Merge branch 'master' into integ_randomization

.gitignore

@@ -14,7 +14,7 @@ docs/html/
 docs/build.log
 /tmp/
 backwards/
-
+html_docs
 ## eclipse ignores (use 'mvn eclipse:eclipse' to build eclipse projects)
 ## All files (.project, .classpath, .settings/*) should be generated through Maven which
 ## will correctly set the classpath based on the declared dependencies and write settings 

core/src/main/java/org/apache/lucene/queries/BlendedTermQuery.java

@@ -33,6 +33,7 @@ import org.apache.lucene.search.Query;
 import org.apache.lucene.search.TermQuery;
 import org.apache.lucene.util.ArrayUtil;
 import org.apache.lucene.util.InPlaceMergeSorter;
+import org.apache.lucene.util.ToStringUtils;
 
 import java.io.IOException;
 import java.util.Arrays;
@@ -62,13 +63,17 @@ import java.util.List;
 public abstract class BlendedTermQuery extends Query {
 
     private final Term[] terms;
+    private final float[] boosts;
 
-
-    public BlendedTermQuery(Term[] terms) {
+    public BlendedTermQuery(Term[] terms, float[] boosts) {
         if (terms == null || terms.length == 0) {
             throw new IllegalArgumentException("terms must not be null or empty");
         }
+        if (boosts != null && boosts.length != terms.length) {
+            throw new IllegalArgumentException("boosts must have the same size as terms");
+        }
         this.terms = terms;
+        this.boosts = boosts;
     }
 
     @Override
@@ -231,8 +236,22 @@ public abstract class BlendedTermQuery extends Query {
 
     @Override
     public String toString(String field) {
-        return "blended(terms: " + Arrays.toString(terms) + ")";
-
+        StringBuilder builder = new StringBuilder("blended(terms:[");
+        for (int i = 0; i < terms.length; ++i) {
+            builder.append(terms[i]);
+            float boost = 1f;
+            if (boosts != null) {
+                boost = boosts[i];
+            }
+            builder.append(ToStringUtils.boost(boost));
+            builder.append(", ");
+        }
+        if (terms.length > 0) {
+            builder.setLength(builder.length() - 2);
+        }
+        builder.append("])");
+        builder.append(ToStringUtils.boost(getBoost()));
+        return builder.toString();
     }
 
     private volatile Term[] equalTerms = null;
@@ -277,7 +296,7 @@ public abstract class BlendedTermQuery extends Query {
     }
 
     public static BlendedTermQuery booleanBlendedQuery(Term[] terms, final float[] boosts, final boolean disableCoord) {
-        return new BlendedTermQuery(terms) {
+        return new BlendedTermQuery(terms, boosts) {
             @Override
             protected Query topLevelQuery(Term[] terms, TermContext[] ctx, int[] docFreqs, int maxDoc) {
                 BooleanQuery query = new BooleanQuery(disableCoord);
@@ -294,7 +313,7 @@ public abstract class BlendedTermQuery extends Query {
     }
 
     public static BlendedTermQuery commonTermsBlendedQuery(Term[] terms, final float[] boosts, final boolean disableCoord, final float maxTermFrequency) {
-        return new BlendedTermQuery(terms) {
+        return new BlendedTermQuery(terms, boosts) {
             @Override
             protected Query topLevelQuery(Term[] terms, TermContext[] ctx, int[] docFreqs, int maxDoc) {
                 BooleanQuery query = new BooleanQuery(true);
@@ -334,7 +353,7 @@ public abstract class BlendedTermQuery extends Query {
     }
 
     public static BlendedTermQuery dismaxBlendedQuery(Term[] terms, final float[] boosts, final float tieBreakerMultiplier) {
-        return new BlendedTermQuery(terms) {
+        return new BlendedTermQuery(terms, boosts) {
             @Override
             protected Query topLevelQuery(Term[] terms, TermContext[] ctx, int[] docFreqs, int maxDoc) {
                 DisjunctionMaxQuery query = new DisjunctionMaxQuery(tieBreakerMultiplier);

core/src/main/java/org/elasticsearch/action/admin/cluster/health/TransportClusterHealthAction.java

@@ -272,13 +272,13 @@ public class TransportClusterHealthAction extends TransportMasterNodeReadAction<
         } catch (IndexNotFoundException e) {
             // one of the specified indices is not there - treat it as RED.
             ClusterHealthResponse response = new ClusterHealthResponse(clusterName.value(), Strings.EMPTY_ARRAY, clusterState,
-                    numberOfPendingTasks, numberOfInFlightFetch, UnassignedInfo.getNumberOfDelayedUnassigned(settings, clusterState),
+                    numberOfPendingTasks, numberOfInFlightFetch, UnassignedInfo.getNumberOfDelayedUnassigned(System.currentTimeMillis(), settings, clusterState),
                     pendingTaskTimeInQueue);
             response.status = ClusterHealthStatus.RED;
             return response;
         }
 
         return new ClusterHealthResponse(clusterName.value(), concreteIndices, clusterState, numberOfPendingTasks,
-                numberOfInFlightFetch, UnassignedInfo.getNumberOfDelayedUnassigned(settings, clusterState), pendingTaskTimeInQueue);
+                numberOfInFlightFetch, UnassignedInfo.getNumberOfDelayedUnassigned(System.currentTimeMillis(), settings, clusterState), pendingTaskTimeInQueue);
     }
 }

core/src/main/java/org/elasticsearch/bootstrap/JVMCheck.java

@@ -59,7 +59,7 @@ final class JVMCheck {
         /** Returns an error message to the user for a broken version */
         String getErrorMessage() {
             StringBuilder sb = new StringBuilder();
-            sb.append("Java version: ").append(Constants.JAVA_VERSION);
+            sb.append("Java version: ").append(fullVersion());
             sb.append(" suffers from critical bug ").append(bugUrl);
             sb.append(" which can cause data corruption.");
             sb.append(System.lineSeparator());
@@ -111,7 +111,7 @@ final class JVMCheck {
      */
     static void check() {
         if (Boolean.parseBoolean(System.getProperty(JVM_BYPASS))) {
-            Loggers.getLogger(JVMCheck.class).warn("bypassing jvm version check for version [{}], this can result in data corruption!", Constants.JAVA_VERSION);
+            Loggers.getLogger(JVMCheck.class).warn("bypassing jvm version check for version [{}], this can result in data corruption!", fullVersion());
         } else if ("Oracle Corporation".equals(Constants.JVM_VENDOR)) {
             HotspotBug bug = JVM_BROKEN_HOTSPOT_VERSIONS.get(Constants.JVM_VERSION);
             if (bug != null) {
@@ -135,11 +135,28 @@ final class JVMCheck {
                 StringBuilder sb = new StringBuilder();
                 sb.append("IBM J9 runtimes < 2.8 suffer from several bugs which can cause data corruption.");
                 sb.append(System.lineSeparator());
-                sb.append("Your version: " + Constants.JVM_VERSION);
+                sb.append("Your version: " + fullVersion());
                 sb.append(System.lineSeparator());
                 sb.append("Please upgrade the JVM to a recent IBM JDK");
                 throw new RuntimeException(sb.toString());
             }
         }
     }
+    
+    /** 
+     * Returns java + jvm version, looks like this:
+     * {@code Oracle Corporation 1.8.0_45 [Java HotSpot(TM) 64-Bit Server VM 25.45-b02]}
+     */
+    static String fullVersion() {
+        StringBuilder sb = new StringBuilder();
+        sb.append(Constants.JAVA_VENDOR);
+        sb.append(" ");
+        sb.append(Constants.JAVA_VERSION);
+        sb.append(" [");
+        sb.append(Constants.JVM_NAME);
+        sb.append(" ");
+        sb.append(Constants.JVM_VERSION);
+        sb.append("]");
+        return sb.toString();
+    }
 }

core/src/main/java/org/elasticsearch/cluster/routing/RoutingService.java

@@ -57,6 +57,7 @@ public class RoutingService extends AbstractLifecycleComponent<RoutingService> i
     private AtomicBoolean rerouting = new AtomicBoolean();
     private volatile long registeredNextDelaySetting = Long.MAX_VALUE;
     private volatile ScheduledFuture registeredNextDelayFuture;
+    private volatile long unassignedShardsAllocatedTimestamp = 0;
 
     @Inject
     public RoutingService(Settings settings, ThreadPool threadPool, ClusterService clusterService, AllocationService allocationService) {
@@ -87,6 +88,19 @@ public class RoutingService extends AbstractLifecycleComponent<RoutingService> i
         return this.allocationService;
     }
 
+    /**
+     * Update the last time the allocator tried to assign unassigned shards
+     *
+     * This is used so that both the GatewayAllocator and RoutingService use a
+     * consistent timestamp for comparing which shards have been delayed to
+     * avoid a race condition where GatewayAllocator thinks the shard should
+     * be delayed and the RoutingService thinks it has already passed the delay
+     * and that the GatewayAllocator has/will handle it.
+     */
+    public void setUnassignedShardsAllocatedTimestamp(long timeInMillis) {
+        this.unassignedShardsAllocatedTimestamp = timeInMillis;
+    }
+
     /**
      * Initiates a reroute.
      */
@@ -108,20 +122,29 @@ public class RoutingService extends AbstractLifecycleComponent<RoutingService> i
             if (nextDelaySetting > 0 && nextDelaySetting < registeredNextDelaySetting) {
                 FutureUtils.cancel(registeredNextDelayFuture);
                 registeredNextDelaySetting = nextDelaySetting;
-                TimeValue nextDelay = TimeValue.timeValueMillis(UnassignedInfo.findNextDelayedAllocationIn(settings, event.state()));
-                logger.info("delaying allocation for [{}] unassigned shards, next check in [{}]", UnassignedInfo.getNumberOfDelayedUnassigned(settings, event.state()), nextDelay);
-                registeredNextDelayFuture = threadPool.schedule(nextDelay, ThreadPool.Names.SAME, new AbstractRunnable() {
-                    @Override
-                    protected void doRun() throws Exception {
-                        registeredNextDelaySetting = Long.MAX_VALUE;
-                        reroute("assign delayed unassigned shards");
-                    }
+                // We use System.currentTimeMillis here because we want the
+                // next delay from the "now" perspective, rather than the
+                // delay from the last time the GatewayAllocator tried to
+                // assign/delay the shard
+                TimeValue nextDelay = TimeValue.timeValueMillis(UnassignedInfo.findNextDelayedAllocationIn(System.currentTimeMillis(), settings, event.state()));
+                int unassignedDelayedShards = UnassignedInfo.getNumberOfDelayedUnassigned(unassignedShardsAllocatedTimestamp, settings, event.state());
+                if (unassignedDelayedShards > 0) {
+                    logger.info("delaying allocation for [{}] unassigned shards, next check in [{}]",
+                            unassignedDelayedShards, nextDelay);
+                    registeredNextDelayFuture = threadPool.schedule(nextDelay, ThreadPool.Names.SAME, new AbstractRunnable() {
+                        @Override
+                        protected void doRun() throws Exception {
+                            registeredNextDelaySetting = Long.MAX_VALUE;
+                            reroute("assign delayed unassigned shards");
+                        }
 
-                    @Override
-                    public void onFailure(Throwable t) {
-                        logger.warn("failed to schedule/execute reroute post unassigned shard", t);
-                    }
-                });
+                        @Override
+                        public void onFailure(Throwable t) {
+                            logger.warn("failed to schedule/execute reroute post unassigned shard", t);
+                            registeredNextDelaySetting = Long.MAX_VALUE;
+                        }
+                    });
+                }
             } else {
                 logger.trace("no need to schedule reroute due to delayed unassigned, next_delay_setting [{}], registered [{}]", nextDelaySetting, registeredNextDelaySetting);
             }

core/src/main/java/org/elasticsearch/cluster/routing/UnassignedInfo.java

@@ -199,12 +199,12 @@ public class UnassignedInfo implements ToXContent, Writeable<UnassignedInfo> {
     /**
      * The time in millisecond until this unassigned shard can be reassigned.
      */
-    public long getDelayAllocationExpirationIn(Settings settings, Settings indexSettings) {
+    public long getDelayAllocationExpirationIn(long unassignedShardsAllocatedTimestamp, Settings settings, Settings indexSettings) {
         long delayTimeout = getAllocationDelayTimeoutSetting(settings, indexSettings);
         if (delayTimeout == 0) {
             return 0;
         }
-        long delta = System.currentTimeMillis() - timestamp;
+        long delta = unassignedShardsAllocatedTimestamp - timestamp;
         // account for time drift, treat it as no timeout
         if (delta < 0) {
             return 0;
@@ -216,12 +216,12 @@ public class UnassignedInfo implements ToXContent, Writeable<UnassignedInfo> {
     /**
      * Returns the number of shards that are unassigned and currently being delayed.
      */
-    public static int getNumberOfDelayedUnassigned(Settings settings, ClusterState state) {
+    public static int getNumberOfDelayedUnassigned(long unassignedShardsAllocatedTimestamp, Settings settings, ClusterState state) {
         int count = 0;
         for (ShardRouting shard : state.routingTable().shardsWithState(ShardRoutingState.UNASSIGNED)) {
             if (shard.primary() == false) {
                 IndexMetaData indexMetaData = state.metaData().index(shard.getIndex());
-                long delay = shard.unassignedInfo().getDelayAllocationExpirationIn(settings, indexMetaData.getSettings());
+                long delay = shard.unassignedInfo().getDelayAllocationExpirationIn(unassignedShardsAllocatedTimestamp, settings, indexMetaData.getSettings());
                 if (delay > 0) {
                     count++;
                 }
@@ -251,12 +251,12 @@ public class UnassignedInfo implements ToXContent, Writeable<UnassignedInfo> {
     /**
      * Finds the next (closest) delay expiration of an unassigned shard. Returns 0 if there are none.
      */
-    public static long findNextDelayedAllocationIn(Settings settings, ClusterState state) {
+    public static long findNextDelayedAllocationIn(long unassignedShardsAllocatedTimestamp, Settings settings, ClusterState state) {
         long nextDelay = Long.MAX_VALUE;
         for (ShardRouting shard : state.routingTable().shardsWithState(ShardRoutingState.UNASSIGNED)) {
             if (shard.primary() == false) {
                 IndexMetaData indexMetaData = state.metaData().index(shard.getIndex());
-                long nextShardDelay = shard.unassignedInfo().getDelayAllocationExpirationIn(settings, indexMetaData.getSettings());
+                long nextShardDelay = shard.unassignedInfo().getDelayAllocationExpirationIn(unassignedShardsAllocatedTimestamp, settings, indexMetaData.getSettings());
                 if (nextShardDelay > 0 && nextShardDelay < nextDelay) {
                     nextDelay = nextShardDelay;
                 }

core/src/main/java/org/elasticsearch/common/lucene/search/function/ScriptScoreFunction.java

@@ -128,9 +128,7 @@ public class ScriptScoreFunction extends ScoreFunction {
 
     @Override
     public boolean needsScores() {
-        // Scripts might use _score so we return true here
-        // TODO: Make scripts able to tell us whether they use scores
-        return true;
+        return script.needsScores();
     }
 
     @Override

core/src/main/java/org/elasticsearch/gateway/GatewayAllocator.java

@@ -113,6 +113,10 @@ public class GatewayAllocator extends AbstractComponent {
     }
 
     public boolean allocateUnassigned(final RoutingAllocation allocation) {
+        // Take a snapshot of the current time and tell the RoutingService
+        // about it, so it will use a consistent timestamp for delays
+        long lastAllocateUnassignedRun = System.currentTimeMillis();
+        this.routingService.setUnassignedShardsAllocatedTimestamp(lastAllocateUnassignedRun);
         boolean changed = false;
 
         RoutingNodes.UnassignedShards unassigned = allocation.routingNodes().unassigned();
@@ -127,7 +131,7 @@ public class GatewayAllocator extends AbstractComponent {
 
         changed |= primaryShardAllocator.allocateUnassigned(allocation);
         changed |= replicaShardAllocator.processExistingRecoveries(allocation);
-        changed |= replicaShardAllocator.allocateUnassigned(allocation);
+        changed |= replicaShardAllocator.allocateUnassigned(allocation, lastAllocateUnassignedRun);
         return changed;
     }
 

core/src/main/java/org/elasticsearch/gateway/ReplicaShardAllocator.java

@@ -111,6 +111,10 @@ public abstract class ReplicaShardAllocator extends AbstractComponent {
     }
 
     public boolean allocateUnassigned(RoutingAllocation allocation) {
+        return allocateUnassigned(allocation, System.currentTimeMillis());
+    }
+
+    public boolean allocateUnassigned(RoutingAllocation allocation, long allocateUnassignedTimestapm) {
         boolean changed = false;
         final RoutingNodes routingNodes = allocation.routingNodes();
         final RoutingNodes.UnassignedShards.UnassignedIterator unassignedIterator = routingNodes.unassigned().iterator();
@@ -174,7 +178,7 @@ public abstract class ReplicaShardAllocator extends AbstractComponent {
                 //       will anyhow wait to find an existing copy of the shard to be allocated
                 // note: the other side of the equation is scheduling a reroute in a timely manner, which happens in the RoutingService
                 IndexMetaData indexMetaData = allocation.metaData().index(shard.getIndex());
-                long delay = shard.unassignedInfo().getDelayAllocationExpirationIn(settings, indexMetaData.getSettings());
+                long delay = shard.unassignedInfo().getDelayAllocationExpirationIn(allocateUnassignedTimestapm, settings, indexMetaData.getSettings());
                 if (delay > 0) {
                     logger.debug("[{}][{}]: delaying allocation of [{}] for [{}]", shard.index(), shard.id(), shard, TimeValue.timeValueMillis(delay));
                     /**

core/src/main/java/org/elasticsearch/index/get/ShardGetService.java

@@ -228,8 +228,6 @@ public final class ShardGetService extends AbstractIndexShardComponent {
                         if (source.ttl > 0) {
                             value = docMapper.TTLFieldMapper().valueForSearch(source.timestamp + source.ttl);
                         }
-                    } else if (field.equals(SizeFieldMapper.NAME) && docMapper.rootMapper(SizeFieldMapper.class).fieldType().stored()) {
-                        value = source.source.length();
                     } else {
                         if (searchLookup == null) {
                             searchLookup = new SearchLookup(mapperService, null, new String[]{type});

core/src/main/java/org/elasticsearch/index/mapper/DocumentMapper.java

@@ -48,7 +48,6 @@ import org.elasticsearch.index.mapper.internal.IdFieldMapper;
 import org.elasticsearch.index.mapper.internal.IndexFieldMapper;
 import org.elasticsearch.index.mapper.internal.ParentFieldMapper;
 import org.elasticsearch.index.mapper.internal.RoutingFieldMapper;
-import org.elasticsearch.index.mapper.internal.SizeFieldMapper;
 import org.elasticsearch.index.mapper.internal.SourceFieldMapper;
 import org.elasticsearch.index.mapper.internal.TTLFieldMapper;
 import org.elasticsearch.index.mapper.internal.TimestampFieldMapper;
@@ -106,7 +105,6 @@ public class DocumentMapper implements ToXContent {
             this.rootMappers.put(IdFieldMapper.class, new IdFieldMapper(indexSettings, mapperService.fullName(IdFieldMapper.NAME)));
             this.rootMappers.put(RoutingFieldMapper.class, new RoutingFieldMapper(indexSettings, mapperService.fullName(RoutingFieldMapper.NAME)));
             // add default mappers, order is important (for example analyzer should come before the rest to set context.analyzer)
-            this.rootMappers.put(SizeFieldMapper.class, new SizeFieldMapper(indexSettings, mapperService.fullName(SizeFieldMapper.NAME)));
             this.rootMappers.put(IndexFieldMapper.class, new IndexFieldMapper(indexSettings, mapperService.fullName(IndexFieldMapper.NAME)));
             this.rootMappers.put(SourceFieldMapper.class, new SourceFieldMapper(indexSettings));
             this.rootMappers.put(TypeFieldMapper.class, new TypeFieldMapper(indexSettings, mapperService.fullName(TypeFieldMapper.NAME)));
@@ -283,10 +281,6 @@ public class DocumentMapper implements ToXContent {
         return rootMapper(ParentFieldMapper.class);
     }
 
-    public SizeFieldMapper sizeFieldMapper() {
-        return rootMapper(SizeFieldMapper.class);
-    }
-
     public TimestampFieldMapper timestampFieldMapper() {
         return rootMapper(TimestampFieldMapper.class);
     }
@@ -299,10 +293,6 @@ public class DocumentMapper implements ToXContent {
         return rootMapper(IndexFieldMapper.class);
     }
 
