldName, String fieldValue) {
+        if (!Strings.isNullOrEmpty(fieldName) && fieldValue != null) {
+            if (ReservedFieldNames.isValidFieldName(fieldName)) {
+                inputFields.computeIfAbsent(fieldName, k -> new HashSet<String>()).add(fieldValue);
+            }
+        }
+    }
+
     public String getJobId() {
         return this.jobId;
     }
@@ -475,11 +513,11 @@ public class AnomalyRecord extends ToXContentToBytes implements Writeable {
     }
 
     public List<Influence> getInfluencers() {
-        return influencers;
+        return influences;
     }
 
     public void setInfluencers(List<Influence> influencers) {
-        this.influencers = influencers;
+        this.influences = influencers;
     }
 
 
@@ -489,7 +527,7 @@ public class AnomalyRecord extends ToXContentToBytes implements Writeable {
                 normalizedProbability, initialNormalizedProbability, typical, actual,
                 function, functionDescription, fieldName, byFieldName, byFieldValue, correlatedByFieldValue,
                 partitionFieldName, partitionFieldValue, overFieldName, overFieldValue,
-                timestamp, isInterim, causes, influencers, jobId);
+                timestamp, isInterim, causes, influences, jobId);
     }
 
 
@@ -528,6 +566,6 @@ public class AnomalyRecord extends ToXContentToBytes implements Writeable {
                 && Objects.equals(this.timestamp, that.timestamp)
                 && Objects.equals(this.isInterim, that.isInterim)
                 && Objects.equals(this.causes, that.causes)
-                && Objects.equals(this.influencers, that.influencers);
+                && Objects.equals(this.influences, that.influences);
     }
 }

elasticsearch/src/main/java/org/elasticsearch/xpack/ml/job/results/Influencer.java

@@ -45,7 +45,7 @@ public class Influencer extends ToXContentToBytes implements Writeable {
     public static final ParseField RESULTS_FIELD = new ParseField("influencers");
 
     public static final ConstructingObjectParser<Influencer, Void> PARSER = new ConstructingObjectParser<>(
-            RESULT_TYPE_FIELD.getPreferredName(), a -> new Influencer((String) a[0], (String) a[1], (String) a[2],
+            RESULT_TYPE_FIELD.getPreferredName(), true, a -> new Influencer((String) a[0], (String) a[1], (String) a[2],
             (Date) a[3], (long) a[4], (int) a[5]));
 
     static {
@@ -123,6 +123,9 @@ public class Influencer extends ToXContentToBytes implements Writeable {
         builder.field(Result.RESULT_TYPE.getPreferredName(), RESULT_TYPE_VALUE);
         builder.field(INFLUENCER_FIELD_NAME.getPreferredName(), influenceField);
         builder.field(INFLUENCER_FIELD_VALUE.getPreferredName(), influenceValue);
+        if (ReservedFieldNames.isValidFieldName(influenceField)) {
+            builder.field(influenceField, influenceValue);
+        }
         builder.field(ANOMALY_SCORE.getPreferredName(), anomalyScore);
         builder.field(INITIAL_ANOMALY_SCORE.getPreferredName(), initialAnomalyScore);
         builder.field(PROBABILITY.getPreferredName(), probability);

elasticsearch/src/main/java/org/elasticsearch/xpack/ml/job/results/ReservedFieldNames.java

@@ -15,6 +15,7 @@ import org.elasticsearch.xpack.ml.job.process.autodetect.state.Quantiles;
 import java.util.Arrays;
 import java.util.HashSet;
 import java.util.Set;
+import java.util.regex.Pattern;
 
 
 /**
@@ -25,15 +26,7 @@ import java.util.Set;
  * contains raw data and in others it contains some aspect of our output.
  */
 public final class ReservedFieldNames {
-    /**
+    private static final Pattern DOT_PATTERN = Pattern.compile("\\.");
-     * jobId isn't in this package, so redefine.
-     */
-    private static final String JOB_ID_NAME = Job.ID.getPreferredName();
-
-    /**
-     * @timestamp isn't in this package, so redefine.
-     */
-    private static final String ES_TIMESTAMP = "timestamp";
 
     /**
      * This array should be updated to contain all the field names that appear
@@ -45,6 +38,8 @@ public final class ReservedFieldNames {
     private static final String[] RESERVED_FIELD_NAME_ARRAY = {
             ElasticsearchMappings.ALL_FIELD_VALUES,
 
+            Job.ID.getPreferredName(),
+
             AnomalyCause.PROBABILITY.getPreferredName(),
             AnomalyCause.OVER_FIELD_NAME.getPreferredName(),
             AnomalyCause.OVER_FIELD_VALUE.getPreferredName(),
@@ -93,6 +88,7 @@ public final class ReservedFieldNames {
             Bucket.INITIAL_ANOMALY_SCORE.getPreferredName(),
             Bucket.PROCESSING_TIME_MS.getPreferredName(),
             Bucket.PARTITION_SCORES.getPreferredName(),
+            Bucket.TIMESTAMP.getPreferredName(),
 
             BucketInfluencer.INITIAL_ANOMALY_SCORE.getPreferredName(), BucketInfluencer.ANOMALY_SCORE.getPreferredName(),
             BucketInfluencer.RAW_ANOMALY_SCORE.getPreferredName(), BucketInfluencer.PROBABILITY.getPreferredName(),
@@ -151,12 +147,24 @@ public final class ReservedFieldNames {
 
             Quantiles.QUANTILE_STATE.getPreferredName(),
 
-            Result.RESULT_TYPE.getPreferredName(),
+            Result.RESULT_TYPE.getPreferredName()
-
-            JOB_ID_NAME,
-            ES_TIMESTAMP
     };
 
+    /**
+     * Test if fieldName is one of the reserved names or if it contains dots then
+     * that the segment before the first dot is not a reserved name. A fieldName
+     * containing dots represents nested fields in which case we only care about
+     * the top level.
+     *
+     * @param fieldName Document field name. This may contain dots '.'
+     * @return True if fieldName is not a reserved name or the top level segment
+     * is not a reserved name.
+     */
+    public static boolean isValidFieldName(String fieldName) {
+        String[] segments = DOT_PATTERN.split(fieldName);
+        return !RESERVED_FIELD_NAMES.contains(segments[0]);
+    }
+
     /**
      * A set of all reserved field names in our results.  Fields from the raw
      * data with these names are not added to any result.

elasticsearch/src/test/java/org/elasticsearch/xpack/ml/integration/AutodetectResultProcessorIT.java

@@ -29,13 +29,11 @@ import org.elasticsearch.xpack.ml.job.process.normalizer.Renormalizer;
 import org.elasticsearch.xpack.ml.job.process.normalizer.noop.NoOpRenormalizer;
 import org.elasticsearch.xpack.ml.job.process.autodetect.state.Quantiles;
 import org.elasticsearch.xpack.ml.job.results.AnomalyRecord;
-import org.elasticsearch.xpack.ml.job.results.AnomalyRecordTests;
 import org.elasticsearch.xpack.ml.job.results.Bucket;
 import org.elasticsearch.xpack.ml.job.results.BucketTests;
 import org.elasticsearch.xpack.ml.job.results.CategoryDefinition;
 import org.elasticsearch.xpack.ml.job.results.CategoryDefinitionTests;
 import org.elasticsearch.xpack.ml.job.results.Influencer;
-import org.elasticsearch.xpack.ml.job.results.InfluencerTests;
 import org.elasticsearch.xpack.ml.job.results.ModelDebugOutput;
 import org.elasticsearch.xpack.ml.job.results.ModelDebugOutputTests;
 import org.junit.Before;
@@ -121,7 +119,7 @@ public class AutodetectResultProcessorIT extends ESSingleNodeTestCase {
         bucket.setRecords(Collections.emptyList());
         assertEquals(bucket, persistedBucket.results().get(0));
 