-    public SizeFieldMapper SizeFieldMapper() {
-        return rootMapper(SizeFieldMapper.class);
-    }
-
     public Query typeFilter() {
         return typeMapper().fieldType().termQuery(type, null);
     }

core/src/main/java/org/elasticsearch/index/mapper/DocumentMapperParser.java

@@ -20,7 +20,9 @@
 package org.elasticsearch.index.mapper;
 
 import com.google.common.collect.ImmutableMap;
+import com.google.common.collect.ImmutableSortedMap;
 import com.google.common.collect.Maps;
+
 import org.elasticsearch.Version;
 import org.elasticsearch.common.Nullable;
 import org.elasticsearch.common.ParseFieldMatcher;
@@ -35,8 +37,6 @@ import org.elasticsearch.common.settings.Settings;
 import org.elasticsearch.common.xcontent.XContentFactory;
 import org.elasticsearch.common.xcontent.XContentHelper;
 import org.elasticsearch.common.xcontent.XContentParser;
-import org.elasticsearch.index.AbstractIndexComponent;
-import org.elasticsearch.index.Index;
 import org.elasticsearch.index.analysis.AnalysisService;
 import org.elasticsearch.index.mapper.core.*;
 import org.elasticsearch.index.mapper.geo.GeoPointFieldMapper;
@@ -50,6 +50,7 @@ import org.elasticsearch.index.similarity.SimilarityLookupService;
 import org.elasticsearch.script.Script;
 import org.elasticsearch.script.ScriptService;
 
+import java.util.Collections;
 import java.util.Iterator;
 import java.util.List;
 import java.util.Map;
@@ -73,6 +74,7 @@ public class DocumentMapperParser {
 
     private volatile ImmutableMap<String, Mapper.TypeParser> typeParsers;
     private volatile ImmutableMap<String, Mapper.TypeParser> rootTypeParsers;
+    private volatile ImmutableMap<String, Mapper.TypeParser> additionalRootMappers;
 
     public DocumentMapperParser(@IndexSettings Settings indexSettings, MapperService mapperService, AnalysisService analysisService,
                                 SimilarityLookupService similarityLookupService, ScriptService scriptService) {
@@ -109,7 +111,6 @@ public class DocumentMapperParser {
         typeParsers = typeParsersBuilder.immutableMap();
 
         rootTypeParsers = new MapBuilder<String, Mapper.TypeParser>()
-                .put(SizeFieldMapper.NAME, new SizeFieldMapper.TypeParser())
                 .put(IndexFieldMapper.NAME, new IndexFieldMapper.TypeParser())
                 .put(SourceFieldMapper.NAME, new SourceFieldMapper.TypeParser())
                 .put(TypeFieldMapper.NAME, new TypeFieldMapper.TypeParser())
@@ -123,6 +124,7 @@ public class DocumentMapperParser {
                 .put(IdFieldMapper.NAME, new IdFieldMapper.TypeParser())
                 .put(FieldNamesFieldMapper.NAME, new FieldNamesFieldMapper.TypeParser())
                 .immutableMap();
+        additionalRootMappers = ImmutableSortedMap.<String, Mapper.TypeParser>of();
         indexVersionCreated = Version.indexCreated(indexSettings);
     }
 
@@ -139,6 +141,10 @@ public class DocumentMapperParser {
             rootTypeParsers = new MapBuilder<>(rootTypeParsers)
                     .put(type, typeParser)
                     .immutableMap();
+            additionalRootMappers = ImmutableSortedMap.<String, Mapper.TypeParser>naturalOrder()
+                    .putAll(additionalRootMappers)
+                    .put(type, typeParser)
+                    .build();
         }
     }
 
@@ -204,6 +210,10 @@ public class DocumentMapperParser {
         Mapper.TypeParser.ParserContext parserContext = parserContext();
         // parse RootObjectMapper
         DocumentMapper.Builder docBuilder = doc(indexSettings, (RootObjectMapper.Builder) rootObjectTypeParser.parse(type, mapping, parserContext), mapperService);
+        // Add default mapping for the plugged-in meta mappers
+        for (Map.Entry<String, Mapper.TypeParser> entry : additionalRootMappers.entrySet()) {
+            docBuilder.put((MetadataFieldMapper.Builder<?, ?>) entry.getValue().parse(entry.getKey(), Collections.<String, Object>emptyMap(), parserContext));
+        }
         Iterator<Map.Entry<String, Object>> iterator = mapping.entrySet().iterator();
         // parse DocumentMapper
         while(iterator.hasNext()) {

core/src/main/java/org/elasticsearch/index/query/QueryParseContext.java

@@ -182,7 +182,9 @@ public class QueryParseContext {
     }
 
     public void addNamedQuery(String name, Query query) {
-        namedQueries.put(name, query);
+        if (query != null) {
+            namedQueries.put(name, query);
+        }
     }
 
     public ImmutableMap<String, Query> copyNamedQueries() {

core/src/main/java/org/elasticsearch/index/search/MultiMatchQuery.java

@@ -85,7 +85,7 @@ public class MultiMatchQuery extends MatchQuery {
                 throw new IllegalStateException("No such type: " + type);
         }
         final List<? extends Query> queries = queryBuilder.buildGroupedQueries(type, fieldNames, value, minimumShouldMatch);
-        return queryBuilder.conbineGrouped(queries);
+        return queryBuilder.combineGrouped(queries);
     }
 
     private QueryBuilder queryBuilder;
@@ -119,7 +119,7 @@ public class MultiMatchQuery extends MatchQuery {
             return parseAndApply(type, field, value, minimumShouldMatch, boostValue);
         }
 
-        public Query conbineGrouped(List<? extends Query> groupQuery) {
+        public Query combineGrouped(List<? extends Query> groupQuery) {
             if (groupQuery == null || groupQuery.isEmpty()) {
                 return null;
             }
@@ -196,7 +196,7 @@ public class MultiMatchQuery extends MatchQuery {
                     blendedFields = null;
                 }
                 final FieldAndFieldType fieldAndFieldType = group.get(0);
-                Query q = parseGroup(type.matchQueryType(), fieldAndFieldType.field, fieldAndFieldType.boost, value, minimumShouldMatch);
+                Query q = parseGroup(type.matchQueryType(), fieldAndFieldType.field, 1f, value, minimumShouldMatch);
                 if (q != null) {
                     queries.add(q);
                 }

core/src/main/java/org/elasticsearch/script/NativeScriptEngineService.java

@@ -86,6 +86,10 @@ public class NativeScriptEngineService extends AbstractComponent implements Scri
                 script.setLookup(lookup.getLeafSearchLookup(context));
                 return script;
             }
+            @Override
+            public boolean needsScores() {
+                return scriptFactory.needsScores();
+            }
         };
     }
 

core/src/main/java/org/elasticsearch/script/NativeScriptFactory.java

@@ -41,4 +41,11 @@ public interface NativeScriptFactory {
      * @param params The parameters passed to the script. Can be <tt>null</tt>.
      */
     ExecutableScript newScript(@Nullable Map<String, Object> params);
+
+    /**
+     * Indicates if document scores may be needed by the produced scripts.
+     * 
+     * @return {@code true} if scores are needed.
+     */
+    boolean needsScores();
 }

core/src/main/java/org/elasticsearch/script/SearchScript.java

@@ -29,4 +29,11 @@ public interface SearchScript {
 
     LeafSearchScript getLeafSearchScript(LeafReaderContext context) throws IOException;
 
+    /**
+     * Indicates if document scores may be needed by this {@link SearchScript}.
+     * 
+     * @return {@code true} if scores are needed.
+     */
+    boolean needsScores();
+
 }

core/src/main/java/org/elasticsearch/script/expression/ExpressionScriptEngineService.java

@@ -112,7 +112,6 @@ public class ExpressionScriptEngineService extends AbstractComponent implements
             for (String variable : expr.variables) {
                 if (variable.equals("_score")) {
                     bindings.add(new SortField("_score", SortField.Type.SCORE));
-
                 } else if (variable.equals("_value")) {
                     specialValue = new ReplaceableConstValueSource();
                     bindings.add("_value", specialValue);
@@ -173,7 +172,8 @@ public class ExpressionScriptEngineService extends AbstractComponent implements
                 }
             }
 
-            return new ExpressionSearchScript(compiledScript, bindings, specialValue);
+            final boolean needsScores = expr.getSortField(bindings, false).needsScores();
+            return new ExpressionSearchScript(compiledScript, bindings, specialValue, needsScores);
         } catch (Exception exception) {
             throw new ScriptException("Error during search with " + compiledScript, exception);
         }

core/src/main/java/org/elasticsearch/script/expression/ExpressionSearchScript.java

@@ -46,14 +46,21 @@ class ExpressionSearchScript implements SearchScript {
     final SimpleBindings bindings;
     final ValueSource source;
     final ReplaceableConstValueSource specialValue; // _value
+    final boolean needsScores;
     Scorer scorer;
     int docid;
 
-    ExpressionSearchScript(CompiledScript c, SimpleBindings b, ReplaceableConstValueSource v) {
+    ExpressionSearchScript(CompiledScript c, SimpleBindings b, ReplaceableConstValueSource v, boolean needsScores) {
         compiledScript = c;
         bindings = b;
         source = ((Expression)compiledScript.compiled()).getValueSource(bindings);
         specialValue = v;
+        this.needsScores = needsScores;
+    }
+
+    @Override
+    public boolean needsScores() {
+        return needsScores;
     }
 
     @Override

core/src/main/java/org/elasticsearch/script/groovy/GroovyScriptEngineService.java

@@ -168,6 +168,12 @@ public class GroovyScriptEngineService extends AbstractComponent implements Scri
                 }
                 return new GroovyScript(compiledScript, scriptObject, leafLookup, logger);
             }
+
+            @Override
+            public boolean needsScores() {
+                // TODO: can we reliably know if a groovy script makes use of _score
+                return true;
+            }
         };
     }
 

core/src/main/java/org/elasticsearch/search/aggregations/support/ValuesSource.java

@@ -216,8 +216,7 @@ public abstract class ValuesSource {
 
             @Override
             public boolean needsScores() {
-                // TODO: add a way to know whether scripts are using scores
-                return true;
+                return script.needsScores();
             }
         }
 
@@ -295,8 +294,7 @@ public abstract class ValuesSource {
 
             @Override
             public boolean needsScores() {
-                // TODO: add a way to know whether scripts are using scores
-                return true;
+                return script.needsScores();
             }
 
             @Override
@@ -431,8 +429,7 @@ public abstract class ValuesSource {
 
             @Override
             public boolean needsScores() {
-                // TODO: add a way to know whether scripts are using scores
-                return true;
+                return script.needsScores();
             }
         }
 
@@ -451,8 +448,7 @@ public abstract class ValuesSource {
 
         @Override
         public boolean needsScores() {
-            // TODO: add a way to know whether scripts are using scores
-            return true;
+            return script.needsScores();
         }
 
         @Override

core/src/test/java/org/elasticsearch/benchmark/scripts/expression/NativeScript1.java

@@ -34,6 +34,11 @@ public class NativeScript1 extends AbstractSearchScript {
         public ExecutableScript newScript(@Nullable Map<String, Object> params) {
             return new NativeScript1();
         }
+
+        @Override
+        public boolean needsScores() {
+            return false;
+        }
     }
 
     public static final String NATIVE_SCRIPT_1 = "native_1";

core/src/test/java/org/elasticsearch/benchmark/scripts/expression/NativeScript2.java

@@ -34,6 +34,11 @@ public class NativeScript2 extends AbstractSearchScript {
         public ExecutableScript newScript(@Nullable Map<String, Object> params) {
             return new NativeScript2();
         }
+
+        @Override
+        public boolean needsScores() {
+            return false;
+        }
     }
 
     public static final String NATIVE_SCRIPT_2 = "native_2";

core/src/test/java/org/elasticsearch/benchmark/scripts/expression/NativeScript3.java

@@ -34,6 +34,11 @@ public class NativeScript3 extends AbstractSearchScript {
         public ExecutableScript newScript(@Nullable Map<String, Object> params) {
             return new NativeScript3();
         }
+
+        @Override
+        public boolean needsScores() {
+            return false;
+        }
     }
 
     public static final String NATIVE_SCRIPT_3 = "native_3";

core/src/test/java/org/elasticsearch/benchmark/scripts/expression/NativeScript4.java

@@ -34,6 +34,11 @@ public class NativeScript4 extends AbstractSearchScript {
         public ExecutableScript newScript(@Nullable Map<String, Object> params) {
             return new NativeScript4();
         }
+
+        @Override
+        public boolean needsScores() {
+            return false;
+        }
     }
 
     public static final String NATIVE_SCRIPT_4 = "native_4";

core/src/test/java/org/elasticsearch/benchmark/scripts/score/script/NativeConstantForLoopScoreScript.java

@@ -36,6 +36,11 @@ public class NativeConstantForLoopScoreScript extends AbstractSearchScript {
         public ExecutableScript newScript(@Nullable Map<String, Object> params) {
             return new NativeConstantForLoopScoreScript(params);
         }
+
+        @Override
+        public boolean needsScores() {
+            return false;
+        }
     }
 
     private NativeConstantForLoopScoreScript(Map<String, Object> params) {

core/src/test/java/org/elasticsearch/benchmark/scripts/score/script/NativeConstantScoreScript.java

@@ -36,6 +36,11 @@ public class NativeConstantScoreScript extends AbstractSearchScript {
         public ExecutableScript newScript(@Nullable Map<String, Object> params) {
             return new NativeConstantScoreScript();
         }
+
+        @Override
+        public boolean needsScores() {
+            return false;
+        }
     }
 
     private NativeConstantScoreScript() {

core/src/test/java/org/elasticsearch/benchmark/scripts/score/script/NativeNaiveTFIDFScoreScript.java

@@ -42,6 +42,11 @@ public class NativeNaiveTFIDFScoreScript extends AbstractSearchScript {
         public ExecutableScript newScript(@Nullable Map<String, Object> params) {
             return new NativeNaiveTFIDFScoreScript(params);
         }
+
+        @Override
+        public boolean needsScores() {
+            return false;
+        }
     }
 
     private NativeNaiveTFIDFScoreScript(Map<String, Object> params) {

core/src/test/java/org/elasticsearch/benchmark/scripts/score/script/NativePayloadSumNoRecordScoreScript.java

@@ -44,6 +44,11 @@ public class NativePayloadSumNoRecordScoreScript extends AbstractSearchScript {
         public ExecutableScript newScript(@Nullable Map<String, Object> params) {
             return new NativePayloadSumNoRecordScoreScript(params);
         }
+
+        @Override
+        public boolean needsScores() {
+            return false;
+        }
     }
 
     private NativePayloadSumNoRecordScoreScript(Map<String, Object> params) {

core/src/test/java/org/elasticsearch/benchmark/scripts/score/script/NativePayloadSumScoreScript.java

@@ -44,6 +44,11 @@ public class NativePayloadSumScoreScript extends AbstractSearchScript {
         public ExecutableScript newScript(@Nullable Map<String, Object> params) {
             return new NativePayloadSumScoreScript(params);
         }
+
+        @Override
+        public boolean needsScores() {
+            return false;
+        }
     }
 
     private NativePayloadSumScoreScript(Map<String, Object> params) {

core/src/test/java/org/elasticsearch/cluster/allocation/ClusterRerouteIT.java

@@ -34,15 +34,18 @@ import org.elasticsearch.cluster.routing.allocation.command.MoveAllocationComman
 import org.elasticsearch.cluster.routing.allocation.decider.Decision;
 import org.elasticsearch.cluster.routing.allocation.decider.DisableAllocationDecider;
 import org.elasticsearch.cluster.routing.allocation.decider.EnableAllocationDecider.Allocation;
+import org.elasticsearch.cluster.routing.allocation.decider.ThrottlingAllocationDecider;
 import org.elasticsearch.common.Priority;
 import org.elasticsearch.common.io.FileSystemUtils;
 import org.elasticsearch.common.logging.ESLogger;
 import org.elasticsearch.common.logging.Loggers;
 import org.elasticsearch.common.settings.Settings;
+import org.elasticsearch.common.unit.TimeValue;
 import org.elasticsearch.env.NodeEnvironment;
 import org.elasticsearch.index.shard.ShardId;
 import org.elasticsearch.test.ESIntegTestCase;
 import org.elasticsearch.test.ESIntegTestCase.ClusterScope;
+import org.elasticsearch.test.InternalTestCluster;
 import org.junit.Test;
 
 import java.nio.file.Path;
@@ -160,6 +163,40 @@ public class ClusterRerouteIT extends ESIntegTestCase {
         rerouteWithAllocateLocalGateway(commonSettings);
     }
 
+    @Test
+    public void testDelayWithALargeAmountOfShards() throws Exception {
+        Settings commonSettings = settingsBuilder()
+                .put("gateway.type", "local")
+                .put(ThrottlingAllocationDecider.CLUSTER_ROUTING_ALLOCATION_CONCURRENT_RECOVERIES, 1)
+                .build();
+        logger.info("--> starting 4 nodes");
+        String node_1 = internalCluster().startNode(commonSettings);
+        internalCluster().startNode(commonSettings);
+        internalCluster().startNode(commonSettings);
+        internalCluster().startNode(commonSettings);
+
+        assertThat(cluster().size(), equalTo(4));
+        ClusterHealthResponse healthResponse = client().admin().cluster().prepareHealth().setWaitForNodes("4").execute().actionGet();
+        assertThat(healthResponse.isTimedOut(), equalTo(false));
+
+        logger.info("--> create indices");
+        for (int i = 0; i < 25; i++) {
+            client().admin().indices().prepareCreate("test" + i)
+                    .setSettings(settingsBuilder()
+                            .put("index.number_of_shards", 5).put("index.number_of_replicas", 1)
+                            .put("index.unassigned.node_left.delayed_timeout", randomIntBetween(250, 1000) + "ms"))
+                    .execute().actionGet();
+        }
+
+        ensureGreen(TimeValue.timeValueMinutes(1));
+
+        logger.info("--> stopping node1");
+        internalCluster().stopRandomNode(InternalTestCluster.nameFilter(node_1));
+
+        // This might run slowly on older hardware
+        ensureGreen(TimeValue.timeValueMinutes(2));
+    }
+
     private void rerouteWithAllocateLocalGateway(Settings commonSettings) throws Exception {
         logger.info("--> starting 2 nodes");
         String node_1 = internalCluster().startNode(commonSettings);

core/src/test/java/org/elasticsearch/cluster/routing/RoutingServiceTests.java

@@ -28,6 +28,7 @@ import org.elasticsearch.cluster.metadata.MetaData;
 import org.elasticsearch.cluster.node.DiscoveryNodes;
 import org.elasticsearch.cluster.routing.allocation.AllocationService;
 import org.elasticsearch.common.settings.Settings;
+import org.elasticsearch.common.unit.TimeValue;
 import org.elasticsearch.test.ESAllocationTestCase;
 import org.elasticsearch.threadpool.ThreadPool;
 import org.junit.After;
@@ -112,6 +113,10 @@ public class RoutingServiceTests extends ESAllocationTestCase {
         ClusterState prevState = clusterState;
         clusterState = ClusterState.builder(clusterState).nodes(DiscoveryNodes.builder(clusterState.nodes()).remove("node2")).build();
         clusterState = ClusterState.builder(clusterState).routingResult(allocation.reroute(clusterState)).build();
+        // We need to update the routing service's last attempted run to
+        // signal that the GatewayAllocator tried to allocated it but
+        // it was delayed
+        routingService.setUnassignedShardsAllocatedTimestamp(System.currentTimeMillis());
         ClusterState newState = clusterState;
 
         routingService.clusterChanged(new ClusterChangedEvent("test", newState, prevState));
@@ -125,6 +130,44 @@ public class RoutingServiceTests extends ESAllocationTestCase {
         assertThat(routingService.getRegisteredNextDelaySetting(), equalTo(Long.MAX_VALUE));
     }
 