-        QueryPage<AnomalyRecord> persistedRecords = getRecords(new RecordsQueryBuilder().includeInterim(true).build());
+        QueryPage<AnomalyRecord> persistedRecords = getRecords(new RecordsQueryBuilder().build());
         assertResultsAreSame(records, persistedRecords);
 
         QueryPage<Influencer> persistedInfluencers = getInfluencers();
@@ -282,9 +280,12 @@ public class AutodetectResultProcessorIT extends ESSingleNodeTestCase {
     }
 
     private void createJob() {
-        Detector detector = new Detector.Builder("avg", "metric_field").build();
+        Detector.Builder detectorBuilder = new Detector.Builder("avg", "metric_field");
+        detectorBuilder.setByFieldName("by_instance");
         Job.Builder jobBuilder = new Job.Builder(JOB_ID);
-        jobBuilder.setAnalysisConfig(new AnalysisConfig.Builder(Collections.singletonList(detector)));
+        AnalysisConfig.Builder analysisConfBuilder = new AnalysisConfig.Builder(Collections.singletonList(detectorBuilder.build()));
+        analysisConfBuilder.setInfluencers(Collections.singletonList("influence_field"));
+        jobBuilder.setAnalysisConfig(analysisConfBuilder);
 
         jobProvider.createJobResultIndex(jobBuilder.build(), new ActionListener<Boolean>() {
             @Override
@@ -307,9 +308,11 @@ public class AutodetectResultProcessorIT extends ESSingleNodeTestCase {
         List<AnomalyRecord> records = new ArrayList<>();
 
         int count = randomIntBetween(0, 100);
-        AnomalyRecordTests anomalyRecordGenerator = new AnomalyRecordTests();
+        Date now = new Date(randomNonNegativeLong());
         for (int i=0; i<count; i++) {
-            AnomalyRecord r = anomalyRecordGenerator.createTestInstance(JOB_ID, i);
+            AnomalyRecord r = new AnomalyRecord(JOB_ID, now, 3600L, i);
+            r.setByFieldName("by_instance");
+            r.setByFieldValue(randomAsciiOfLength(8));
             r.setInterim(isInterim);
             records.add(r);
         }
@@ -320,9 +323,9 @@ public class AutodetectResultProcessorIT extends ESSingleNodeTestCase {
         List<Influencer> influencers = new ArrayList<>();
 
         int count = randomIntBetween(0, 100);
-        InfluencerTests influencerGenerator = new InfluencerTests();
+        Date now = new Date();
         for (int i=0; i<count; i++) {
-            Influencer influencer = influencerGenerator.createTestInstance(JOB_ID);
+            Influencer influencer = new Influencer(JOB_ID, "influence_field", randomAsciiOfLength(10), now, 3600L, i);
             influencer.setInterim(isInterim);
             influencers.add(influencer);
         }

elasticsearch/src/test/java/org/elasticsearch/xpack/ml/job/persistence/ElasticsearchDotNotationReverserTests.java

@@ -1,55 +0,0 @@
-/*
- * Copyright Elasticsearch B.V. and/or licensed to Elasticsearch B.V. under one
- * or more contributor license agreements. Licensed under the Elastic License;
- * you may not use this file except in compliance with the Elastic License.
- */
-package org.elasticsearch.xpack.ml.job.persistence;
-
-import org.elasticsearch.common.xcontent.XContentFactory;
-import org.elasticsearch.test.ESTestCase;
-
-
-public class ElasticsearchDotNotationReverserTests extends ESTestCase {
-    public void testResultsMap() throws Exception {
-        ElasticsearchDotNotationReverser reverser = createReverser();
-
-        String expected = "{\"complex\":{\"nested\":{\"structure\":{\"first\":\"x\"," +
-                "\"second\":\"y\"},\"value\":\"z\"}},\"cpu\":{\"system\":\"5\"," +
-                "\"user\":\"10\",\"wait\":\"1\"},\"simple\":\"simon\"}";
-
-        String actual = XContentFactory.jsonBuilder().map(reverser.getResultsMap()).string();
-        assertEquals(expected, actual);
-    }
-
-    public void testMappingsMap() throws Exception {
-        ElasticsearchDotNotationReverser reverser = createReverser();
-
-        String expected = "{\"complex\":{\"properties\":{\"nested\":{\"properties\":" +
-                "{\"structure\":{\"properties\":{\"first\":{\"type\":\"keyword\"}," +
-                "\"second\":{\"type\":\"keyword\"}},\"type\":\"object\"}," +
-                "\"value\":{\"type\":\"keyword\"}},\"type\":\"object\"}}," +
-                "\"type\":\"object\"},\"cpu\":{\"properties\":{\"system\":" +
-                "{\"type\":\"keyword\"},\"user\":{\"type\":\"keyword\"}," +
-                "\"wait\":{\"type\":\"keyword\"}},\"type\":\"object\"}," +
-                "\"simple\":{\"type\":\"keyword\"}}";
-
-        String actual = XContentFactory.jsonBuilder().map(reverser.getMappingsMap()).string();
-        assertEquals(expected, actual);
-    }
-
-    private ElasticsearchDotNotationReverser createReverser() {
-        ElasticsearchDotNotationReverser reverser = new ElasticsearchDotNotationReverser();
-        // This should get ignored as it's a reserved field name
-        reverser.add("bucket_span", "3600");
-        reverser.add("simple", "simon");
-        reverser.add("cpu.user", "10");
-        reverser.add("cpu.system", "5");
-        reverser.add("cpu.wait", "1");
-        // This should get ignored as one of its segments is a reserved field name
-        reverser.add("foo.bucket_span", "3600");
-        reverser.add("complex.nested.structure.first", "x");
-        reverser.add("complex.nested.structure.second", "y");
-        reverser.add("complex.nested.value", "z");
-        return reverser;
-    }
-}

elasticsearch/src/test/java/org/elasticsearch/xpack/ml/job/persistence/ElasticsearchMappingsTests.java

@@ -6,6 +6,7 @@
 package org.elasticsearch.xpack.ml.job.persistence;
 
 import org.elasticsearch.common.xcontent.XContentBuilder;
+import org.elasticsearch.common.xcontent.XContentParser;
 import org.elasticsearch.test.ESTestCase;
 import org.elasticsearch.xpack.ml.job.process.autodetect.state.CategorizerState;
 import org.elasticsearch.xpack.ml.job.process.autodetect.state.DataCounts;
@@ -13,6 +14,7 @@ import org.elasticsearch.xpack.ml.job.config.Job;
 import org.elasticsearch.xpack.ml.job.process.autodetect.state.ModelSizeStats;
 import org.elasticsearch.xpack.ml.job.process.autodetect.state.ModelSnapshot;
 import org.elasticsearch.xpack.ml.job.process.autodetect.state.ModelState;
+import org.elasticsearch.xpack.ml.job.results.AnomalyRecord;
 import org.elasticsearch.xpack.ml.notifications.AuditActivity;
 import org.elasticsearch.xpack.ml.notifications.AuditMessage;
 import org.elasticsearch.xpack.ml.job.metadata.Allocation;
@@ -32,8 +34,10 @@ import java.io.ByteArrayInputStream;
 import java.io.IOException;
 import java.lang.reflect.InvocationTargetException;
 import java.nio.charset.StandardCharsets;
+import java.util.Arrays;
 import java.util.Collections;
 import java.util.HashSet;
+import java.util.Map;
 import java.util.Set;
 
 
@@ -169,4 +173,26 @@ public class ElasticsearchMappingsTests extends ESTestCase {
         }
     }
 