+    @Test
+    public void testDelayedUnassignedDoesNotRerouteForNegativeDelays() throws Exception {
+        AllocationService allocation = createAllocationService();
+        MetaData metaData = MetaData.builder()
+                .put(IndexMetaData.builder("test").settings(settings(Version.CURRENT).put(UnassignedInfo.INDEX_DELAYED_NODE_LEFT_TIMEOUT_SETTING, "100ms"))
+                        .numberOfShards(1).numberOfReplicas(1))
+                .build();
+        ClusterState clusterState = ClusterState.builder(ClusterName.DEFAULT)
+                .metaData(metaData)
+                .routingTable(RoutingTable.builder().addAsNew(metaData.index("test"))).build();
+        clusterState = ClusterState.builder(clusterState).nodes(DiscoveryNodes.builder().put(newNode("node1")).put(newNode("node2")).localNodeId("node1").masterNodeId("node1")).build();
+        clusterState = ClusterState.builder(clusterState).routingResult(allocation.reroute(clusterState)).build();
+        // starting primaries
+        clusterState = ClusterState.builder(clusterState).routingResult(allocation.applyStartedShards(clusterState, clusterState.routingNodes().shardsWithState(INITIALIZING))).build();
+        // starting replicas
+        clusterState = ClusterState.builder(clusterState).routingResult(allocation.applyStartedShards(clusterState, clusterState.routingNodes().shardsWithState(INITIALIZING))).build();
+        assertThat(clusterState.routingNodes().hasUnassigned(), equalTo(false));
+        // remove node2 and reroute
+        ClusterState prevState = clusterState;
+        clusterState = ClusterState.builder(clusterState).nodes(DiscoveryNodes.builder(clusterState.nodes()).remove("node2")).build();
+        clusterState = ClusterState.builder(clusterState).routingResult(allocation.reroute(clusterState)).build();
+        // Set it in the future so the delay will be negative
+        routingService.setUnassignedShardsAllocatedTimestamp(System.currentTimeMillis() + TimeValue.timeValueMinutes(1).millis());
+
+        ClusterState newState = clusterState;
+
+        routingService.clusterChanged(new ClusterChangedEvent("test", newState, prevState));
+        assertBusy(new Runnable() {
+            @Override
+            public void run() {
+                assertThat(routingService.hasReroutedAndClear(), equalTo(false));
+
+                // verify the registration has been updated
+                assertThat(routingService.getRegisteredNextDelaySetting(), equalTo(100L));
+            }
+        });
+    }
+
     private class TestRoutingService extends RoutingService {
 
         private AtomicBoolean rerouted = new AtomicBoolean();

core/src/test/java/org/elasticsearch/cluster/routing/UnassignedInfoTests.java

@@ -273,7 +273,8 @@ public class UnassignedInfoTests extends ESAllocationTestCase {
         assertBusy(new Runnable() {
             @Override
             public void run() {
-                long delay = unassignedInfo.getDelayAllocationExpirationIn(Settings.builder().put(UnassignedInfo.INDEX_DELAYED_NODE_LEFT_TIMEOUT_SETTING, "10h").build(), Settings.EMPTY);
+                long delay = unassignedInfo.getDelayAllocationExpirationIn(System.currentTimeMillis(),
+                        Settings.builder().put(UnassignedInfo.INDEX_DELAYED_NODE_LEFT_TIMEOUT_SETTING, "10h").build(), Settings.EMPTY);
                 assertThat(delay, greaterThan(0l));
                 assertThat(delay, lessThan(TimeValue.timeValueHours(10).millis()));
             }
@@ -290,7 +291,8 @@ public class UnassignedInfoTests extends ESAllocationTestCase {
         UnassignedInfo unassignedInfo = new UnassignedInfo(RandomPicks.randomFrom(getRandom(), reasons), null);
         long delay = unassignedInfo.getAllocationDelayTimeoutSetting(Settings.builder().put(UnassignedInfo.INDEX_DELAYED_NODE_LEFT_TIMEOUT_SETTING, "10h").build(), Settings.EMPTY);
         assertThat(delay, equalTo(0l));
-        delay = unassignedInfo.getDelayAllocationExpirationIn(Settings.builder().put(UnassignedInfo.INDEX_DELAYED_NODE_LEFT_TIMEOUT_SETTING, "10h").build(), Settings.EMPTY);
+        delay = unassignedInfo.getDelayAllocationExpirationIn(System.currentTimeMillis(),
+                Settings.builder().put(UnassignedInfo.INDEX_DELAYED_NODE_LEFT_TIMEOUT_SETTING, "10h").build(), Settings.EMPTY);
         assertThat(delay, equalTo(0l));
     }
 
@@ -306,7 +308,8 @@ public class UnassignedInfoTests extends ESAllocationTestCase {
                 .routingTable(RoutingTable.builder().addAsNew(metaData.index("test1")).addAsNew(metaData.index("test2"))).build();
         clusterState = ClusterState.builder(clusterState).nodes(DiscoveryNodes.builder().put(newNode("node1")).put(newNode("node2"))).build();
         clusterState = ClusterState.builder(clusterState).routingResult(allocation.reroute(clusterState)).build();
-        assertThat(UnassignedInfo.getNumberOfDelayedUnassigned(Settings.builder().put(UnassignedInfo.INDEX_DELAYED_NODE_LEFT_TIMEOUT_SETTING, "10h").build(), clusterState), equalTo(0));
+        assertThat(UnassignedInfo.getNumberOfDelayedUnassigned(System.currentTimeMillis(),
+                Settings.builder().put(UnassignedInfo.INDEX_DELAYED_NODE_LEFT_TIMEOUT_SETTING, "10h").build(), clusterState), equalTo(0));
         // starting primaries
         clusterState = ClusterState.builder(clusterState).routingResult(allocation.applyStartedShards(clusterState, clusterState.routingNodes().shardsWithState(INITIALIZING))).build();
         // starting replicas
@@ -315,7 +318,8 @@ public class UnassignedInfoTests extends ESAllocationTestCase {
         // remove node2 and reroute
         clusterState = ClusterState.builder(clusterState).nodes(DiscoveryNodes.builder(clusterState.nodes()).remove("node2")).build();
         clusterState = ClusterState.builder(clusterState).routingResult(allocation.reroute(clusterState)).build();
-        assertThat(clusterState.prettyPrint(), UnassignedInfo.getNumberOfDelayedUnassigned(Settings.builder().put(UnassignedInfo.INDEX_DELAYED_NODE_LEFT_TIMEOUT_SETTING, "10h").build(), clusterState), equalTo(2));
+        assertThat(clusterState.prettyPrint(), UnassignedInfo.getNumberOfDelayedUnassigned(System.currentTimeMillis(),
+                Settings.builder().put(UnassignedInfo.INDEX_DELAYED_NODE_LEFT_TIMEOUT_SETTING, "10h").build(), clusterState), equalTo(2));
     }
 
     @Test
@@ -330,7 +334,8 @@ public class UnassignedInfoTests extends ESAllocationTestCase {
                 .routingTable(RoutingTable.builder().addAsNew(metaData.index("test1")).addAsNew(metaData.index("test2"))).build();
         clusterState = ClusterState.builder(clusterState).nodes(DiscoveryNodes.builder().put(newNode("node1")).put(newNode("node2"))).build();
         clusterState = ClusterState.builder(clusterState).routingResult(allocation.reroute(clusterState)).build();
-        assertThat(UnassignedInfo.getNumberOfDelayedUnassigned(Settings.builder().put(UnassignedInfo.INDEX_DELAYED_NODE_LEFT_TIMEOUT_SETTING, "10h").build(), clusterState), equalTo(0));
+        assertThat(UnassignedInfo.getNumberOfDelayedUnassigned(System.currentTimeMillis(),
+                Settings.builder().put(UnassignedInfo.INDEX_DELAYED_NODE_LEFT_TIMEOUT_SETTING, "10h").build(), clusterState), equalTo(0));
         // starting primaries
         clusterState = ClusterState.builder(clusterState).routingResult(allocation.applyStartedShards(clusterState, clusterState.routingNodes().shardsWithState(INITIALIZING))).build();
         // starting replicas
@@ -343,7 +348,8 @@ public class UnassignedInfoTests extends ESAllocationTestCase {
         long nextDelaySetting = UnassignedInfo.findSmallestDelayedAllocationSetting(Settings.builder().put(UnassignedInfo.INDEX_DELAYED_NODE_LEFT_TIMEOUT_SETTING, "10h").build(), clusterState);
         assertThat(nextDelaySetting, equalTo(TimeValue.timeValueHours(10).millis()));
 
-        long nextDelay = UnassignedInfo.findNextDelayedAllocationIn(Settings.builder().put(UnassignedInfo.INDEX_DELAYED_NODE_LEFT_TIMEOUT_SETTING, "10h").build(), clusterState);
+        long nextDelay = UnassignedInfo.findNextDelayedAllocationIn(System.currentTimeMillis(),
+                Settings.builder().put(UnassignedInfo.INDEX_DELAYED_NODE_LEFT_TIMEOUT_SETTING, "10h").build(), clusterState);
         assertThat(nextDelay, greaterThan(TimeValue.timeValueHours(9).millis()));
         assertThat(nextDelay, lessThanOrEqualTo(TimeValue.timeValueHours(10).millis()));
     }

core/src/test/java/org/elasticsearch/common/lucene/search/function/ScriptScoreFunctionTests.java

@@ -73,5 +73,10 @@ public class ScriptScoreFunctionTests extends ESTestCase {
                 }
             };
         }
+
+        @Override
+        public boolean needsScores() {
+            return false;
+        }
     }
 }

core/src/test/java/org/elasticsearch/get/GetActionIT.java

@@ -1031,9 +1031,6 @@ public class GetActionIT extends ESIntegTestCase {
             "    \"doc\": {\n" +
             "      \"_timestamp\": {\n" +
             "        \"enabled\": true\n" +
-            "      },\n" +
-            "      \"_size\": {\n" +
-            "        \"enabled\": true\n" +
             "      }\n" +
             "    }\n" +
             "  }\n" +
@@ -1045,7 +1042,7 @@ public class GetActionIT extends ESIntegTestCase {
             "  \"text\": \"some text.\"\n" +
             "}\n";
         client().prepareIndex("test", "doc").setId("1").setSource(doc).setRouting("1").get();
-        String[] fieldsList = {"_timestamp", "_size", "_routing"};
+        String[] fieldsList = {"_timestamp", "_routing"};
         // before refresh - document is only in translog
         assertGetFieldsAlwaysWorks(indexOrAlias(), "doc", "1", fieldsList, "1");
         refresh();

core/src/test/java/org/elasticsearch/index/mapper/all/SimpleAllMapperTests.java

@@ -44,8 +44,8 @@ import org.elasticsearch.index.mapper.MapperParsingException;
 import org.elasticsearch.index.mapper.ParseContext.Document;
 import org.elasticsearch.index.mapper.ParsedDocument;
 import org.elasticsearch.index.mapper.internal.AllFieldMapper;
-import org.elasticsearch.index.mapper.internal.SizeFieldMapper;
 import org.elasticsearch.test.ESSingleNodeTestCase;
+import org.elasticsearch.index.mapper.internal.TimestampFieldMapper;
 import org.hamcrest.Matchers;
 import org.junit.Test;
 
@@ -387,7 +387,7 @@ public class SimpleAllMapperTests extends ESSingleNodeTestCase {
         String mapping = "{";
         Map<String, String> rootTypes = new HashMap<>();
         //just pick some example from DocumentMapperParser.rootTypeParsers
-        rootTypes.put(SizeFieldMapper.NAME, "{\"enabled\" : true}");
+        rootTypes.put(TimestampFieldMapper.NAME, "{\"enabled\" : true}");
         rootTypes.put("include_in_all", "true");
         rootTypes.put("dynamic_date_formats", "[\"yyyy-MM-dd\", \"dd-MM-yyyy\"]");
         rootTypes.put("numeric_detection", "true");

core/src/test/java/org/elasticsearch/index/mapper/typelevels/ParseMappingTypeLevelTests.java

@@ -33,16 +33,16 @@ public class ParseMappingTypeLevelTests extends ESSingleNodeTestCase {
     @Test
     public void testTypeLevel() throws Exception {
         String mapping = XContentFactory.jsonBuilder().startObject().startObject("type")
-                .startObject("_size").field("enabled", true).endObject()
+                .startObject("_timestamp").field("enabled", true).endObject()
                 .endObject().endObject().string();
 
         DocumentMapperParser parser = createIndex("test").mapperService().documentMapperParser();
         DocumentMapper mapper = parser.parse("type", mapping);
         assertThat(mapper.type(), equalTo("type"));
-        assertThat(mapper.sizeFieldMapper().enabled(), equalTo(true));
+        assertThat(mapper.timestampFieldMapper().enabled(), equalTo(true));
 
         mapper = parser.parse(mapping);
         assertThat(mapper.type(), equalTo("type"));
-        assertThat(mapper.sizeFieldMapper().enabled(), equalTo(true));
+        assertThat(mapper.timestampFieldMapper().enabled(), equalTo(true));
     }
 }

core/src/test/java/org/elasticsearch/index/mapper/update/UpdateMappingTests.java

@@ -158,25 +158,6 @@ public class UpdateMappingTests extends ESSingleNodeTestCase {
         assertTrue(documentMapper.timestampFieldMapper().fieldType().stored());
     }
 
-    @Test
-    public void testSizeParsing() throws IOException {
-        IndexService indexService = createIndex("test", Settings.settingsBuilder().build());
-        XContentBuilder indexMapping = XContentFactory.jsonBuilder();
-        boolean enabled = randomBoolean();
-        indexMapping.startObject()
-                .startObject("type")
-                .startObject("_size")
-                .field("enabled", enabled)
-                .endObject()
-                .endObject()
-                .endObject();
-        DocumentMapper documentMapper = indexService.mapperService().parse("type", new CompressedXContent(indexMapping.string()), true);
-        assertThat(documentMapper.sizeFieldMapper().enabled(), equalTo(enabled));
-        assertTrue(documentMapper.sizeFieldMapper().fieldType().stored());
-        documentMapper = indexService.mapperService().parse("type", new CompressedXContent(documentMapper.mappingSource().string()), true);
-        assertThat(documentMapper.sizeFieldMapper().enabled(), equalTo(enabled));
-    }
-
     @Test
     public void testSizeTimestampIndexParsing() throws IOException {
         IndexService indexService = createIndex("test", Settings.settingsBuilder().build());
@@ -192,7 +173,7 @@ public class UpdateMappingTests extends ESSingleNodeTestCase {
         createIndex("test1", Settings.settingsBuilder().build());
         createIndex("test2", Settings.settingsBuilder().build());
         XContentBuilder defaultMapping = XContentFactory.jsonBuilder().startObject()
-                .startObject(MapperService.DEFAULT_MAPPING).startObject("_size").field("enabled", true).endObject().endObject()
+                .startObject(MapperService.DEFAULT_MAPPING).startObject("_timestamp").field("enabled", true).endObject().endObject()
                 .endObject();
         client().admin().indices().preparePutMapping().setType(MapperService.DEFAULT_MAPPING).setSource(defaultMapping).get();
         XContentBuilder typeMapping = XContentFactory.jsonBuilder().startObject()
@@ -204,7 +185,7 @@ public class UpdateMappingTests extends ESSingleNodeTestCase {
         GetMappingsResponse response = client().admin().indices().prepareGetMappings("test2").get();
         assertNotNull(response.getMappings().get("test2").get("type").getSourceAsMap().get("_all"));
         assertFalse((Boolean) ((LinkedHashMap) response.getMappings().get("test2").get("type").getSourceAsMap().get("_all")).get("enabled"));
-        assertNotNull(response.getMappings().get("test2").get("type").getSourceAsMap().get("_size"));
-        assertTrue((Boolean)((LinkedHashMap)response.getMappings().get("test2").get("type").getSourceAsMap().get("_size")).get("enabled"));
+        assertNotNull(response.getMappings().get("test2").get("type").getSourceAsMap().get("_timestamp"));
+        assertTrue((Boolean)((LinkedHashMap)response.getMappings().get("test2").get("type").getSourceAsMap().get("_timestamp")).get("enabled"));
     }
 }

core/src/test/java/org/elasticsearch/index/mapper/update/default_mapping_with_disabled_root_types.json

@@ -1 +1 @@
-{"type":{"_size":{"enabled":false},"_timestamp":{"enabled":false}}}
+{"type":{"_timestamp":{"enabled":false}}}

core/src/test/java/org/elasticsearch/index/query/CommonTermsQueryParserTest.java

@@ -0,0 +1,52 @@
+/*
+ * Licensed to Elasticsearch under one or more contributor
+ * license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright
+ * ownership. Elasticsearch licenses this file to you under
+ * the Apache License, Version 2.0 (the "License"); you may
+ * not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.elasticsearch.index.query;
+
+import org.elasticsearch.action.search.SearchResponse;
+import org.elasticsearch.test.ESSingleNodeTestCase;
+import org.junit.Test;
+
+import java.io.IOException;
+
+public class CommonTermsQueryParserTest extends ESSingleNodeTestCase {
+    @Test
+    public void testWhenParsedQueryIsNullNoNullPointerExceptionIsThrown() throws IOException {
+        final String index = "test-index";
+        final String type = "test-type";
+        client()
+                .admin()
+                .indices()
+                .prepareCreate(index)
+                .addMapping(type, "name", "type=string,analyzer=stop")
+                .execute()
+                .actionGet();
+        ensureGreen();
+
+        CommonTermsQueryBuilder commonTermsQueryBuilder =
+                new CommonTermsQueryBuilder("name", "the").queryName("query-name");
+
+        // the named query parses to null; we are testing this does not cause a NullPointerException
+        SearchResponse response =
+                client().prepareSearch(index).setTypes(type).setQuery(commonTermsQueryBuilder).execute().actionGet();
+
+        assertNotNull(response);
+        assertEquals(response.getHits().hits().length, 0);
+    }
+}

core/src/test/java/org/elasticsearch/index/query/SimpleIndexQueryParserTests.java

@@ -54,6 +54,7 @@ import org.elasticsearch.common.xcontent.XContentFactory;
 import org.elasticsearch.common.xcontent.XContentHelper;
 import org.elasticsearch.common.xcontent.XContentParser;
 import org.elasticsearch.index.IndexService;
+import org.elasticsearch.index.engine.Engine;
 import org.elasticsearch.index.mapper.MapperService;
 import org.elasticsearch.index.mapper.ParsedDocument;
 import org.elasticsearch.index.mapper.core.NumberFieldMapper;
@@ -83,6 +84,7 @@ import static org.hamcrest.Matchers.*;
 public class SimpleIndexQueryParserTests extends ESSingleNodeTestCase {
 
     private IndexQueryParserService queryParser;
+    private IndexService indexService;
 
     @Before
     public void setup() throws IOException {
@@ -99,6 +101,7 @@ public class SimpleIndexQueryParserTests extends ESSingleNodeTestCase {
         assertNotNull(doc.dynamicMappingsUpdate());
         client().admin().indices().preparePutMapping("test").setType("person").setSource(doc.dynamicMappingsUpdate().toString()).get();
 
+        this.indexService = indexService;
         queryParser = indexService.queryParserService();
     }
 
@@ -2269,6 +2272,23 @@ public class SimpleIndexQueryParserTests extends ESSingleNodeTestCase {
         assertThat(parsedQuery, instanceOf(BooleanQuery.class));
     }
 
+    public void testCrossFieldMultiMatchQuery() throws IOException {
+        IndexQueryParserService queryParser = queryParser();
+        Query parsedQuery = queryParser.parse(multiMatchQuery("banon", "name.first^2", "name.last^3", "foobar").type(MultiMatchQueryBuilder.Type.CROSS_FIELDS)).query();
+        try (Engine.Searcher searcher = indexService.shardSafe(0).acquireSearcher("test")) {
+            Query rewrittenQuery = searcher.searcher().rewrite(parsedQuery);
+
+            BooleanQuery expected = new BooleanQuery();
+            expected.add(new TermQuery(new Term("foobar", "banon")), Occur.SHOULD);
+            TermQuery tq1 = new TermQuery(new Term("name.first", "banon"));
+            tq1.setBoost(2);
+            TermQuery tq2 = new TermQuery(new Term("name.last", "banon"));
+            tq2.setBoost(3);
+            expected.add(new DisjunctionMaxQuery(Arrays.<Query>asList(tq1, tq2), 0f), Occur.SHOULD);
+            assertEquals(expected, rewrittenQuery);
+        }
+    }
+
     @Test
     public void testSimpleQueryString() throws Exception {
         IndexQueryParserService queryParser = queryParser();

core/src/test/java/org/elasticsearch/percolator/PercolatorIT.java

@@ -506,37 +506,6 @@ public class PercolatorIT extends ESIntegTestCase {
         assertThat(percolate.getMatches(), emptyArray());
     }
 
-    @Test
-    public void percolateWithSizeField() throws Exception {
-        String mapping = XContentFactory.jsonBuilder().startObject().startObject("type1")
-                .startObject("_size").field("enabled", true).endObject()
-                .startObject("properties").startObject("field1").field("type", "string").endObject().endObject()
-                .endObject().endObject().string();
-
-        assertAcked(prepareCreate("test").addMapping("type1", mapping));
-        ensureGreen();
-
-        logger.info("--> register a query");
-        client().prepareIndex("test", PercolatorService.TYPE_NAME, "kuku")
-                .setSource(jsonBuilder().startObject()
-                        .field("query", termQuery("field1", "value1"))
-                        .endObject())
-                .setRefresh(true)
-                .execute().actionGet();
-
-        logger.info("--> percolate a document");
-        PercolateResponse percolate = client().preparePercolate().setIndices("test").setDocumentType("type1")
-                .setSource(jsonBuilder().startObject()
-                        .startObject("doc")
-                        .field("field1", "value1")
-                        .endObject()
-                        .endObject())
-                .execute().actionGet();
-        assertMatchCount(percolate, 1l);
-        assertThat(percolate.getMatches(), arrayWithSize(1));
-        assertThat(convertFromTextArray(percolate.getMatches(), "test"), arrayContaining("kuku"));
-    }
-
     @Test
     public void testPercolateStatistics() throws Exception {
         client().admin().indices().prepareCreate("test").execute().actionGet();

core/src/test/java/org/elasticsearch/script/NativeScriptTests.java

@@ -97,6 +97,11 @@ public class NativeScriptTests extends ESTestCase {
         public ExecutableScript newScript(@Nullable Map<String, Object> params) {
             return new MyScript();
         }
+
+        @Override
+        public boolean needsScores() {
+            return false;
+        }
     }
 
     static class MyScript extends AbstractExecutableScript {

core/src/test/java/org/elasticsearch/script/ScriptFieldIT.java

@@ -81,6 +81,11 @@ public class ScriptFieldIT extends ESIntegTestCase {
         public ExecutableScript newScript(@Nullable Map<String, Object> params) {
             return new IntScript();
         }
+
+        @Override
+        public boolean needsScores() {
+            return false;
+        }
     }
 
     static class IntScript extends AbstractSearchScript {
@@ -95,6 +100,11 @@ public class ScriptFieldIT extends ESIntegTestCase {
         public ExecutableScript newScript(@Nullable Map<String, Object> params) {
             return new LongScript();
         }
+
+        @Override
+        public boolean needsScores() {
+            return false;
+        }
     }
 
     static class LongScript extends AbstractSearchScript {
@@ -109,6 +119,11 @@ public class ScriptFieldIT extends ESIntegTestCase {
         public ExecutableScript newScript(@Nullable Map<String, Object> params) {
             return new FloatScript();
         }
+
+        @Override
+        public boolean needsScores() {
+            return false;
+        }
     }
 
     static class FloatScript extends AbstractSearchScript {
@@ -123,6 +138,11 @@ public class ScriptFieldIT extends ESIntegTestCase {
         public ExecutableScript newScript(@Nullable Map<String, Object> params) {
             return new DoubleScript();
         }
+
+        @Override
+        public boolean needsScores() {
+            return false;
+        }
     }
 
     static class DoubleScript extends AbstractSearchScript {

core/src/test/java/org/elasticsearch/script/expression/ExpressionScriptTests.java

@@ -0,0 +1,57 @@
+/*
+ * Licensed to Elasticsearch under one or more contributor
+ * license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright
+ * ownership. Elasticsearch licenses this file to you under
+ * the Apache License, Version 2.0 (the "License"); you may
+ * not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.elasticsearch.script.expression;
+
+import org.elasticsearch.common.settings.Settings;
+import org.elasticsearch.index.IndexService;
+import org.elasticsearch.script.CompiledScript;
+import org.elasticsearch.script.ScriptService.ScriptType;
+import org.elasticsearch.script.SearchScript;
+import org.elasticsearch.search.lookup.SearchLookup;
+import org.elasticsearch.test.ESSingleNodeTestCase;
+
+import java.util.Collections;
+
+public class ExpressionScriptTests extends ESSingleNodeTestCase {
+
+    public void testNeedsScores() {
+        IndexService index = createIndex("test", Settings.EMPTY, "type", "d", "type=double");
+        
+        ExpressionScriptEngineService service = new ExpressionScriptEngineService(Settings.EMPTY);
+        SearchLookup lookup = new SearchLookup(index.mapperService(), index.fieldData(), null);
+
+        Object compiled = service.compile("1.2");
+        SearchScript ss = service.search(new CompiledScript(ScriptType.INLINE, "randomName", "expression", compiled), lookup, Collections.<String, Object>emptyMap());
+        assertFalse(ss.needsScores());
+
+        compiled = service.compile("doc['d'].value");
+        ss = service.search(new CompiledScript(ScriptType.INLINE, "randomName", "expression", compiled), lookup, Collections.<String, Object>emptyMap());
+        assertFalse(ss.needsScores());
+
+        compiled = service.compile("1/_score");
+        ss = service.search(new CompiledScript(ScriptType.INLINE, "randomName", "expression", compiled), lookup, Collections.<String, Object>emptyMap());
+        assertTrue(ss.needsScores());
+
+        compiled = service.compile("doc['d'].value * _score");
+        ss = service.search(new CompiledScript(ScriptType.INLINE, "randomName", "expression", compiled), lookup, Collections.<String, Object>emptyMap());
+        assertTrue(ss.needsScores());
+    }
+
+}

core/src/test/java/org/elasticsearch/search/aggregations/bucket/script/NativeSignificanceScoreScriptNoParams.java

@@ -35,6 +35,11 @@ public class NativeSignificanceScoreScriptNoParams extends TestScript {
         public ExecutableScript newScript(@Nullable Map<String, Object> params) {
             return new NativeSignificanceScoreScriptNoParams();
         }
+
+        @Override
+        public boolean needsScores() {
+            return false;
+        }
     }
 
     private NativeSignificanceScoreScriptNoParams() {

core/src/test/java/org/elasticsearch/search/aggregations/bucket/script/NativeSignificanceScoreScriptWithParams.java

@@ -36,6 +36,11 @@ public class NativeSignificanceScoreScriptWithParams extends TestScript {
         public ExecutableScript newScript(@Nullable Map<String, Object> params) {
             return new NativeSignificanceScoreScriptWithParams(params);
         }
+
+        @Override
+        public boolean needsScores() {
+            return false;
+        }
     }
 
     private NativeSignificanceScoreScriptWithParams(Map<String, Object> params) {

core/src/test/java/org/elasticsearch/search/fields/SearchFieldsIT.java

@@ -76,9 +76,8 @@ public class SearchFieldsIT extends ESIntegTestCase {
         client().admin().cluster().prepareHealth().setWaitForEvents(Priority.LANGUID).setWaitForYellowStatus().execute().actionGet();
 
         String mapping = XContentFactory.jsonBuilder().startObject().startObject("type1")
-                // _timestamp and _size are randomly enabled via templates but we don't want it here to test stored fields behaviour
+                // _timestamp is randomly enabled via templates but we don't want it here to test stored fields behaviour
                 .startObject("_timestamp").field("enabled", false).endObject()
-                .startObject("_size").field("enabled", false).endObject()
                 .startObject("properties")
                 .startObject("field1").field("type", "string").field("store", "yes").endObject()
                 .startObject("field2").field("type", "string").field("store", "no").endObject()

core/src/test/java/org/elasticsearch/search/functionscore/ExplainableScriptIT.java

@@ -102,6 +102,10 @@ public class ExplainableScriptIT extends ESIntegTestCase {
         public ExecutableScript newScript(@Nullable Map<String, Object> params) {
             return new MyScript();
         }
+        @Override
+        public boolean needsScores() {
+            return true;
+        }
     }
 
     static class MyScript extends AbstractDoubleSearchScript implements ExplainableSearchScript, ExecutableScript {

core/src/test/java/org/elasticsearch/test/ESIntegTestCase.java

@@ -102,7 +102,6 @@ import org.elasticsearch.index.fielddata.FieldDataType;
 import org.elasticsearch.index.mapper.DocumentMapper;
 import org.elasticsearch.index.mapper.MappedFieldType;
 import org.elasticsearch.index.mapper.MappedFieldType.Loading;
-import org.elasticsearch.index.mapper.internal.SizeFieldMapper;
 import org.elasticsearch.index.mapper.internal.TimestampFieldMapper;
 import org.elasticsearch.index.shard.MergePolicyConfig;
 import org.elasticsearch.index.translog.Translog;
@@ -357,11 +356,6 @@ public abstract class ESIntegTestCase extends ESTestCase {
                             .field("enabled", randomBoolean());
                     mappings.endObject();
                 }
-                if (randomBoolean()) {
-                    mappings.startObject(SizeFieldMapper.NAME)
-                            .field("enabled", randomBoolean())
-                            .endObject();
-                }
                 mappings.startArray("dynamic_templates")
                         .startObject()
                         .startObject("template-strings")

core/src/test/java/org/elasticsearch/update/UpdateByNativeScriptIT.java

@@ -74,6 +74,10 @@ public class UpdateByNativeScriptIT extends ESIntegTestCase {
         public ExecutableScript newScript(@Nullable Map<String, Object> params) {
             return new CustomScript(params);
         }
+        @Override
+        public boolean needsScores() {
+            return false;
+        }
     }
 
     static class CustomScript extends AbstractExecutableScript {

docs/reference/aggregations/bucket/geodistance-aggregation.asciidoc

@@ -53,7 +53,7 @@ Response:
 }
 --------------------------------------------------
 
-The specified field must be of type `geo_point` (which can only be set explicitly in the mappings). And it can also hold an array of `geo_point` fields, in which case all will be taken into account during aggregation. The origin point can accept all formats supported by the `geo_point` <<mapping-geo-point-type,type>>:
+The specified field must be of type `geo_point` (which can only be set explicitly in the mappings). And it can also hold an array of `geo_point` fields, in which case all will be taken into account during aggregation. The origin point can accept all formats supported by the <<geo-point,`geo_point` type>>:
 
 * Object format: `{ "lat" : 52.3760, "lon" : 4.894 }` - this is the safest format as it is the most explicit about the `lat` & `lon` values
 * String format: `"52.3760, 4.894"` - where the first number is the `lat` and the second is the `lon`

docs/reference/aggregations/metrics/tophits-aggregation.asciidoc

@@ -200,7 +200,7 @@ and therefore can't be used in the `order` option of the `terms` aggregator.
 If the `top_hits` aggregator is wrapped in a `nested` or `reverse_nested` aggregator then nested hits are being returned.
 Nested hits are in a sense hidden mini documents that are part of regular document where in the mapping a nested field type
 has been configured. The `top_hits` aggregator has the ability to un-hide these documents if it is wrapped in a `nested`
-or `reverse_nested` aggregator. Read more about nested in the <<mapping-nested-type,nested type mapping>>.
+or `reverse_nested` aggregator. Read more about nested in the <<nested,nested type mapping>>.
 
 If nested type has been configured a single document is actually indexed as multiple Lucene documents and they share
 the same id. In order to determine the identity of a nested hit there is more needed than just the id, so that is why

docs/reference/api-conventions.asciidoc

@@ -152,6 +152,34 @@ being consumed by a monitoring tool, rather than intended for human
 consumption.  The default for the `human` flag is
 `false`.
 
+[[date-math]]
+[float]
+=== Date Math
+
+Most parameters which accept a formatted date value -- such as `gt` and `lt`
+in <<query-dsl-range-query,range queries>> `range` queries, or `from` and `to`
+in <<search-aggregations-bucket-daterange-aggregation,`daterange`
+aggregations>> -- understand date maths.
+
+The expression starts with an anchor date, which can either be `now`, or a
+date string ending with `||`. This anchor date can optionally be followed by
+one or more maths expressions:
+
+* `+1h` - add one hour
+* `-1d` - subtract one day
+* `/d`  - round down to the nearest day
+
+The supported <<time-units,time units>> are: `y` (year), `M` (month), `w` (week),
+`d` (day), `h` (hour), `m` (minute), and `s` (second).
+
+Some examples are:
+
+[horizontal]
+`now+1h`::              The current time plus one hour, with ms resolution.
+`now+1h+1m`::           The current time plus one hour plus one minute, with ms resolution.
+`now+1h/d`::            The current time plus one hour, rounded down to the nearest day.
+`2015-01-01||+1M/d`::   `2015-01-01` plus one month, rounded down to the nearest day.
+
 [float]
 === Response Filtering
 
@@ -237,10 +265,10 @@ curl 'localhost:9200/_segments?pretty&filter_path=indices.**.version'
 --------------------------------------------------
 
 Note that elasticsearch sometimes returns directly the raw value of a field,
-like the `_source` field. If you want to filter _source fields, you should
+like the `_source` field. If you want to filter `_source` fields, you should
 consider combining the already existing `_source` parameter (see
 <<get-source-filtering,Get API>> for more details) with the `filter_path`
- parameter like this:
+parameter like this:
 
 [source,sh]
 --------------------------------------------------
@@ -318,8 +346,9 @@ of supporting the native JSON number types.
 [float]
 === Time units
 
-Whenever durations need to be specified, eg for a `timeout` parameter, the duration
-can be specified as a whole number representing time in milliseconds, or as a time value like `2d` for 2 days.  The supported units are:
+Whenever durations need to be specified, eg for a `timeout` parameter, the
+duration must specify the unit, like `2d` for 2 days.  The supported units
+are:
 
 [horizontal]
 `y`::   Year
@@ -329,6 +358,7 @@ can be specified as a whole number representing time in milliseconds, or as a ti
 `h`::   Hour
 `m`::   Minute
 `s`::   Second
+`ms`::  Milli-second
 
 [[distance-units]]
 [float]

docs/reference/index-modules/mapper.asciidoc

@@ -6,53 +6,3 @@ added to an index either when creating it or by using the put mapping
 api. It also handles the dynamic mapping support for types that have no
 explicit mappings pre defined. For more information about mapping
 definitions, check out the <<mapping,mapping section>>.
-
-[float]
-=== Dynamic Mappings
-
-New types and new fields within types can be added dynamically just
-by indexing a document.  When Elasticsearch encounters a new type,
-it creates the type using the `_default_` mapping (see below).
-
-When it encounters a new field within a type, it autodetects the
-datatype that the field contains and adds it to the type mapping
-automatically.
-
-See <<mapping-dynamic-mapping>> for details of how to control and
-configure dynamic mapping.
-
-[float]
-=== Default Mapping
-
-When a new type is created (at <<indices-create-index,index creation>> time,
-using the  <<indices-put-mapping,`put-mapping` API>> or just by indexing a
-document into it), the type uses the `_default_` mapping as its basis.  Any
-mapping specified in the  <<indices-create-index,`create-index`>> or
-<<indices-put-mapping,`put-mapping`>> request override values set in the
-`_default_` mapping.
-
-The default mapping definition is a plain mapping definition that is
-embedded within Elasticsearch:
-
-[source,js]
---------------------------------------------------
-{
-    _default_ : {
-    }
-}
---------------------------------------------------
-
-Pretty short, isn't it? Basically, everything is `_default_`ed, including the
-dynamic nature of the root object mapping which allows new fields to be added
-automatically.
-
-The default mapping can be overridden by specifying the `_default_` type when
-creating a new index.
-
-[float]
-=== Mapper settings
-
-`index.mapper.dynamic` (_dynamic_)::
-
-    Dynamic creation of mappings for unmapped types can be completely
-    disabled by setting `index.mapper.dynamic` to `false`.

docs/reference/index-modules/similarity.asciidoc

@@ -6,8 +6,8 @@ are scored. Similarity is per field, meaning that via the mapping one
 can define a different similarity per field.
 
 Configuring a custom similarity is considered a expert feature and the
-builtin similarities are most likely sufficient as is described in the
-<<mapping-core-types,mapping section>>
+builtin similarities are most likely sufficient as is described in
+<<similarity>>.
 
 [float]
 [[configuration]]
@@ -41,7 +41,7 @@ Here we configure the DFRSimilarity so it can be referenced as
     "properties" : {
       "title" : { "type" : "string", "similarity" : "my_similarity" }
     }
-} 
+}
 --------------------------------------------------
 
 [float]
@@ -52,9 +52,9 @@ Here we configure the DFRSimilarity so it can be referenced as
 ==== Default similarity
 
 The default similarity that is based on the TF/IDF model. This
-similarity has the following option: 
+similarity has the following option:
 
-`discount_overlaps`:: 
+`discount_overlaps`::
     Determines whether overlap tokens (Tokens with
     0 position increment) are ignored when computing norm. By default this
     is true, meaning overlap tokens do not count when computing norms.
@@ -71,14 +71,14 @@ http://en.wikipedia.org/wiki/Okapi_BM25[Okapi_BM25] for more details.
 This similarity has the following options:
 
 [horizontal]
-`k1`:: 
+`k1`::
     Controls non-linear term frequency normalization
-    (saturation). 
+    (saturation).
 
-`b`:: 
-    Controls to what degree document length normalizes tf values. 
+`b`::
+    Controls to what degree document length normalizes tf values.
 
-`discount_overlaps`:: 
+`discount_overlaps`::
     Determines whether overlap tokens (Tokens with
     0 position increment) are ignored when computing norm. By default this
     is true, meaning overlap tokens do not count when computing norms.
@@ -90,17 +90,17 @@ Type name: `BM25`
 ==== DFR similarity
 
 Similarity that implements the
-http://lucene.apache.org/core/4_1_0/core/org/apache/lucene/search/similarities/DFRSimilarity.html[divergence
+http://lucene.apache.org/core/5_2_1/core/org/apache/lucene/search/similarities/DFRSimilarity.html[divergence
 from randomness] framework. This similarity has the following options:
 
 [horizontal]
-`basic_model`:: 
-    Possible values: `be`, `d`, `g`, `if`, `in`, `ine` and `p`. 
+`basic_model`::
+    Possible values: `be`, `d`, `g`, `if`, `in`, `ine` and `p`.
 
 `after_effect`::
-    Possible values: `no`, `b` and `l`. 
+    Possible values: `no`, `b` and `l`.
 
-`normalization`:: 
+`normalization`::
     Possible values: `no`, `h1`, `h2`, `h3` and `z`.
 
 All options but the first option need a normalization value.
@@ -111,12 +111,12 @@ Type name: `DFR`
 [[ib]]
 ==== IB similarity.
 
-http://lucene.apache.org/core/4_1_0/core/org/apache/lucene/search/similarities/IBSimilarity.html[Information
+http://lucene.apache.org/core/5_2_1/core/org/apache/lucene/search/similarities/IBSimilarity.html[Information
 based model] . This similarity has the following options:
 
 [horizontal]
-`distribution`::  Possible values: `ll` and `spl`. 
-`lambda`::        Possible values: `df` and `ttf`. 
+`distribution`::  Possible values: `ll` and `spl`.
+`lambda`::        Possible values: `df` and `ttf`.
 `normalization`:: Same as in `DFR` similarity.
 
 Type name: `IB`
@@ -125,7 +125,7 @@ Type name: `IB`
 [[lm_dirichlet]]
 ==== LM Dirichlet similarity.
 
-http://lucene.apache.org/core/4_7_1/core/org/apache/lucene/search/similarities/LMDirichletSimilarity.html[LM
+http://lucene.apache.org/core/5_2_1/core/org/apache/lucene/search/similarities/LMDirichletSimilarity.html[LM
 Dirichlet similarity] . This similarity has the following options:
 
 [horizontal]
@@ -137,7 +137,7 @@ Type name: `LMDirichlet`
 [[lm_jelinek_mercer]]
 ==== LM Jelinek Mercer similarity.
 
-http://lucene.apache.org/core/4_7_1/core/org/apache/lucene/search/similarities/LMJelinekMercerSimilarity.html[LM
+http://lucene.apache.org/core/5_2_1/core/org/apache/lucene/search/similarities/LMJelinekMercerSimilarity.html[LM
 Jelinek Mercer similarity] . This similarity has the following options:
 
 [horizontal]

docs/reference/mapping.asciidoc

@@ -3,76 +3,173 @@
 
 [partintro]
 --
-Mapping is the process of defining how a document should be mapped to
-the Search Engine, including its searchable characteristics such as
-which fields are searchable and if/how they are tokenized. In
-Elasticsearch, an index may store documents of different "mapping
-types". Elasticsearch allows one to associate multiple mapping
-definitions for each mapping type.
 
-Explicit mapping is defined on an index/type level. By default, there
-isn't a need to define an explicit mapping, since one is automatically
-created and registered when a new type or new field is introduced (with
-no performance overhead) and have sensible defaults. Only when the
-defaults need to be overridden must a mapping definition be provided.
+Mapping is the process of defining how a document, and the fields it contains,
+are stored and indexed.  For instance, use mappings to define:
+
+* which string fields should be treated as full text fields.
+* which fields contain numbers, dates, or geolocations.
+* whether the values of all fields in the document should be
+  indexed into the catch-all <<mapping-all-field,`_all`>> field.
+* the <<mapping-date-format,format>> of date values.
+* custom rules to control the mapping for
+  <<dynamic-mapping,dynamically added fields>>.
 
 [float]
-[[all-mapping-types]]
-=== Mapping Types
+[[mapping-type]]
+== Mapping Types
 
-Mapping types are a way to divide the documents in an index into logical
-groups. Think of it as tables in a database. Though there is separation
-between types, it's not a full separation (all end up as a document
-within the same Lucene index).
+Each index has one or more _mapping types_, which are used to divide the
+documents in an index into logical groups. User documents might be stored in a
+`user` type, and blog posts in a `blogpost` type.
 
-Field names with the same name across types are highly recommended to
-have the same type and same mapping characteristics (analysis settings
-for example). There is an effort to allow to explicitly "choose" which
-field to use by using type prefix (`my_type.my_field`), but it's not
-complete, and there are places where it will never work (like
-aggregations on the field).
+Each mapping type has:
+
+<<mapping-fields,Meta-fields>>::
+
+Meta-fields are used to customize how a document's metadata associated is
+treated. Examples of meta-fields include the document's
+<<mapping-index-field,`_index`>>, <<mapping-type-field,`_type`>>,
+<<mapping-id-field,`_id`>>,  and <<mapping-source-field,`_source`>> fields.
+
+<<mapping-types,Fields>> or _properties_::
+
+Each mapping type contains a list of fields or `properties` pertinent to that
+type.  A `user` type might contain `title`, `name`, and `age` fields, while a
+`blogpost` type might contain `title`, `body`, `user_id` and `created` fields.
+Fields with the same name in different mapping types in the same index
+<<field-conflicts,must have the same mapping>>.
 
-In practice though, this restriction is almost never an issue. The field
-name usually ends up being a good indication to its "typeness" (e.g.
-"first_name" will always be a string). Note also, that this does not
-apply to the cross index case.
 
 [float]
-[[mapping-api]]
-=== Mapping API
+== Field datatypes
 
-To create a mapping, you will need the <<indices-put-mapping,Put Mapping
-API>>, or you can add multiple mappings when you <<indices-create-index,create an
-index>>.
+Each field has a data `type` which can be:
+
+* a simple type like <<string,`string`>>, <<date,`date`>>, <<number,`long`>>,
+  <<number,`double`>>, <<boolean,`boolean`>> or <<ip,`ip`>>.
+* a type which supports the hierarchical nature of JSON such as
+  <<object,`object`>> or <<nested,`nested`>>.
+* or a specialised type like <<geo-point,`geo_point`>>,
+  <<geo-shape,`geo_shape`>>, or <<search-suggesters-completion,`completion`>>.
+
+It is often useful to index the same field in different ways for different
+purposes. For instance, a `string` field could be <<mapping-index,indexed>> as
+an `analyzed` field for full-text search, and as a `not_analyzed` field for
+sorting or aggregations.  Alternatively, you could index a string field with
+the <<analysis-standard-analyzer,`standard` analyzer>>, the
+<<english-analyzer,`english`>> analyzer, and the
+<<french-analyzer,`french` analyzer>>.
+
+This is the purpose of _multi-fields_.  Most datatypes support multi-fields
+via the <<multi-fields>> parameter.
 