+    @SuppressWarnings("unchecked")
+    public void testResultMapping() throws IOException {
+
+        XContentBuilder builder = ElasticsearchMappings.resultsMapping(
+                Arrays.asList("instance", AnomalyRecord.ANOMALY_SCORE.getPreferredName()));
+        XContentParser parser = createParser(builder);
+        Map<String, Object> type = (Map<String, Object>) parser.map().get(Result.TYPE.getPreferredName());
+        Map<String, Object> properties = (Map<String, Object>) type.get(ElasticsearchMappings.PROPERTIES);
+
+        // check a keyword mapping for the 'instance' field was created
+        Map<String, Object> instanceMapping = (Map<String, Object>) properties.get("instance");
+        assertNotNull(instanceMapping);
+        String dataType = (String)instanceMapping.get(ElasticsearchMappings.TYPE);
+        assertEquals(ElasticsearchMappings.KEYWORD, dataType);
+
+        // check anomaly score wasn't overwritten
+        Map<String, Object> anomalyScoreMapping = (Map<String, Object>) properties.get(AnomalyRecord.ANOMALY_SCORE.getPreferredName());
+        assertNotNull(anomalyScoreMapping);
+        dataType = (String)anomalyScoreMapping.get(ElasticsearchMappings.TYPE);
+        assertEquals(ElasticsearchMappings.DOUBLE, dataType);
+    }
+
 }

elasticsearch/src/test/java/org/elasticsearch/xpack/ml/job/results/AnomalyRecordTests.java

@@ -6,13 +6,18 @@
 package org.elasticsearch.xpack.ml.job.results;
 
 import org.elasticsearch.common.io.stream.Writeable;
+import org.elasticsearch.common.xcontent.XContentBuilder;
 import org.elasticsearch.common.xcontent.XContentParser;
+import org.elasticsearch.common.xcontent.XContentType;
 import org.elasticsearch.xpack.ml.support.AbstractSerializingTestCase;
 
+import java.io.IOException;
 import java.util.ArrayList;
+import java.util.Arrays;
 import java.util.Collections;
 import java.util.Date;
 import java.util.List;
+import java.util.Map;
 
 public class AnomalyRecordTests extends AbstractSerializingTestCase<AnomalyRecord> {
 
@@ -79,4 +84,47 @@ public class AnomalyRecordTests extends AbstractSerializingTestCase<AnomalyRecor
     protected AnomalyRecord parseInstance(XContentParser parser) {
         return AnomalyRecord.PARSER.apply(parser, null);
     }
+
+    @SuppressWarnings("unchecked")
+    public void testToXContentIncludesInputFields() throws IOException {
+        AnomalyRecord record = createTestInstance();
+        record.setByFieldName("byfn");
+        record.setByFieldValue("byfv");
+        record.setOverFieldName("overfn");
+        record.setOverFieldValue("overfv");
+        record.setPartitionFieldName("partfn");
+        record.setPartitionFieldValue("partfv");
+
+        Influence influence1 = new Influence("inffn", Arrays.asList("inffv1", "inffv2"));
+        Influence influence2 = new Influence("inffn", Arrays.asList("inffv1", "inffv2"));
+        record.setInfluencers(Arrays.asList(influence1, influence2));
+
+        XContentBuilder builder = toXContent(record, XContentType.JSON);
+        XContentParser parser = createParser(builder);
+        Map<String, Object> map = parser.map();
+        List<String> serialisedByFieldValues = (List<String>) map.get(record.getByFieldName());
+        assertEquals(Collections.singletonList(record.getByFieldValue()), serialisedByFieldValues);
+        List<String> serialisedOverFieldValues = (List<String>) map.get(record.getOverFieldName());
+        assertEquals(Collections.singletonList(record.getOverFieldValue()), serialisedOverFieldValues);
+        List<String> serialisedPartFieldValues = (List<String>) map.get(record.getPartitionFieldName());
+        assertEquals(Collections.singletonList(record.getPartitionFieldValue()), serialisedPartFieldValues);
+
+        List<String> serialisedInfFieldValues1 = (List<String>) map.get(influence1.getInfluencerFieldName());
+        assertEquals(influence1.getInfluencerFieldValues(), serialisedInfFieldValues1);
+        List<String> serialisedInfFieldValues2 = (List<String>) map.get(influence2.getInfluencerFieldName());
+        assertEquals(influence2.getInfluencerFieldValues(), serialisedInfFieldValues2);
+    }
+
+    @SuppressWarnings("unchecked")
+    public void testToXContentDoesNotIncludesReservedWordInputFields() throws IOException {
+        AnomalyRecord record = createTestInstance();
+        record.setByFieldName(AnomalyRecord.BUCKET_SPAN.getPreferredName());
+        record.setByFieldValue("bar");
+
+        XContentBuilder builder = toXContent(record, XContentType.JSON);
+        XContentParser parser = createParser(builder);
+        Object value = parser.map().get(AnomalyRecord.BUCKET_SPAN.getPreferredName());
+        assertNotEquals("bar", value);
+        assertEquals((Long)record.getBucketSpan(), (Long)value);
+    }
 }