 [float]
-[[mapping-settings]]
-=== Global Settings
+== Dynamic mapping
+
+Fields and mapping types do not need to be defined before being used. Thanks
+to _dynamic mapping_, new mapping types and new field names will be added
+automatically, just by indexing a document. New fields can be added both to
+the top-level mapping type, and to inner <<object,`object`>>  and
+<<nested,`nested`>> fields.
+
+The
+<<dynamic-mapping,dynamic mapping>> rules can be configured to
+customise the mapping that is used for new types and new fields.
+
+[float]
+== Explicit mappings
+
+You know more about your data than Elasticsearch can guess, so while dynamic
+mapping can be useful to get started, at some point you will want to specify
+your own explicit mappings.
+
+You can create mapping types and field mappings when you
+<<indices-create-index,create an index>>, and you can add mapping types and
+fields to an existing index with the <<indices-put-mapping,PUT mapping API>>.
+
+[float]
+== Updating existing mappings
+
+Other than where documented, *existing type and field mappings cannot be
+updated*. Changing the mapping would mean invalidating already indexed
+documents.  Instead, you should create a new index with the correct mappings
+and reindex your data into that index.
+
+[[field-conflicts]]
+[float]
+== Fields are shared across mapping types
+
+Mapping types are used to group fields, but the fields in each mapping type
+are not independent of each other. Fields with:
+
+* the _same name_
+* in the _same index_
+* in _different mapping types_
+* map to the _same field_ internally,
+* and *must have the same mapping*.
+
+If a `title` field exists in both the `user` and `blogpost` mapping types, the
+`title` fields must have exactly the same mapping in each type.  The only
+exceptions to this rule are the <<copy-to>>, <<dynamic>>, <<enabled>>,
+<<ignore-above>>, <<include-in-all>>, and <<properties>> parameters, which may
+have different settings per field.
+
+Usually, fields with the same name also contain the same type of data, so
+having the same mapping is not a problem.  When conflicts do arise, these can
+be solved by choosing more descriptive names, such as `user_title` and
+`blog_title`.
+
+[float]
+== Example mapping
+
+A mapping for the example described above could be specified when creating the
+index, as follows:
+
+[source,js]
+---------------------------------------
+PUT my_index <1>
+{
+  "mappings": {
+    "user": { <2>
+      "_all":       { "enabled": false  }, <3>
+      "properties": { <4>
+        "title":    { "type": "string"  }, <5>
+        "name":     { "type": "string"  }, <5>
+        "age":      { "type": "integer" }  <5>
+      }
+    },
+    "blogpost": { <2>
+      "properties": { <4>
+        "title":    { "type": "string"  }, <5>
+        "body":     { "type": "string"  }, <5>
+        "user_id":  {
+          "type":   "string", <5>
+          "index":  "not_analyzed"
+        },
+        "created":  {
+          "type":   "date", <5>
+          "format": "strict_date_optional_time||epoch_millis"
+        }
+      }
+    }
+  }
+}
+---------------------------------------
+// AUTOSENSE
+<1> Create an index called `my_index`.
+<2> Add mapping types called `user` and `blogpost`.
+<3> Disable the `_all` <<mapping-fields,meta field>> for the `user` mapping type.
+<4> Specify fields or _properties_ in each mapping type.
+<5> Specify the data `type` and mapping for each field.
 
-The `index.mapping.ignore_malformed` global setting can be set on the
-index level to allow to ignore malformed content globally across all
-mapping types (malformed content example is trying to index a text string
-value as a numeric type).
 
-The `index.mapping.coerce` global setting can be set on the
-index level to coerce numeric content globally across all
-mapping types (The default setting is true and coercions attempted are
-to convert strings with numbers into numeric types and also numeric values
-with fractions to any integer/short/long values minus the fraction part).
-When the permitted conversions fail in their attempts, the value is considered
-malformed and the ignore_malformed setting dictates what will happen next.
 --
 
-include::mapping/fields.asciidoc[]
-
 include::mapping/types.asciidoc[]
 
-include::mapping/date-format.asciidoc[]
+include::mapping/fields.asciidoc[]
 
-include::mapping/fielddata_formats.asciidoc[]
+include::mapping/params.asciidoc[]
 
 include::mapping/dynamic-mapping.asciidoc[]
-
-include::mapping/meta.asciidoc[]
-
-include::mapping/transform.asciidoc[]

docs/reference/mapping/date-format.asciidoc

@@ -1,238 +0,0 @@
-[[mapping-date-format]]
-== Date Format
-
-In JSON documents, dates are represented as strings. Elasticsearch uses a set
-of pre-configured format to recognize and convert those, but you can change the
-defaults by specifying the `format` option when defining a `date` type, or by
-specifying `dynamic_date_formats` in the `root object` mapping (which will
-be used unless explicitly overridden by a `date` type). There are built in
-formats supported, as well as complete custom one.
-
-The parsing of dates uses http://www.joda.org/joda-time/[Joda]. The
-default date parsing used if no format is specified is
-http://www.joda.org/joda-time/apidocs/org/joda/time/format/ISODateTimeFormat.html#dateOptionalTimeParser--[ISODateTimeFormat.dateOptionalTimeParser].
-
-An extension to the format allow to define several formats using `||`
-separator. This allows to define less strict formats that can be used,
-for example, the `yyyy/MM/dd HH:mm:ss||yyyy/MM/dd` format will parse
-both `yyyy/MM/dd HH:mm:ss` and `yyyy/MM/dd`. The first format will also
-act as the one that converts back from milliseconds to a string
-representation.
-
-[float]
-[[date-math]]
-=== Date Math
-
-The `date` type supports using date math expression when using it in a
-query/filter (mainly makes sense in `range` query/filter).
-
-The expression starts with an "anchor" date, which can be either `now`
-or a date string (in the applicable format) ending with `||`. It can
-then follow by a math expression, supporting `+`, `-` and `/`
-(rounding). The units supported are `y` (year), `M` (month), `w` (week),
-`d` (day), `h` (hour), `m` (minute), and `s` (second).
-
-Here are some samples: `now+1h`, `now+1h+1m`, `now+1h/d`,
-`2012-01-01||+1M/d`.
-
-When doing `range` type searches with rounding, the value parsed
-depends on whether the end of the range is inclusive or exclusive, and
-whether the beginning or end of the range.  Rounding up moves to the
-last millisecond of the rounding scope, and rounding down to the
-first millisecond of the rounding scope. The semantics work as follows:
-* `gt` - round up, and use > that value (`2014-11-18||/M` becomes `2014-11-30T23:59:59.999`, ie excluding the entire month)
-* `gte` - round D down, and use >= that value (`2014-11-18||/M` becomes `2014-11-01`, ie including the entire month)
-* `lt` - round D down, and use < that value (`2014-11-18||/M` becomes `2014-11-01`, ie excluding the entire month)
-* `lte` - round D up, and use <= that value(`2014-11-18||/M` becomes `2014-11-30T23:59:59.999`, ie including the entire month)
-
-[float]
-[[built-in]]
-=== Built In Formats
-
-Most of the below dates have a `strict` companion dates, which means, that
-year, month and day parts of the week must have prepending zeros in order
-to be valid. This means, that a date like `5/11/1` would not be valid, but
-you would need to specify the full date, which would be `2005/11/01` in this
-example. So instead of `date_optional_time` you would need to specify
-`strict_date_optional_time`.
-
-The following tables lists all the defaults ISO formats supported:
-
-[cols="<,<",options="header",]
-|=======================================================================
-|Name |Description
-|`basic_date`|A basic formatter for a full date as four digit year, two
-digit month of year, and two digit day of month (yyyyMMdd).
-
-|`basic_date_time`|A basic formatter that combines a basic date and time,
-separated by a 'T' (yyyyMMdd'T'HHmmss.SSSZ).
-
-|`basic_date_time_no_millis`|A basic formatter that combines a basic date
-and time without millis, separated by a 'T' (yyyyMMdd'T'HHmmssZ).
-
-|`basic_ordinal_date`|A formatter for a full ordinal date, using a four
-digit year and three digit dayOfYear (yyyyDDD).
-
-|`basic_ordinal_date_time`|A formatter for a full ordinal date and time,
-using a four digit year and three digit dayOfYear
-(yyyyDDD'T'HHmmss.SSSZ).
-
-|`basic_ordinal_date_time_no_millis`|A formatter for a full ordinal date
-and time without millis, using a four digit year and three digit
-dayOfYear (yyyyDDD'T'HHmmssZ).
-
-|`basic_time`|A basic formatter for a two digit hour of day, two digit
-minute of hour, two digit second of minute, three digit millis, and time
-zone offset (HHmmss.SSSZ).
-
-|`basic_time_no_millis`|A basic formatter for a two digit hour of day,
-two digit minute of hour, two digit second of minute, and time zone
-offset (HHmmssZ).
-
-|`basic_t_time`|A basic formatter for a two digit hour of day, two digit
-minute of hour, two digit second of minute, three digit millis, and time
-zone off set prefixed by 'T' ('T'HHmmss.SSSZ).
-
-|`basic_t_time_no_millis`|A basic formatter for a two digit hour of day,
-two digit minute of hour, two digit second of minute, and time zone
-offset prefixed by 'T' ('T'HHmmssZ).
-
-|`basic_week_date`|A basic formatter for a full date as four digit
-weekyear, two digit week of weekyear, and one digit day of week
-(xxxx'W'wwe). `strict_basic_week_date` is supported.
-
-|`basic_week_date_time`|A basic formatter that combines a basic weekyear
-date and time, separated by a 'T' (xxxx'W'wwe'T'HHmmss.SSSZ).
-`strict_basic_week_date_time` is supported.
-
-|`basic_week_date_time_no_millis`|A basic formatter that combines a basic
-weekyear date and time without millis, separated by a 'T'
-(xxxx'W'wwe'T'HHmmssZ). `strict_week_date_time` is supported.
-
-|`date`|A formatter for a full date as four digit year, two digit month
-of year, and two digit day of month (yyyy-MM-dd). `strict_date` is supported.
-_
-|`date_hour`|A formatter that combines a full date and two digit hour of
-day. strict_date_hour` is supported.
-
-
-|`date_hour_minute`|A formatter that combines a full date, two digit hour
-of day, and two digit minute of hour. strict_date_hour_minute` is supported.
-
-|`date_hour_minute_second`|A formatter that combines a full date, two
-digit hour of day, two digit minute of hour, and two digit second of
-minute. `strict_date_hour_minute_second` is supported.
-
-|`date_hour_minute_second_fraction`|A formatter that combines a full
-date, two digit hour of day, two digit minute of hour, two digit second
-of minute, and three digit fraction of second
-(yyyy-MM-dd'T'HH:mm:ss.SSS). `strict_date_hour_minute_second_fraction` is supported.
-
-|`date_hour_minute_second_millis`|A formatter that combines a full date,
-two digit hour of day, two digit minute of hour, two digit second of
-minute, and three digit fraction of second (yyyy-MM-dd'T'HH:mm:ss.SSS).
-`strict_date_hour_minute_second_millis` is supported.
-
-|`date_optional_time`|a generic ISO datetime parser where the date is
-mandatory and the time is optional. `strict_date_optional_time` is supported.
-
-|`date_time`|A formatter that combines a full date and time, separated by
-a 'T' (yyyy-MM-dd'T'HH:mm:ss.SSSZZ). `strict_date_time` is supported.
-
-|`date_time_no_millis`|A formatter that combines a full date and time
-without millis, separated by a 'T' (yyyy-MM-dd'T'HH:mm:ssZZ).
-`strict_date_time_no_millis` is supported.
-
-|`hour`|A formatter for a two digit hour of day. `strict_hour` is supported.
-
-|`hour_minute`|A formatter for a two digit hour of day and two digit
-minute of hour. `strict_hour_minute` is supported.
-
-|`hour_minute_second`|A formatter for a two digit hour of day, two digit
-minute of hour, and two digit second of minute.
-`strict_hour_minute_second` is supported.
-
-|`hour_minute_second_fraction`|A formatter for a two digit hour of day,
-two digit minute of hour, two digit second of minute, and three digit
-fraction of second (HH:mm:ss.SSS).
-`strict_hour_minute_second_fraction` is supported.
-
-|`hour_minute_second_millis`|A formatter for a two digit hour of day, two
-digit minute of hour, two digit second of minute, and three digit
-fraction of second (HH:mm:ss.SSS).
-`strict_hour_minute_second_millis` is supported.
-
-|`ordinal_date`|A formatter for a full ordinal date, using a four digit
-year and three digit dayOfYear (yyyy-DDD). `strict_ordinal_date` is supported.
-
-|`ordinal_date_time`|A formatter for a full ordinal date and time, using
-a four digit year and three digit dayOfYear (yyyy-DDD'T'HH:mm:ss.SSSZZ).
-`strict_ordinal_date_time` is supported.
-
-|`ordinal_date_time_no_millis`|A formatter for a full ordinal date and
-time without millis, using a four digit year and three digit dayOfYear
-(yyyy-DDD'T'HH:mm:ssZZ).
-`strict_ordinal_date_time_no_millis` is supported.
-
-|`time`|A formatter for a two digit hour of day, two digit minute of
-hour, two digit second of minute, three digit fraction of second, and
-time zone offset (HH:mm:ss.SSSZZ). `strict_time` is supported.
-
-|`time_no_millis`|A formatter for a two digit hour of day, two digit
-minute of hour, two digit second of minute, and time zone offset
-(HH:mm:ssZZ). `strict_time_no_millis` is supported.
-
-|`t_time`|A formatter for a two digit hour of day, two digit minute of
-hour, two digit second of minute, three digit fraction of second, and
-time zone offset prefixed by 'T' ('T'HH:mm:ss.SSSZZ).
-`strict_t_time` is supported.
-
-|`t_time_no_millis`|A formatter for a two digit hour of day, two digit
-minute of hour, two digit second of minute, and time zone offset
-prefixed by 'T' ('T'HH:mm:ssZZ). `strict_t_time_no_millis` is supported.
-
-|`week_date`|A formatter for a full date as four digit weekyear, two
-digit week of weekyear, and one digit day of week (xxxx-'W'ww-e).
-`strict_week_date` is supported.
-
-|`week_date_time`|A formatter that combines a full weekyear date and
-time, separated by a 'T' (xxxx-'W'ww-e'T'HH:mm:ss.SSSZZ).
-`strict_week_date_time` is supported.
-
-|`week_date_time_no_millis`|A formatter that combines a full weekyear date
-and time without millis, separated by a 'T' (xxxx-'W'ww-e'T'HH:mm:ssZZ).
-`strict_week_date_time` is supported.
-
-|`weekyear`|A formatter for a four digit weekyear. `strict_week_year` is supported.
-
-|`weekyear_week`|A formatter for a four digit weekyear and two digit week
-of weekyear. `strict_weekyear_week` is supported.
-
-|`weekyear_week_day`|A formatter for a four digit weekyear, two digit week
-of weekyear, and one digit day of week. `strict_weekyear_week_day` is supported.
-
-|`year`|A formatter for a four digit year. `strict_year` is supported.
-
-|`year_month`|A formatter for a four digit year and two digit month of
-year. `strict_year_month` is supported.
-
-|`year_month_day`|A formatter for a four digit year, two digit month of
-year, and two digit day of month. `strict_year_month_day` is supported.
-
-|`epoch_second`|A formatter for the number of seconds since the epoch.
-Note, that this timestamp allows a max length of 10 chars, so dates
-older than 1653 and 2286 are not supported. You should use a different
-date formatter in that case.
-
-|`epoch_millis`|A formatter for the number of milliseconds since the epoch.
-Note, that this timestamp allows a max length of 13 chars, so dates
-older than 1653 and 2286 are not supported. You should use a different
-date formatter in that case.
-|=======================================================================
-
-[float]
-[[custom]]
-=== Custom Format
-
-Allows for a completely customizable date format explained
-http://www.joda.org/joda-time/apidocs/org/joda/time/format/DateTimeFormat.html[here].

docs/reference/mapping/dynamic-mapping.asciidoc

@@ -1,73 +1,67 @@
-[[mapping-dynamic-mapping]]
+[[dynamic-mapping]]
 == Dynamic Mapping
 
-Default mappings allow generic mapping definitions to be automatically applied
-to types that do not have mappings predefined. This is mainly done
-thanks to the fact that the
-<<mapping-object-type,object mapping>> and
-namely the <<mapping-root-object-type,root
-object mapping>> allow for schema-less dynamic addition of unmapped
-fields.
-
-The default mapping definition is a plain mapping definition that is
-embedded within the distribution:
+One of the most important features of Elasticsearch is that it tries to get
+out of your way and let you start exploring your data as quickly as possible.
+To index a document, you don't have to first create an index, define a mapping
+type, and define your fields -- you can just index a document and the index,
+type, and fields will spring to life automatically:
 
 [source,js]
 --------------------------------------------------
-{
-    "_default_" : {
-    }
-}
+PUT data/counters/1 <1>
+{ "count": 5 }
 --------------------------------------------------
+// AUTOSENSE
+<1> Creates the `data` index, the `counters` mapping type, and a field
+    called `count` with datatype `long`.
 
-Pretty short, isn't it? Basically, everything is defaulted, especially the
-dynamic nature of the root object mapping. The default mapping can be
-overridden by specifying the `_default_` type when creating a new index.
+The automatic detection and addition of new types and fields is called
+_dynamic mapping_. The dynamic mapping rules can be customised to suit your
+purposes with:
 
-The dynamic creation of mappings for unmapped types can be completely
-disabled by setting `index.mapper.dynamic` to `false`.
+<<default-mapping,`_default_` mapping>>::
 
-The dynamic creation of fields within a type can be completely
-disabled by setting the `dynamic` property of the type to `strict`.
+    Configure the base mapping to be used for new mapping types.
 
-Here is a <<indices-put-mapping,Put Mapping>> example that
-disables dynamic field creation for a `tweet`:
+<<dynamic-field-mapping,Dynamic field mappings>>::
 
-[source,js]
---------------------------------------------------
-$ curl -XPUT 'http://localhost:9200/twitter/_mapping/tweet' -d '
-{
-    "tweet" : {
-        "dynamic": "strict",
-        "properties" : {
-            "message" : {"type" : "string", "store" : true }
-        }
-    }
-}
-'
---------------------------------------------------
+    The rules governing dynamic field detection.
 
-Here is how we can change the default
-<<mapping-date-format,date_formats>> used in the
-root and inner object types:
+<<dynamic-templates,Dynamic templates>>::
+
+    Custom rules to configure the mapping for dynamically added fields.
+
+TIP: <<indices-templates,Index templates>> allow you to configure the default
+mappings, settings, aliases, and warmers for new indices, whether created
+automatically or explicitly.
 