elasticsearch/src/test/java/org/elasticsearch/xpack/ml/job/results/InfluencerTests.java

@@ -6,9 +6,12 @@
 package org.elasticsearch.xpack.ml.job.results;
 
 import org.elasticsearch.common.io.stream.Writeable.Reader;
+import org.elasticsearch.common.xcontent.XContentBuilder;
 import org.elasticsearch.common.xcontent.XContentParser;
+import org.elasticsearch.common.xcontent.XContentType;
 import org.elasticsearch.xpack.ml.support.AbstractSerializingTestCase;
 
+import java.io.IOException;
 import java.util.Date;
 
 public class InfluencerTests extends AbstractSerializingTestCase<Influencer> {
@@ -37,4 +40,22 @@ public class InfluencerTests extends AbstractSerializingTestCase<Influencer> {
         return Influencer.PARSER.apply(parser, null);
     }
 
+    public void testToXContentIncludesNameValueField() throws IOException {
+        Influencer influencer = createTestInstance("foo");
+        XContentBuilder builder = toXContent(influencer, XContentType.JSON);
+        XContentParser parser = createParser(builder);
+        String serialisedFieldName = (String) parser.map().get(influencer.getInfluencerFieldName());
+        assertNotNull(serialisedFieldName);
+        assertEquals(influencer.getInfluencerFieldValue(), serialisedFieldName);
+    }
+
+    public void testToXContentDoesNotIncludeNameValueFieldWhenReservedWord() throws IOException {
+        Influencer influencer = new Influencer("foo", AnomalyRecord.ANOMALY_SCORE.getPreferredName(), "bar", new Date(), 300L, 0);
+        XContentBuilder builder = toXContent(influencer, XContentType.JSON);
+        XContentParser parser = createParser(builder);
+        Object serialisedFieldValue = parser.map().get(AnomalyRecord.ANOMALY_SCORE.getPreferredName());
+        assertNotEquals("bar", serialisedFieldValue);
+        assertEquals(0.0, (Double)serialisedFieldValue, 0.0001);
+    }
+
 }

elasticsearch/src/test/java/org/elasticsearch/xpack/ml/job/results/ReservedFieldNamesTests.java

@@ -0,0 +1,19 @@
+/*
+ * Copyright Elasticsearch B.V. and/or licensed to Elasticsearch B.V. under one
+ * or more contributor license agreements. Licensed under the Elastic License;
+ * you may not use this file except in compliance with the Elastic License.
+ */
+package org.elasticsearch.xpack.ml.job.results;
+
+import org.elasticsearch.test.ESTestCase;
+
+public class ReservedFieldNamesTests extends ESTestCase {
+
+    public void testIsValidFieldName() throws Exception {
+        assertTrue(ReservedFieldNames.isValidFieldName("host"));
+        assertTrue(ReservedFieldNames.isValidFieldName("host.actual"));
+        assertFalse(ReservedFieldNames.isValidFieldName("actual.host"));
+        assertFalse(ReservedFieldNames.isValidFieldName(AnomalyRecord.BUCKET_SPAN.getPreferredName()));
+    }
+
+}