-[source,js]
---------------------------------------------------
-{
-    "_default_" : {
-        "dynamic_date_formats" : ["yyyy-MM-dd", "dd-MM-yyyy", "date_optional_time"]
-    }
-}
---------------------------------------------------
 
 [float]
-=== Unmapped fields in queries
+=== Disabling automatic type creation
 
-Queries and filters can refer to fields that don't exist in a mapping. Whether this
-is allowed is controlled by the `index.query.parse.allow_unmapped_fields` setting.
-This setting defaults to `true`. Setting it to `false` will disallow the usage of
-unmapped fields in queries.
+Automatic type creation can be disabled by setting the `index.mapper.dynamic`
+setting to `false`, either by setting the default value in the
+`config/elasticsearch.yml` file, or per-index as an index setting:
+
+[source,js]
+--------------------------------------------------
+PUT /_settings <1>
+{
+  "index.mapper.dynamic":false
+}
+--------------------------------------------------
+// AUTOSENSE
+<1> Disable automatic type creation for all indices.
+
+Regardless of the value of this setting, types can still be added explicitly
+when <<indices-create-index,creating an index>> or with the
+<<indices-put-mapping,PUT mapping>> API.
+
+
+include::dynamic/default-mapping.asciidoc[]
+
+include::dynamic/field-mapping.asciidoc[]
+
+include::dynamic/templates.asciidoc[]
 
-When registering a new <<search-percolate,percolator query>> or creating
-a <<filtered,filtered alias>> then the `index.query.parse.allow_unmapped_fields` setting
-is forcefully overwritten to disallowed unmapped fields.

docs/reference/mapping/dynamic/default-mapping.asciidoc

@@ -0,0 +1,82 @@
+[[default-mapping]]
+=== `_default_` mapping
+
+The default mapping, which will be used as the base mapping for any new
+mapping types, can be customised by adding a mapping type with the name
+`_default_` to an index, either when
+<<indices-create-index,creating the index>> or later on with the
+<<indices-put-mapping,PUT mapping>> API.
+
+
+[source,js]
+--------------------------------------------------
+PUT my_index
+{
+  "mappings": {
+    "_default_": { <1>
+      "_all": {
+        "enabled": false
+      }
+    },
+    "user": {}, <2>
+    "blogpost": { <3>
+      "_all": {
+        "enabled": true
+      }
+    }
+  }
+}
+--------------------------------------------------
+// AUTOSENSE
+<1> The `_default_` mapping defaults the <<mapping-all-field,`_all`>> field to disabled.
+<2> The `user` type inherits the settings from `_default_`.
+<3> The `blogpost` type overrides the defaults and enables the <<mapping-all-field,`_all`>> field.
+
+While the `_default_` mapping can be updated after an index has been created,
+the new defaults will only affect mapping types that are created afterwards.
+
+The `_default_` mapping can be used in conjunction with
+<<indices-templates,Index templates>> to control dynamically created types
+within automatically created indices:
+
+
+[source,js]
+--------------------------------------------------
+PUT _template/logging
+{
+  "template":   "logs-*", <1>
+  "settings": { "number_of_shards": 1 }, <2>
+  "mappings": {
+    "_default_": {
+      "_all": { <3>
+        "enabled": false
+      },
+      "dynamic_templates": [
+        {
+          "strings": { <4>
+            "match_mapping_type": "string",
+            "mapping": {
+              "type": "string",
+              "fields": {
+                "raw": {
+                  "type":  "string",
+                  "index": "not_analyzed",
+                  "ignore_above": 256
+                }
+              }
+            }
+          }
+        }
+      ]
+    }
+  }
+}
+
+PUT logs-2015.10.01/event/1
+{ "message": "error:16" }
+--------------------------------------------------
+// AUTOSENSE
+<1> The `logging` template will match any indices beginning with `logs-`.
+<2> Matching indices will be created with a single primary shard.
+<3> The `_all` field will be disabled by default for new type mappings.
+<4> String fields will be created with an `analyzed` main field, and a `not_analyzed` `.raw` field.

docs/reference/mapping/dynamic/field-mapping.asciidoc

@@ -0,0 +1,139 @@
+[[dynamic-field-mapping]]
+=== Dynamic field mapping
+
+By default, when a previously unseen field is found in a document,
+Elasticsearch will add the new field to the type mapping.   This behaviour can
+be disabled, both at the document and at the <<object,`object`>>  level, by
+setting the <<dynamic,`dynamic`>> parameter to `false` or to `strict`.
+
+Assuming `dynamic` field mapping is enabled, some simple rules are used to
+determine which datatype the field should have:
+
+[horizontal]
+*JSON datatype*::                   *Elasticsearch datatype*
+
+`null`::                            No field is added.
+`true` or `false`::                 <<boolean,`boolean`>> field
+floating{nbsp}point{nbsp}number::   <<number,`double`>> field
+integer::                           <<number,`long`>> field
+object::                            <<object,`object`>> field
+array::                             Depends on the first non-`null` value in the array.
+string::                            Either a <<date,`date`>> field
+                                        (if the value passes <<date-detection,date detection>>),
+                                    a <<number,`double`>> or <<number,`long`>> field
+                                        (if the value passes <<numeric-detection,numeric detection>>)
+                                    or an <<mapping-index,`analyzed`>> <<string,`string`>> field.
+
+These are the only <<mapping-types,field datatypes>> that are dynamically
+detected.  All other datatypes must be mapped explicitly.
+
+Besides the options listed below, dynamic field mapping rules can be further
+customised with <<dynamic-templates,`dynamic_templates`>>.
+
+[[date-detection]]
+==== Date detection
+
+If `date_detection` is enabled (default), then new string fields are checked
+to see whether their contents match any of the date patterns specified in
+`dynamic_date_formats`.  If a match is found, a new <<date,`date`>> field is
+added with the corresponding format.
+
+The default value for `dynamic_date_formats` is:
+
+&#91; <<strict-date-time,`"strict_date_optional_time"`>>,`"yyyy/MM/dd HH:mm:ss Z||yyyy/MM/dd Z"`]
+
+For example:
+
+
+[source,js]
+--------------------------------------------------
+PUT my_index/my_type/1
+{
+  "create_date": "2015/09/02"
+}
+
+GET my_index/_mapping <1>
+--------------------------------------------------
+// AUTOSENSE
+<1> The `create_date` field has been added as a <<date,`date`>>
+    field with the <<mapping-date-format,`format`>>: +
+    `"yyyy/MM/dd HH:mm:ss Z||yyyy/MM/dd Z"`.
+
+===== Disabling date detection
+
+Dynamic date dection can be disabled by setting `date_detection` to `false`:
+
+[source,js]
+--------------------------------------------------
+PUT my_index
+{
+  "mappings": {
+    "my_type": {
+      "date_detection": false
+    }
+  }
+}
+
+PUT my_index/my_type/1 <1>
+{
+  "create": "2015/09/02"
+}
+--------------------------------------------------
+// AUTOSENSE
+
+<1> The `create_date` field has been added as a <<string,`string`>> field.
+
+===== Customising detected date formats
+
+Alternatively, the `dynamic_date_formats` can be customised to support your
+own <<mapping-date-format,date formats>>:
+
+[source,js]
+--------------------------------------------------
+PUT my_index
+{
+  "mappings": {
+    "my_type": {
+      "dynamic_date_formats": ["MM/dd/yyyy"]
+    }
+  }
+}
+
+PUT my_index/my_type/1
+{
+  "create_date": "09/25/2015"
+}
+--------------------------------------------------
+// AUTOSENSE
+
+
+[[numeric-detection]]
+==== Numeric detection
+
+While JSON has support for native floating point and integer datatypes, some
+applications or languages may sometimes render numbers as strings. Usually the
+correct solution is to map these fields explicitly, but numeric detection
+(which is disabled by default) can be enabled to do this automatically:
+
+
+[source,js]
+--------------------------------------------------
+PUT my_index
+{
+  "mappings": {
+    "my_type": {
+      "numeric_detection": true
+    }
+  }
+}
+
+PUT my_index/my_type/1
+{
+  "my_float":   "1.0", <1>
+  "my_integer": "1" <2>
+}
+--------------------------------------------------
+// AUTOSENSE
+<1> The `my_float` field is added as a <<number,`double`>> field.
+<2> The `my_integer` field is added as a <<number,`long`>> field.
+

docs/reference/mapping/dynamic/templates.asciidoc

@@ -0,0 +1,251 @@
+[[dynamic-templates]]
+=== Dynamic templates
+
+Dynamic templates allow you to define custom mappings that can be applied to
+dynamically added fields based on:
+
+* the <<dynamic-mapping,datatype>> detected by Elasticsearch, with <<match-mapping-type,`match_mapping_type`>>.
+* the name of the field, with <<match-unmatch,`match` and `unmatch`>> or <<match-pattern,`match_pattern`>>.
+* the full dotted path to the field, with <<path-match-unmatch,`path_match` and `path_unmatch`>>.
+
+The original field name `{name}` and the detected datatype
+`{dynamic_type`} <<template-variables,template variables>> can be used in
+the mapping specification as placeholders.
+
+IMPORTANT: Dynamic field mappings are only added when a field contains a
+concrete value -- not `null` or an empty array. This means that if the
+`null_value` option  is used in a `dynamic_template`, it will only be applied
+after the first document  with a concrete value for the field has been
+indexed.
+
+Dynamic templates are specified as an array of named objects:
+
+[source,js]
+--------------------------------------------------
+  "dynamic_templates": [
+    {
+      "my_template_name": { <1>
+        ...  match conditions ... <2>
+        "mapping": { ... } <3>
+      }
+    },
+    ...
+  ]
+--------------------------------------------------
+<1> The template name can be any string value.
+<2> The match conditions can include any of : `match_mapping_type`, `match`, `match_pattern`, `unmatch`, `match_path`, `unmatch_path`.
+<3> The mapping that the matched field should use.
+
+
+Templates are processed in order -- the first matching template wins. New
+templates can be appended to the end of the list with the
+<<indices-put-mapping,PUT mapping>> API.  If a new template has the same
+name as an existing template, it will replace the old version.
+
+[[match-mapping-type]]
+==== `match_mapping_type`
+
+The `match_mapping_type` matches on the datatype detected by
+<<dynamic-field-mapping,dynamic field mapping>>, in other words, the datatype
+that Elasticsearch thinks the field should have.  Only the following datatypes
+can be automatically detected: `boolean`, `date`, `double`, `long`, `object`,
+`string`.  It also accepts `*` to match all datatypes.
+
+For example, if we wanted to map all integer fields as `integer` instead of
+`long`, and all `string` fields as both `analyzed` and `not_analyzed`, we
+could use the following template:
+
+[source,js]
+--------------------------------------------------
+PUT my_index
+{
+  "mappings": {
+    "my_type": {
+      "dynamic_templates": [
+        {
+          "integers": {
+            "match_mapping_type": "long",
+            "mapping": {
+              "type": "integer"
+            }
+          }
+        },
+        {
+          "strings": {
+            "match_mapping_type": "string",
+            "mapping": {
+              "type": "string",
+              "fields": {
+                "raw": {
+                  "type":  "string",
+                  "index": "not_analyzed",
+                  "ignore_above": 256
+                }
+              }
+            }
+          }
+        }
+      ]
+    }
+  }
+}
+
+PUT my_index/my_type/1
+{
+  "my_integer": 5, <1>
+  "my_string": "Some string" <2>
+}
+
+--------------------------------------------------
+// AUTOSENSE
+<1> The `my_integer` field is mapped as an `integer`.
+<2> The `my_string` field is mapped as an analyzed `string`, with a `not_analyzed` <<multi-fields,multi field>>.
+
+
+[[match-unmatch]]
+==== `match` and `unmatch`
+
+The `match` parameter uses a pattern to match on the fieldname, while
+`unmatch` uses a pattern to exclude fields matched by `match`.
+
+The following example matches all `string` fields whose name starts with
+`long_` (except for those which end with `_text`) and maps them as `long`
+fields:
+
+
+[source,js]
+--------------------------------------------------
+PUT my_index
+{
+  "mappings": {
+    "my_type": {
+      "dynamic_templates": [
+        {
+          "longs_as_strings": {
+            "match_mapping_type": "string",
+            "match":   "long_*",
+            "unmatch": "*_text",
+            "mapping": {
+              "type": "long"
+            }
+          }
+        }
+      ]
+    }
+  }
+}
+
+PUT my_index/my_type/1
+{
+  "long_num": "5", <1>
+  "long_text": "foo" <2>
+}
+--------------------------------------------------
+// AUTOSENSE
+<1> The `long_num` field is mapped as a `long`.
+<2> The `long_text` field uses the default `string` mapping.
+
+[[match-pattern]]
+==== `match_pattern`
+
+The `match_pattern` parameter behaves just like the `match` parameter, but
+supports full Java regular expression matching on the field name instead of
+simple wildcards, for instance:
+
+[source,js]
+--------------------------------------------------
+  "match_pattern": "^profit_\d+$"
+--------------------------------------------------
+
+[[path-match-unmatch]]
+==== `path_match` and `path_unmatch`
+
+The `path_match` and `path_unmatch` parameters work in the same way as `match`
+and `unmatch`, but operate on the full dotted path to the field, not just the
+final name, e.g. `some_object.*.some_field`.
+
+This example copies the values of any fields in the `name` object to the
+top-level `full_name` field, except for the `middle` field:
+
+[source,js]
+--------------------------------------------------
+PUT my_index
+{
+  "mappings": {
+    "my_type": {
+      "dynamic_templates": [
+        {
+          "full_name": {
+            "path_match":   "name.*",
+            "path_unmatch": "*.middle",
+            "mapping": {
+              "type":       "string",
+              "copy_to":    "full_name"
+            }
+          }
+        }
+      ]
+    }
+  }
+}
+
+PUT my_index/my_type/1
+{
+  "name": {
+    "first":  "Alice",
+    "middle": "Mary",
+    "last":   "White"
+  }
+}
+--------------------------------------------------
+// AUTOSENSE
+
+[[template-variables]]
+==== `{name}` and `{dynamic_type}`
+
+The `{name}` and `{dynamic_type}` placeholders are replaced in the `mapping`
+with the field name and detected dynamic type.  The following example sets all
+string fields to use an <<analyzer,`analyzer`>> with the same name as the
+field, and disables <<doc-values,`doc_values`>> for all non-string fields:
+
+[source,js]
+--------------------------------------------------
+PUT my_index
+{
+  "mappings": {
+    "my_type": {
+      "dynamic_templates": [
+        {
+          "named_analyzers": {
+            "match_mapping_type": "string",
+            "match": "*",
+            "mapping": {
+              "type": "string",
+              "analyzer": "{name}"
+            }
+          }
+        },
+        {
+          "no_doc_values": {
+            "match_mapping_type":"*",
+            "mapping": {
+              "type": "{dynamic_type}",
+              "doc_values": false
+            }
+          }
+        }
+      ]
+    }
+  }
+}
+
+PUT my_index/my_type/1
+{
+  "english": "Some English text", <1>
+  "count":   5 <2>
+}
+--------------------------------------------------
+// AUTOSENSE
+<1> The `english` field is mapped as a `string` field with the `english` analyzer.
+<2> The `count` field is mapped as a `long` field with `doc_values` disabled
+

docs/reference/mapping/fielddata_formats.asciidoc

@@ -1,257 +0,0 @@
-[[fielddata-formats]]
-== Fielddata formats
-
-The field data format controls how field data should be stored.
-
-Depending on the field type, there might be several field data types
-available. In particular, string, geo-point and numeric types support the `doc_values`
-format which allows for computing the field data data-structures at indexing
-time and storing them on disk. Although it will make the index larger and may
-be slightly slower, this implementation will be more near-realtime-friendly
-and will require much less memory from the JVM than other implementations.
-
-Here is an example of how to configure the `tag` field to use the `paged_bytes` field
-data format.
-
-[source,js]
---------------------------------------------------
-{
-    "tag": {
-        "type":      "string",
-        "fielddata": {
-            "format": "paged_bytes"
-        }
-    }
-}
---------------------------------------------------
-
-It is possible to change the field data format (and the field data settings
-in general) on a live index by using the update mapping API.
-
-[float]
-=== String field data types
-
-`paged_bytes` (default on analyzed string fields)::
-    Stores unique terms sequentially in a large buffer and maps documents to
-    the indices of the terms they contain in this large buffer.
-
-`doc_values` (default when index is set to `not_analyzed`)::
-    Computes and stores field data data-structures on disk at indexing time.
-    Lowers memory usage but only works on non-analyzed strings (`index`: `no` or
-    `not_analyzed`).
-
-[float]
-=== Numeric field data types
-
-`array`::
-    Stores field values in memory using arrays.
-
-`doc_values` (default unless doc values are disabled)::
-    Computes and stores field data data-structures on disk at indexing time.
-
-[float]
-=== Geo point field data types
-
-`array`::
-    Stores latitudes and longitudes in arrays.
-
-`doc_values` (default unless doc values are disabled)::
-    Computes and stores field data data-structures on disk at indexing time.
-
-[float]
-[[global-ordinals]]
-=== Global ordinals
-
-Global ordinals is a data-structure on top of field data, that maintains an
-incremental numbering for all the terms in field data in a lexicographic order.
-Each term has a unique number and the number of term 'A' is lower than the number
-of term 'B'. Global ordinals are only supported on string fields.
-
-Field data on string also has ordinals, which is a unique numbering for all terms
-in a particular segment and field. Global ordinals just build on top of this,
-by providing a mapping between the segment ordinals and the global ordinals.
-The latter being unique across the entire shard.
-
-Global ordinals can be beneficial in search features that use segment ordinals already
-such as the terms aggregator to improve the execution time. Often these search features
-need to merge the segment ordinal results to a cross segment terms result. With
-global ordinals this mapping happens during field data load time instead of during each
-query execution. With global ordinals search features only need to resolve the actual
-term when building the (shard) response, but during the execution there is no need
-at all to use the actual terms and the unique numbering global ordinals provided is
-sufficient and improves the execution time.
-
-Global ordinals for a specified field are tied to all the segments of a shard (Lucene index),
-which is different than for field data for a specific field which is tied to a single segment.
-For this reason global ordinals need to be rebuilt in its entirety once new segments
-become visible. This one time cost would happen anyway without global ordinals, but
-then it would happen for each search execution instead!
-
-The loading time of global ordinals depends on the number of terms in a field, but in general
-it is low, since it source field data has already been loaded. The memory overhead of global
-ordinals is a small because it is very efficiently compressed. Eager loading of global ordinals
-can move the loading time from the first search request, to the refresh itself.
-
-[float]
-[[fielddata-loading]]
-=== Fielddata loading
-
-By default, field data is loaded lazily, ie. the first time that a query that
-requires them is executed. However, this can make the first requests that
-follow a merge operation quite slow since fielddata loading is a heavy
-operation.
-
-It is possible to force field data to be loaded and cached eagerly through the
-`loading` setting of fielddata:
-
-[source,js]
---------------------------------------------------
-{
-    "category": {
-        "type":      "string",
-        "fielddata": {
-            "loading": "eager"
-        }
-    }
-}
---------------------------------------------------
-
-Global ordinals can also be eagerly loaded:
-
-[source,js]
---------------------------------------------------
-{
-    "category": {
-        "type":      "string",
-        "fielddata": {
-            "loading": "eager_global_ordinals"
-        }
-    }
-}
---------------------------------------------------
-
-With the above setting both field data and global ordinals for a specific field
-are eagerly loaded.
-
-[float]
-==== Disabling field data loading
-
-Field data can take a lot of RAM so it makes sense to disable field data
-loading on the fields that don't need field data, for example those that are
-used for full-text search only. In order to disable field data loading, just
-change the field data format to `disabled`. When disabled, all requests that
-will try to load field data, e.g. when they include aggregations and/or sorting,
-will return an error.
-
-[source,js]
---------------------------------------------------
-{
-    "text": {
-        "type":      "string",
-        "fielddata": {
-            "format": "disabled"
-        }
-    }
-}
---------------------------------------------------
-
-The `disabled` format is supported by all field types.
-
-[float]
-[[field-data-filtering]]
-=== Filtering fielddata
-
-It is possible to control which field values are loaded into memory,
-which is particularly useful for string fields. When specifying the
-<<mapping-core-types,mapping>> for a field, you
-can also specify a fielddata filter.
-
-Fielddata filters can be changed using the
-<<indices-put-mapping,PUT mapping>>
-API. After changing the filters, use the
-<<indices-clearcache,Clear Cache>> API
-to reload the fielddata using the new filters.
-
-[float]
-==== Filtering by frequency:
-
-The frequency filter allows you to only load terms whose frequency falls
-between a `min` and `max` value, which can be expressed an absolute
-number (when the number is bigger than 1.0) or as a percentage
-(eg `0.01` is `1%` and `1.0` is `100%`). Frequency is calculated
-*per segment*. Percentages are based on the number of docs which have a
-value for the field, as opposed to all docs in the segment.
-
-Small segments can be excluded completely by specifying the minimum
-number of docs that the segment should contain with `min_segment_size`:
-
-[source,js]
---------------------------------------------------
-{
-    "tag": {
-        "type":      "string",
-        "fielddata": {
-            "filter": {
-                "frequency": {
-                    "min":              0.001,
-                    "max":              0.1,
-                    "min_segment_size": 500
-                }
-            }
-        }
-    }
-}
---------------------------------------------------
-
-[float]
-==== Filtering by regex
-
-Terms can also be filtered by regular expression - only values which
-match the regular expression are loaded. Note: the regular expression is
-applied to each term in the field, not to the whole field value. For
-instance, to only load hashtags from a tweet, we can use a regular
-expression which matches terms beginning with `#`:
-
-[source,js]
---------------------------------------------------
-{
-    "tweet": {
-        "type":      "string",
-        "analyzer":  "whitespace"
-        "fielddata": {
-            "filter": {
-                "regex": {
-                    "pattern": "^#.*"
-                }
-            }
-        }
-    }
-}
---------------------------------------------------
-
-[float]
-==== Combining filters
-
-The `frequency` and `regex` filters can be combined:
-
-[source,js]
---------------------------------------------------
-{
-    "tweet": {
-        "type":      "string",
-        "analyzer":  "whitespace"
-        "fielddata": {
-            "filter": {
-                "regex": {
-                    "pattern":          "^#.*",
-                },
-                "frequency": {
-                    "min":              0.001,
-                    "max":              0.1,
-                    "min_segment_size": 500
-                }
-            }
-        }
-    }
-}
---------------------------------------------------

docs/reference/mapping/fields.asciidoc

@@ -5,7 +5,8 @@ Each document has metadata associated with it, such as the `_index`, mapping
 <<mapping-type-field,`_type`>>, and `_id` meta-fields.  The behaviour of some of these meta-fields
 can be customised when a mapping type is created.
 
-The meta-fields are:
+[float]
+=== Identity meta-fields
 
 [horizontal]
 <<mapping-index-field,`_index`>>::
@@ -18,16 +19,26 @@ The meta-fields are:
 
 <<mapping-type-field,`_type`>>::
 
-    The document's <<all-mapping-types,mapping type>>.
+    The document's <<mapping-type,mapping type>>.
 
 <<mapping-id-field,`_id`>>::
 
     The document's ID.
 
+[float]
+=== Document source meta-fields
+
 <<mapping-source-field,`_source`>>::
 
     The original JSON representing the body of the document.
 
+<<mapping-size-field,`_size`>>::
+
+    The size of the `_source` field in bytes.
+
+[float]
+=== Indexing meta-fields
+
 <<mapping-all-field,`_all`>>::
 
     A _catch-all_  field that indexes the values of all other fields.
@@ -36,18 +47,6 @@ The meta-fields are:
 
     All fields in the document which contain non-null values.
 
-<<mapping-parent-field,`_parent`>>::
-
-    Used to create a parent-child relationship between two mapping types.
-
-<<mapping-routing-field,`_routing`>>::
-
-    A custom routing value which routes a document to a particular shard.
-
-<<mapping-size-field,`_size`>>::
-
-    The size of the `_source` field in bytes.
-
 <<mapping-timestamp-field,`_timestamp`>>::
 
     A timestamp associated with the document, either specified manually or auto-generated.
@@ -56,27 +55,49 @@ The meta-fields are:
 
     How long a document should live before it is automatically deleted.
 
-include::fields/index-field.asciidoc[]
+[float]
+=== Routing meta-fields
 
-include::fields/uid-field.asciidoc[]
+<<mapping-parent-field,`_parent`>>::
 
-include::fields/type-field.asciidoc[]
+    Used to create a parent-child relationship between two mapping types.
+
+<<mapping-routing-field,`_routing`>>::
+
+    A custom routing value which routes a document to a particular shard.
+
+[float]
+=== Other meta-field
+
+<<mapping-meta-field,`_meta`>>::
+
+    Application specific metadata.
 
-include::fields/id-field.asciidoc[]
 
-include::fields/source-field.asciidoc[]
 
 include::fields/all-field.asciidoc[]
 
 include::fields/field-names-field.asciidoc[]
 
+include::fields/id-field.asciidoc[]
+
+include::fields/index-field.asciidoc[]
+
+include::fields/meta-field.asciidoc[]
+
 include::fields/parent-field.asciidoc[]
 
 include::fields/routing-field.asciidoc[]
 
 include::fields/size-field.asciidoc[]
 
+include::fields/source-field.asciidoc[]
+
 include::fields/timestamp-field.asciidoc[]
 
 include::fields/ttl-field.asciidoc[]
 
+include::fields/type-field.asciidoc[]
+
+include::fields/uid-field.asciidoc[]
+

docs/reference/mapping/fields/all-field.asciidoc

@@ -151,82 +151,18 @@ PUT my_index
 <1> The `_all` field is disabled for the `my_type` type.
 <2> The `query_string` query will default to querying the `content` field in this index.
 
-[[include-in-all]]
-==== Including specific fields in `_all`
+[[excluding-from-all]]
+==== Excluding fields from `_all`
 
 Individual fields can be included or excluded from the `_all` field with the
-`include_in_all` setting, which defaults to `true`:
+<<include-in-all,`include_in_all`>> setting.
 
-[source,js]
---------------------------------
-PUT my_index
-{
-  "mappings": {
-    "my_type": {
-      "properties": {
-        "title": { <1>
-          "type": "string"
-        }
-        "content": { <1>
-          "type": "string"
-        },
-        "date": { <2>
-          "type": "date",
-          "include_in_all": false
-        }
-      }
-    }
-  }
-}
---------------------------------
-// AUTOSENSE
-
-<1> The `title` and `content` fields with be included in the `_all` field.
-<2> The `date` field will not be included in the `_all` field.
-
-The `include_in_all` parameter can also be set at the type level and on
-<<mapping-object-type,`object`>> or <<mapping-nested-type,`nested`>> fields,
-in which case all sub-fields inherit that setting.  For instance:
-
-[source,js]
---------------------------------
-PUT my_index
-{
-  "mappings": {
-    "my_type": {
-      "include_in_all": false, <1>
-      "properties": {
-        "title":          { "type": "string" },
-        "author": {
-          "include_in_all": true, <2>
-          "properties": {
-            "first_name": { "type": "string" },
-            "last_name":  { "type": "string" }
-          }
-        },
-        "editor": {
-          "properties": {
-            "first_name": { "type": "string" }, <3>
-            "last_name":  { "type": "string", "include_in_all": true } <3>
-          }
-        }
-      }
-    }
-  }
-}
---------------------------------
-// AUTOSENSE
-
-<1> All fields in `my_type` are excluded from `_all`.
-<2> The `author.first_name` and `author.last_name` fields are included in `_all`.
-<3> Only the `editor.last_name` field is included in `_all`.
-    The `editor.first_name` inherits the type-level setting and is excluded.
 
 [[all-field-and-boosting]]
 ==== Index boosting and the `_all` field
 
-Individual fields can be _boosted_  at index time, with the `boost` parameter.
-The `_all` field takes these boosts into account:
+Individual fields can be _boosted_ at index time, with the <<index-boost,`boost`>>
+parameter. The `_all` field takes these boosts into account:
 
 [source,js]
 --------------------------------

docs/reference/mapping/fields/id-field.asciidoc

@@ -2,8 +2,8 @@
 === `_id` field
 
 Each document indexed is associated with a <<mapping-type-field,`_type`>> (see
-<<all-mapping-types,Mapping Types>>) and an <<mapping-id-field,`_id`>>.  The
-`_id` field is not indexed as its value can be derived automatically from the
+<<mapping-type>>) and an <<mapping-id-field,`_id`>>.  The `_id` field is not
+indexed as its value can be derived automatically from the
 <<mapping-uid-field,`_uid`>> field.
 
 The value of the `_id` field is accessible in queries and scripts, but _not_

docs/reference/mapping/fields/meta-field.asciidoc

@@ -0,0 +1,30 @@
+[[mapping-meta-field]]
+=== `_meta` field
+
+Each mapping type can have custom meta data associated with it. These are not
+used at all by Elasticsearch, but can be used to store application-specific
+metadata, such as the class that a document belongs to:
+
+[source,js]
+--------------------------------------------------
+PUT my_index
+{
+  "mappings": {
+    "user": {
+      "_meta": { <1>
+        "class": "MyApp::User",
+        "version": {
+          "min": "1.0",
+          "max": "1.3"
+        }
+      }
+    }
+  }
+}
+--------------------------------------------------
+// AUTOSENSE
+<1> This `_meta` info can be retrieved with the
+    <<indices-get-mapping,GET mapping>> API.
+
+The `_meta` field can be updated on an existing type using the
+<<indices-put-mapping,PUT mapping>> API.

docs/reference/mapping/fields/source-field.asciidoc

@@ -78,8 +78,7 @@ stored.
 WARNING: Removing fields from the `_source` has similar downsides to disabling
 `_source`, especially the fact that you cannot reindex documents from one
 Elasticsearch index to another. Consider using
-<<search-request-source-filtering,source filtering>> or a
-<<mapping-transform,transform script>> instead.
+<<search-request-source-filtering,source filtering>> instead.
 
 The `includes`/`excludes` parameters (which also accept wildcards) can be used
 as follows:

docs/reference/mapping/fields/ttl-field.asciidoc

@@ -1,5 +1,5 @@
 [[mapping-ttl-field]]
-=== `_ttl`
+=== `_ttl` field
 
 Some types of documents, such as session data or special offers, come with an
 expiration date. The `_ttl` field allows you to specify the minimum time a

docs/reference/mapping/fields/type-field.asciidoc

@@ -2,8 +2,8 @@
 === `_type` field
 
 Each document indexed is associated with a <<mapping-type-field,`_type`>> (see
-<<all-mapping-types,Mapping Types>>) and an <<mapping-id-field,`_id`>>.  The
-`_type` field is indexed in order to make searching by type name fast.
+<<mapping-type>>) and an <<mapping-id-field,`_id`>>.  The `_type` field is
+indexed in order to make searching by type name fast.
 
 The value of the `_type` field is accessible in queries, aggregations,
 scripts, and when sorting:

docs/reference/mapping/fields/uid-field.asciidoc

@@ -2,8 +2,8 @@
 === `_uid` field
 
 Each document indexed is associated with a <<mapping-type-field,`_type`>> (see
-<<all-mapping-types,Mapping Types>>) and an <<mapping-id-field,`_id`>>.  These
-values are combined as `{type}#{id}` and indexed as the `_uid` field.
+<<mapping-type>>) and an <<mapping-id-field,`_id`>>.  These values are
+combined as `{type}#{id}` and indexed as the `_uid` field.
 
 The value of the `_uid` field is accessible in queries, aggregations, scripts,
 and when sorting:

docs/reference/mapping/meta.asciidoc

@@ -1,25 +0,0 @@
-[[mapping-meta]]
-== Meta
-
-Each mapping can have custom meta data associated with it. These are
-simple storage elements that are simply persisted along with the mapping
-and can be retrieved when fetching the mapping definition. The meta is
-defined under the `_meta` element, for example:
-
-[source,js]
---------------------------------------------------
-{
-    "tweet" : {
-        "_meta" : {
-            "attr1" : "value1",
-            "attr2" : {
-                "attr3" : "value3"
-            }
-        }
-    }
-}
---------------------------------------------------
-
-Meta can be handy for example for client libraries that perform
-serialization and deserialization to store its meta model (for example,
-the class the document maps to).

docs/reference/mapping/params.asciidoc

@@ -0,0 +1,100 @@
+[[mapping-params]]
+== Mapping parameters
+
+The following pages provide detailed explanations of the various mapping
+parameters that are used by <<mapping-types,field mappings>>:
+
+
+The following mapping parameters are common to some or all field datatypes:
+
+* <<analyzer,`analyzer`>>
+* <<index-boost,`boost`>>
+* <<coerce,`coerce`>>
+* <<copy-to,`copy_to`>>
+* <<doc-values,`doc_values`>>
+* <<dynamic,`dynamic`>>
+* <<enabled,`enabled`>>
+* <<fielddata,`fielddata`>>
+* <<geohash,`geohash`>>
+* <<geohash-precision,`geohash_precision`>>
+* <<geohash-prefix,`geohash_prefix`>>
+* <<mapping-date-format,`format`>>
+* <<ignore-above,`ignore_above`>>
+* <<ignore-malformed,`ignore_malformed`>>
+* <<include-in-all,`include_in_all`>>
+* <<index-options,`index_options`>>
+* <<lat-lon,`lat_lon`>>
+* <<mapping-index,`index`>>
+* <<multi-fields,`fields`>>
+* <<norms,`norms`>>
+* <<null-value,`null_value`>>
+* <<position-offset-gap,`position_offset_gap`>>
+* <<properties,`properties`>>
+* <<search-analyzer,`search_analyzer`>>
+* <<similarity,`similarity`>>
+* <<mapping-store,`store`>>
+* <<term-vector,`term_vector`>>
+
+
+include::params/analyzer.asciidoc[]
+
+include::params/boost.asciidoc[]
+
+include::params/coerce.asciidoc[]
+
+include::params/copy-to.asciidoc[]
+
+include::params/doc-values.asciidoc[]
+
+include::params/dynamic.asciidoc[]
+
+include::params/enabled.asciidoc[]
+
+include::params/fielddata.asciidoc[]
+
+include::params/format.asciidoc[]
+
+include::params/geohash.asciidoc[]
+
+include::params/geohash-precision.asciidoc[]
+
+include::params/geohash-prefix.asciidoc[]
+
+include::params/ignore-above.asciidoc[]
+
+include::params/ignore-malformed.asciidoc[]
+
+include::params/include-in-all.asciidoc[]
+
+include::params/index.asciidoc[]
+
+include::params/index-options.asciidoc[]
+
+include::params/lat-lon.asciidoc[]
+
+include::params/multi-fields.asciidoc[]
+
+include::params/norms.asciidoc[]
+
+include::params/null-value.asciidoc[]
+
+include::params/position-offset-gap.asciidoc[]
+
+include::params/precision-step.asciidoc[]
+
+include::params/properties.asciidoc[]
+
+include::params/search-analyzer.asciidoc[]
+
+include::params/similarity.asciidoc[]
+
+include::params/store.asciidoc[]
+
+include::params/term-vector.asciidoc[]
+
+
+[source,js]
+--------------------------------------------------
+--------------------------------------------------
+// AUTOSENSE
+

docs/reference/mapping/params/analyzer.asciidoc

@@ -0,0 +1,80 @@
+[[analyzer]]
+=== `analyzer`
+
+The values of <<mapping-index,`analyzed`>> string fields are passed through an
+<<analysis,analyzer>> to convert the string into a stream of _tokens_ or
+_terms_.  For instance, the string `"The quick Brown Foxes."` may, depending
+on which analyzer is used,  be analyzed to the tokens: `quick`, `brown`,
+`fox`.  These are the actual terms that are indexed for the field, which makes
+it possible to search efficiently for individual words _within_  big blobs of
+text.
+
+This analysis process needs to happen not just at index time, but also at
+query time: the query string needs to be passed through the same (or a
+similar) analyzer so that the terms that it tries to find are in the same
+format as those that exist in the index.
+
+Elasticsearch ships with a number of <<analysis-analyzers,pre-defined analyzers>>,
+which can be used without further configuration.  It also ships with many
+<<analysis-charfilters,character filters>>, <<analysis-tokenizers,tokenizers>>,
+and <<analysis-tokenfilters>> which can be combined to configure
+custom analyzers per index.
+
+Analyzers can be specified per-query, per-field or per-index. At index time,
+Elasticsearch will look for an analyzer in this order:
+
+* The `analyzer` defined in the field mapping.
+* An analyzer named `default` in the index settings.
+* The <<analysis-standard-analyzer,`standard`>> analyzer.
+
+At query time, there are a few more layers:
+
+* The `analyzer` defined in a <<full-text-queries,full-text query>>.
+* The `search_analyzer` defined in the field mapping.
+* The `analyzer` defined in the field mapping.
+* An analyzer named `default_search` in the index settings.
+* An analyzer named `default` in the index settings.
+* The <<analysis-standard-analyzer,`standard`>> analyzer.
+
+The easiest way to specify an analyzer for a particular field is to define it
+in the field mapping, as follows:
+
+[source,js]
+--------------------------------------------------
+PUT my_index
+{
+  "mappings": {
+    "my_type": {
+      "properties": {
+        "text": { <1>
+          "type": "string",
+          "fields": {
+            "english": { <2>
+              "type":     "string",
+              "analyzer": "english"
+            }
+          }
+        }
+      }
+    }
+  }
+}
+
+GET my_index/_analyze?field=text <3>
+{
+  "text": "The quick Brown Foxes."
+}
+
+GET my_index/_analyze?field=text.english <4>
+{
+  "text": "The quick Brown Foxes."
+}
+--------------------------------------------------
+// AUTOSENSE
+<1> The `text` field uses the default `standard` analyzer`.
+<2> The `text.english` <<multi-fields,multi-field>> uses the `english` analyzer, which removes stop words and applies stemming.
+<3> This returns the tokens: [ `the`, `quick`, `brown`, `foxes` ].
+<4> This returns the tokens: [ `quick`, `brown`, `fox` ].
+
+
+

docs/reference/mapping/params/boost.asciidoc

@@ -0,0 +1,59 @@
+[[index-boost]]
+=== `boost`
+
+Individual fields can be _boosted_ -- count more towards the relevance score
+-- at index time, with the `boost` parameter as follows:
+
+[source,js]
+--------------------------------------------------
+PUT my_index
+{
+  "mappings": {
+    "my_type": {
+      "properties": {
+        "title": {
+          "type": "string",
+          "boost": 2 <1>
+        },
+        "content": {
+          "type": "string"
+        }
+      }
+    }
+  }
+}
+--------------------------------------------------
+// AUTOSENSE
+
+<1> Matches on the `title` field will have twice the weight as those on the
+    `content` field, which has the default `boost` of `1.0`.
+
+Note that a `title` field will usually be shorter than a `content` field.  The
+default relevance calculation takes field length into account, so a short
+`title` field will have a higher natural boost than a long `content` field.
+
+[WARNING]
+.Why index time boosting is a bad idea
+==================================================
+
+We advise against using index time boosting for the following reasons:
+
+* You cannot change index-time `boost` values without reindexing all of your
+  documents.
+
+* Every query supports query-time boosting which achieves the same effect. The
+  difference is that you can tweak the `boost` value without having to reindex.
+
+* Index-time boosts are stored as part of the <<norms,`norm`>>, which is only one
+  byte.  This reduces the resolution of the field length normalization factor
+  which can lead to lower quality relevance calculations.
+
+==================================================
+
+The only advantage that index time boosting has is that it is copied with the
+value into the <<mapping-all-field,`_all`>> field. This means that, when
+querying the `_all` field, words that originated from the `title` field will
+have a higher score than words that originated in the `content` field.
+This functionality comes at a cost: queries on the `_all` field are slower
+when index-time boosting is used.
+

docs/reference/mapping/params/coerce.asciidoc

@@ -0,0 +1,89 @@
+[[coerce]]
+=== `coerce`
+
+Data is not always clean.  Depending on how it is produced a number might be
+rendered in the JSON body as a true JSON number, e.g. `5`, but it might also
+be rendered as a string, e.g. `"5"`.  Alternatively, a number that should be
+an integer might instead be rendered as a floating point, e.g. `5.0`, or even
+`"5.0"`.
+
+Coercion attempts to clean up dirty values to fit the datatype of a field.
+For instance:
+
+* Strings will be coerced to numbers.
+* Floating points will be truncated for integer values.
+* Lon/lat geo-points will be normalized to a standard -180:180 / -90:90 coordinate system.
+
+For instance:
+
+[source,js]
+--------------------------------------------------
+PUT my_index
+{
+  "mappings": {
+    "my_type": {
+      "properties": {
+        "number_one": {
+          "type": "integer"
+        },
+        "number_two": {
+          "type": "integer",
+          "coerce": false
+        }
+      }
+    }
+  }
+}
+
+PUT my_index/my_type/1
+{
+  "number_one": "10" <1>
+}
+
+PUT my_index/my_type/2
+{
+  "number_two": "10" <2>
+}
+--------------------------------------------------
+// AUTOSENSE
+<1> The `number_one` field will contain the integer `10`.
+<2> This document will be rejected because coercion is disabled.
+
+[[coerce-setting]]
+==== Index-level default
+
+The `index.mapping.coerce` setting can be set on the index level to disable
+coercion globally across all mapping types:
+
+[source,js]
+--------------------------------------------------
+PUT my_index
+{
+  "settings": {
+    "index.mapping.coerce": false
+  },
+  "mappings": {
+    "my_type": {
+      "properties": {
+        "number_one": {
+          "type": "integer"
+        },
+        "number_two": {
+          "type": "integer",
+          "coerce": true
+        }
+      }
+    }
+  }
+}
+
+PUT my_index/my_type/1
+{ "number_one": "10" } <1>
+
+PUT my_index/my_type/2
+{ "number_two": "10" } <2>
+--------------------------------------------------
+// AUTOSENSE
+<1> This document will be rejected because the `number_one` field inherits the index-level coercion setting.
+<2> The `number_two` field overrides the index level setting to enable coercion.
+

docs/reference/mapping/params/copy-to.asciidoc

@@ -0,0 +1,64 @@
+[[copy-to]]
+=== `copy_to`
+
+The `copy_to` parameter allows you to create custom
+<<mapping-all-field,`_all`>> fields.  In other words, the values of multiple
+fields can be copied into a group field, which can then be queried as a single
+field.  For instance, the `first_name` and `last_name` fields can be copied to
+the `full_name` field as follows:
+
+[source,js]
+--------------------------------------------------
+PUT /my_index
+{
+  "mappings": {
+    "my_type": {
+      "properties": {
+        "first_name": {
+          "type": "string",
+          "copy_to": "full_name" <1>
+        },
+        "last_name": {
+          "type": "string",
+          "copy_to": "full_name" <1>
+        },
+        "full_name": {
+          "type": "string"
+        }
+      }
+    }
+  }
+}
+
+PUT /my_index/my_type/1
+{
+  "first_name": "John",
+  "last_name": "Smith"
+}
+
+GET /my_index/_search
+{
+  "query": {
+    "match": {
+      "full_name": { <2>
+        "query": "John Smith",
+        "operator": "and"
+      }
+    }
+  }
+}
+
+--------------------------------------------------
+// AUTOSENSE
+<1>  The values of the `first_name` and `last_name` fields are copied to the
+     `full_name` field.
+
+<2>  The `first_name` and `last_name` fields can still be queried for the
+     first name and last name respectively, but the `full_name` field can be
+     queried for both first and last names.
+
+Some important points:
+
+* It is the field _value_ which is copied, not the terms (which result from the analysis process).
+* The original <<mapping-source-field,`_source`>> field will not be modified to show the copied values.
+* The same value can be copied to multiple fields, with `"copy_to": [ "field_1", "field_2" ]`

docs/reference/mapping/params/doc-values.asciidoc

@@ -0,0 +1,46 @@
+[[doc-values]]
+=== `doc_values`
+
+Most fields are <<mapping-index,indexed>> by default, which makes them
+searchable. The inverted index allows queries to look up the search term in
+unique sorted list of terms, and from that immediately have access to the list
+of documents that contain the term.
+
+Sorting, aggregations, and access to field values in scripts requires a
+different data access pattern.  Instead of lookup up the term and finding
+documents, we need to be able to look up the document and find the terms that
+is has in a field.
+
+Doc values are the on-disk data structure, built at document index time, which
+makes this data access pattern possible. Doc values are supported on almost
+all field types, with the __notable exception of `analyzed` string fields__.
+
+All fields which support doc values have them enabled by default. If you are
+sure that you don't need to sort or aggregate on a field, or access the field
+value from a script, you can disable doc values in order to save disk space:
+
+[source,js]
+--------------------------------------------------
+PUT my_index
+{
+  "mappings": {
+    "my_type": {
+      "properties": {
+        "status_code": { <1>
+          "type":       "string",
+          "index":      "not_analyzed"
+        },
+        "session_id": { <2>
+          "type":       "string",
+          "index":      "not_analyzed",
+          "doc_values": false
+        }
+      }
+    }
+  }
+}
+--------------------------------------------------
+// AUTOSENSE
+<1> The `status_code` field has `doc_values` enabled by default.
+<2> The `session_id` has `doc_values` disabled, but can still be queried.
+

docs/reference/mapping/params/dynamic.asciidoc

@@ -0,0 +1,87 @@
+[[dynamic]]
+=== `dynamic`
+
+By default, fields can be added _dynamically_ to a document, or to
+<<object,inner objects>> within a document, just by indexing a document
+containing the new field.  For instance:
+
+[source,js]
+--------------------------------------------------
+DELETE my_index <1>
+
+PUT my_index/my_type/1 <2>
+{
+  "username": "johnsmith",
+  "name": {
+    "first": "John",
+    "last": "Smith"
+  }
+}
+
+GET my_index/_mapping <3>
+
+PUT my_index/my_type/2 <4>
+{
+  "username": "marywhite",
+  "email": "mary@white.com",
+  "name": {
+    "first": "Mary",
+    "middle": "Alice",
+    "last": "White"
+  }
+}
+
+GET my_index/_mapping <5>
+--------------------------------------------------
+// AUTOSENSE
+<1> First delete the index, in case it already exists.
+<2> This document introduces the string field `username`, the object field
+    `name`, and two string fields under the `name` object which can be
+    referred to as `name.first` and `name.last`.
+<3> Check the mapping to verify the above.
+<4> This document adds two string fields: `email` and `name.middle`.
+<5> Check the mapping to verify the changes.
+
+The details of how new fields are detected and added to the mapping is explained in <<dynamic-mapping>>.
+
+The `dynamic` setting controls whether new fields can be added dynamically or
+not.  It accepts three settings:
+
+[horizontal]
+`true`::    Newly detected fields are added to the mapping. (default)
+`false`::   Newly detected fields are ignored.  New fields must be added explicitly.
+`strict`::  If new fields are detected, an exception is thrown and the document is rejected.
+
+The `dynamic` setting may be set at the mapping type level, and on each
+<<object,inner object>>.  Inner objects inherit the setting from their parent
+object or from the mapping type.  For instance:
+
+[source,js]
+--------------------------------------------------
+PUT my_index
+{
+  "mappings": {
+    "my_type": {
+      "dynamic": false, <1>
+      "properties": {
+        "user": { <2>
+          "properties": {
+            "name": {
+              "type": "string"
+            },
+            "social_networks": { <3>
+              "dynamic": true,
+              "properties": {}
+            }
+          }
+        }
+      }
+    }
+  }
+}
+--------------------------------------------------
+// AUTOSENSE
+<1> Dynamic mapping is disabled at the type level, so no new top-level fields will be added dynamically.
+<2> The `user` object inherits the type-level setting.
+<3> The `user.social_networks` object enables dynamic mapping, so new fields may be added to this inner object.
+

docs/reference/mapping/params/enabled.asciidoc

@@ -0,0 +1,94 @@
+[[enabled]]
+=== `enabled`
+
+Elasticsearch tries to index all of the fields you give it, but sometimes you
+want to just store the field without indexing it.  For instance, imagine that
+you are using Elasticsearch as a web session store.  You may want to index the
+session ID and last update time, but you don't need to query or run
+aggregations on the session data itself.
+
+The `enabled` setting, which can be applied only to the mapping type and to
+<<object,`object`>> fields, causes Elasticsearch to skip parsing of the
+contents of the field entirely.  The JSON can still be retrieved from the
+<<mapping-source-field,`_source`>> field, but it is not searchable or stored
+in any other way:
+
+[source,js]
+--------------------------------------------------
+PUT my_index
+{
+  "mappings": {
+    "session": {
+      "properties": {
+        "user_id": {
+          "type":  "string",
+          "index": "not_analyzed"
+        },
+        "last_updated": {
+          "type": "date"
+        },
+        "session_data": { <1>
+          "enabled": false
+        }
+      }
+    }
+  }
+}
+
+PUT my_index/session/session_1
+{
+  "user_id": "kimchy",
+  "session_data": { <2>
+    "arbitrary_object": {
+      "some_array": [ "foo", "bar", { "baz": 2 } ]
+    }
+  },
+  "last_updated": "2015-12-06T18:20:22"
+}
+
+PUT my_index/session/session_2
+{
+  "user_id": "jpountz",
+  "session_data": "none", <3>
+  "last_updated": "2015-12-06T18:22:13"
+}
+--------------------------------------------------
+// AUTOSENSE
+<1> The `session_data` field is disabled.
+<2> Any arbitrary data can be passed to the `session_data` field as it will be entirely ignored.
+<3> The `session_data` will also ignore values that are not JSON objects.
+
+The entire mapping type may be disabled as well, in which case the document is
+stored in the <<mapping-source-field,`_source`>> field, which means it can be
+retrieved, but none of its contents are indexed in any way:
+
+[source,js]
+--------------------------------------------------
+PUT my_index
+{
+  "mappings": {
+    "session": { <1>
+      "enabled": false
+    }
+  }
+}
+
+PUT my_index/session/session_1
+{
+  "user_id": "kimchy",
+  "session_data": {
+    "arbitrary_object": {
+      "some_array": [ "foo", "bar", { "baz": 2 } ]
+    }
+  },
+  "last_updated": "2015-12-06T18:20:22"
+}
+
+GET my_index/session/session_1 <2>
+
+GET my_index/_mapping <3>
+--------------------------------------------------
+// AUTOSENSE
+<1> The entire `session` mapping type is disabled.
+<2> The document can be retrieved.
+<3> Checking the mapping reveals that no fields have been added.

docs/reference/mapping/params/fielddata.asciidoc

@@ -0,0 +1,225 @@
+[[fielddata]]
+=== `fielddata`
+
+Most fields are <<mapping-index,indexed>> by default, which makes them
+searchable. The inverted index allows queries to look up the search term in
+unique sorted list of terms, and from that immediately have access to the list
+of documents that contain the term.
+
+Sorting, aggregations, and access to field values in scripts requires a
+different data access pattern.  Instead of lookup up the term and finding
+documents, we need to be able to look up the document and find the terms that
+is has in a field.
+
+Most fields can use index-time, on-disk <<doc-values,`doc_values`>> to support
+this type of data access pattern, but `analyzed` string fields do not support
+`doc_values`.
+
+Instead, `analyzed` strings use a query-time data structure called
+`fielddata`.  This data structure is built on demand the first time that a
+field is used for aggregations, sorting, or is accessed in a script.  It is built
+by reading the entire inverted index for each segment from disk, inverting the
+term ↔︎ document relationship, and storing the result in memory, in the
+JVM heap.
+
+
+Loading fielddata is an expensive process so, once it has been loaded, it
+remains in memory for the lifetime of the segment.
+
+[WARNING]
+.Fielddata can fill up your heap space
+==============================================================================
+Fielddata can consume a lot of heap space, especially when loading high
+cardinality `analyzed` string fields.  Most of the time, it doesn't make sense
+to sort or aggregate on `analyzed` string fields (with the notable exception
+of the
+<<search-aggregations-bucket-significantterms-aggregation,`significant_terms`>>
+aggregation).  Always think about whether a `not_analyzed` field (which can
+use `doc_values`) would be  a better fit for your use case.
+==============================================================================
+
+[[fielddata-format]]
+==== `fielddata.format`
+
+For `analyzed` string fields, the fielddata `format` controls whether
+fielddata should be enabled or not.  It accepts: `disabled` and `paged_bytes`
+(enabled, which is the default).  To disable fielddata loading, you can use
+the following mapping:
+
+[source,js]
+--------------------------------------------------
+PUT my_index
+{
+  "mappings": {
+    "my_type": {
+      "properties": {
+        "text": {
+          "type": "string",
+          "fielddata": {
+            "format": "disabled" <1>
+          }
+        }
+      }
+    }
+  }
+}
+--------------------------------------------------
+// AUTOSENSE
+<1> The `text` field cannot be used for sorting, aggregations, or in scripts.
+
+.Fielddata and other datatypes
+[NOTE]
+==================================================
+
+Historically, other field datatypes also used fielddata, but this has been replaced
+by index-time, disk-based <<doc-values,`doc_values`>>.
+
+==================================================
+
+
+[[fielddata-loading]]
+==== `fielddata.loading`
+
+This per-field setting controls when fielddata is loaded into memory. It
+accepts three options:
+
+[horizontal]
+`lazy`::
+
+    Fielddata is only loaded into memory when it is needed. (default)
+
+`eager`::
+
+    Fielddata is loaded into memory before a new search segment becomes
+    visible to search.  This can reduce the latency that a user may experience
+    if their search request has to trigger lazy loading from a big segment.
+
+`eager_global_ordinals`::
+
+    Loading fielddata into memory is only part of the work that is required.
+    After loading the fielddata for each segment, Elasticsearch builds the
+    <<global-ordinals>> data structure to make a list of all unique terms
+    across all the segments in a shard.  By default, global ordinals are built
+    lazily.  If the field has a very high cardinality, global ordinals may
+    take some time to build, in which case you can use eager loading instead.
+
+[[global-ordinals]]
+.Global ordinals
+*****************************************
+
+Global ordinals is a data-structure on top of fielddata and doc values, that
+maintains an incremental numbering for each unique term in a lexicographic
+order. Each term has a unique number and the number of term 'A' is lower than
+the number of term 'B'. Global ordinals are only supported on string fields.
+
+Fielddata and doc values also have ordinals, which is a unique numbering for all terms
+in a particular segment and field. Global ordinals just build on top of this,
+by providing a mapping between the segment ordinals and the global ordinals,
+the latter being unique across the entire shard.
+
+Global ordinals are used for features that use segment ordinals, such as
+sorting and the terms aggregation, to improve the execution time. A terms
+aggregation relies purely on global ordinals to perform the aggregation at the
+shard level, then converts global ordinals to the real term only for the final
+reduce phase, which combines results from different shards.
+
+Global ordinals for a specified field are tied to _all the segments of a
+shard_, while fielddata and doc values ordinals are tied to a single segment.
+which is different than for field data for a specific field which is tied to a
+single segment. For this reason global ordinals need to be entirely rebuilt
+whenever a once new segment becomes visible.
+
+The loading time of global ordinals depends on the number of terms in a field, but in general
+it is low, since it source field data has already been loaded. The memory overhead of global
+ordinals is a small because it is very efficiently compressed. Eager loading of global ordinals
+can move the loading time from the first search request, to the refresh itself.
+
+*****************************************
+
+[[field-data-filtering]]
+==== `fielddata.filter`
+
+Fielddata filtering can be used to reduce the number of terms loaded into
+memory, and thus reduce memory usage. Terms can be filtered by _frequency_ or
+by _regular expression_, or a combination of the two:
+
+Filtering by frequency::
++
+--
+
+The frequency filter allows you to only load terms whose term frequency falls
+between a `min` and `max` value, which can be expressed an absolute
+number (when the number is bigger than 1.0) or as a percentage
+(eg `0.01` is `1%` and `1.0` is `100%`). Frequency is calculated
+*per segment*. Percentages are based on the number of docs which have a
+value for the field, as opposed to all docs in the segment.
+
+Small segments can be excluded completely by specifying the minimum
+number of docs that the segment should contain with `min_segment_size`:
+
+[source,js]
+--------------------------------------------------
+PUT my_index
+{
+  "mappings": {
+    "my_type": {
+      "properties": {
+        "tag": {
+          "type": "string",
+          "fielddata": {
+            "filter": {
+              "frequency": {
+                "min": 0.001,
+                "max": 0.1,
+                "min_segment_size": 500
+              }
+            }
+          }
+        }
+      }
+    }
+  }
+}
+--------------------------------------------------
+// AUTOSENSE
+--
+
+Filtering by regex::
++
+--
+Terms can also be filtered by regular expression - only values which
+match the regular expression are loaded. Note: the regular expression is
+applied to each term in the field, not to the whole field value. For
+instance, to only load hashtags from a tweet, we can use a regular
+expression which matches terms beginning with `#`:
+
+[source,js]
+--------------------------------------------------
+PUT my_index
+{
+  "mappings": {
+    "my_type": {
+      "properties": {
+        "tweet": {
+          "type": "string",
+          "analyzer": "whitespace",
+          "fielddata": {
+            "filter": {
+              "regex": {
+                "pattern": "^#.*"
+              }
+            }
+          }
+        }
+      }
+    }
+  }
+}
+--------------------------------------------------
+// AUTOSENSE
+--
+
+These filters can be updated on an existing field mapping and will take
+effect the next time the fielddata for a segment is loaded. Use the
+<<indices-clearcache,Clear Cache>> API
+to reload the fielddata using the new filters.

docs/reference/mapping/params/format.asciidoc

@@ -0,0 +1,281 @@
+[[mapping-date-format]]
+=== `format`
+
+In JSON documents, dates are represented as strings. Elasticsearch uses a set
+of preconfigured formats to recognize and parse these strings into a long
+value representing _milliseconds-since-the-epoch_ in UTC.
+
+Besides the <<built-in-date-formats,built-in formats>>, your own
+<<custom-date-formats,custom formats>> can be specified using the familiar
+`yyyy/MM/dd` syntax:
+
+[source,js]
+--------------------------------------------------
+PUT my_index
+{
+  "mappings": {
+    "my_type": {
+      "properties": {
+        "date": {
+          "type":   "date",
+          "format": "yyyy-MM-dd"
+        }
+      }
+    }
+  }
+}
+--------------------------------------------------
+// AUTOSENSE
+
+Many APIs which support date values also support <<date-math,date math>>
+expressions, such as `now-1m/d` -- the current time, minus one month, rounded
+down to the nearest day.
+
+[[custom-date-formats]]
+==== Custom date formats
+
+Completely customizable date formats are supported.  The syntax for these is explained
+http://www.joda.org/joda-time/apidocs/org/joda/time/format/DateTimeFormat.html[in the Joda docs].
+
+[[built-in-date-formats]]
+==== Built In Formats
+
+Most of the below dates have a `strict` companion dates, which means, that
+year, month and day parts of the week must have prepending zeros in order
+to be valid. This means, that a date like `5/11/1` would not be valid, but
+you would need to specify the full date, which would be `2005/11/01` in this
+example. So instead of `date_optional_time` you would need to specify
+`strict_date_optional_time`.
+
+The following tables lists all the defaults ISO formats supported:
+
+`epoch_millis`::
+
+    A formatter for the number of milliseconds since the epoch. Note, that
+    this timestamp allows a max length of 13 chars, so dates older than 1653
+    and 2286 are not supported. You should use a different date formatter in
+    that case.
+
+`epoch_second`::
+
+    A formatter for the number of seconds since the epoch. Note, that this
+    timestamp allows a max length of 10 chars, so dates older than 1653 and
+    2286 are not supported. You should use a different date formatter in that
+    case.
+
+[[strict-date-time]]`date_optional_time` or `strict_date_optional_time`::
+
+    A generic ISO datetime parser where the date is mandatory and the time is
+    optional.
+    http://www.joda.org/joda-time/apidocs/org/joda/time/format/ISODateTimeFormat.html#dateOptionalTimeParser--[Full details here].
+
+`basic_date`::
+
+    A basic formatter for a full date as four digit year, two digit month of
+    year, and two digit day of month: `yyyyMMdd`.
+
+`basic_date_time`::
+
+    A basic formatter that combines a basic date and time, separated by a 'T':
+    `yyyyMMdd'T'HHmmss.SSSZ`.
+
+`basic_date_time_no_millis`::
+
+    A basic formatter that combines a basic date and time without millis,
+    separated by a 'T': `yyyyMMdd'T'HHmmssZ`.
+
+`basic_ordinal_date`::
+
+    A formatter for a full ordinal date, using a four digit year and three
+    digit dayOfYear: `yyyyDDD`.
+
+`basic_ordinal_date_time`::
+
+    A formatter for a full ordinal date and time, using a four digit year and
+    three digit dayOfYear: `yyyyDDD'T'HHmmss.SSSZ`.
+
+`basic_ordinal_date_time_no_millis`::
+
+    A formatter for a full ordinal date and time without millis, using a four
+    digit year and three digit dayOfYear: `yyyyDDD'T'HHmmssZ`.
+
+`basic_time`::
+
+    A basic formatter for a two digit hour of day, two digit minute of hour,
+    two digit second of minute, three digit millis, and time zone offset:
+    `HHmmss.SSSZ`.
+
+`basic_time_no_millis`::
+
+    A basic formatter for a two digit hour of day, two digit minute of hour,
+    two digit second of minute, and time zone offset: `HHmmssZ`.
+
+`basic_t_time`::
+
+    A basic formatter for a two digit hour of day, two digit minute of hour,
+    two digit second of minute, three digit millis, and time zone off set
+    prefixed by 'T': `'T'HHmmss.SSSZ`.
+
+`basic_t_time_no_millis`::
+
+    A basic formatter for a two digit hour of day, two digit minute of hour,
+    two digit second of minute, and time zone offset prefixed by 'T':
+    `'T'HHmmssZ`.
+
+`basic_week_date` or `strict_basic_week_date`::
+
+    A basic formatter for a full date as four digit weekyear, two digit week
+    of weekyear, and one digit day of week: `xxxx'W'wwe`.
+
+`basic_week_date_time` or `strict_basic_week_date_time`::
+
+    A basic formatter that combines a basic weekyear date and time, separated
+    by a 'T': `xxxx'W'wwe'T'HHmmss.SSSZ`.
+
+`basic_week_date_time_no_millis` or `strict_basic_week_date_time_no_millis`::
+
+    A basic formatter that combines a basic weekyear date and time without
+    millis, separated by a 'T': `xxxx'W'wwe'T'HHmmssZ`.
+
+`date` or `strict_date`::
+
+    A formatter for a full date as four digit year, two digit month of year,
+    and two digit day of month: `yyyy-MM-dd`.
+
+`date_hour` or `strict_date_hour`::
+
+    A formatter that combines a full date and two digit hour of day.
+
+`date_hour_minute` or `strict_date_hour_minute`::
+
+    A formatter that combines a full date, two digit hour of day, and two
+    digit minute of hour.
+
+`date_hour_minute_second` or `strict_date_hour_minute_second`::
+
+    A formatter that combines a full date, two digit hour of day, two digit
+    minute of hour, and two digit second of minute.
+
+`date_hour_minute_second_fraction` or `strict_date_hour_minute_second_fraction`::
+
+    A formatter that combines a full date, two digit hour of day, two digit
+    minute of hour, two digit second of minute, and three digit fraction of
+    second: `yyyy-MM-dd'T'HH:mm:ss.SSS`.
+
+`date_hour_minute_second_millis` or `strict_date_hour_minute_second_millis`::
+
+    A formatter that combines a full date, two digit hour of day, two digit
+    minute of hour, two digit second of minute, and three digit fraction of
+    second: `yyyy-MM-dd'T'HH:mm:ss.SSS`.
+
+`date_time` or `strict_date_time`::
+
+    A formatter that combines a full date and time, separated by a 'T': `yyyy-
+    MM-dd'T'HH:mm:ss.SSSZZ`.
+
+`date_time_no_millis` or `strict_date_time_no_millis`::
+
+    A formatter that combines a full date and time without millis, separated
+    by a 'T': `yyyy-MM-dd'T'HH:mm:ssZZ`.
+
+`hour` or `strict_hour`::
+
+    A formatter for a two digit hour of day.
+
+`hour_minute` or `strict_hour_minute`::
+
+    A formatter for a two digit hour of day and two digit minute of hour.
+
+`hour_minute_second` or `strict_hour_minute_second`::
+
+    A formatter for a two digit hour of day, two digit minute of hour, and two
+    digit second of minute.
+
+`hour_minute_second_fraction` or `strict_hour_minute_second_fraction`::
+
+    A formatter for a two digit hour of day, two digit minute of hour, two
+    digit second of minute, and three digit fraction of second: `HH:mm:ss.SSS`.
+
+`hour_minute_second_millis` or `strict_hour_minute_second_millis`::
+
+    A formatter for a two digit hour of day, two digit minute of hour, two
+    digit second of minute, and three digit fraction of second: `HH:mm:ss.SSS`.
+
+`ordinal_date` or `strict_ordinal_date`::
+
+    A formatter for a full ordinal date, using a four digit year and three
+    digit dayOfYear: `yyyy-DDD`.
+
+`ordinal_date_time` or `strict_ordinal_date_time`::
+
+    A formatter for a full ordinal date and time, using a four digit year and
+    three digit dayOfYear: `yyyy-DDD'T'HH:mm:ss.SSSZZ`.
+
+`ordinal_date_time_no_millis` or `strict_ordinal_date_time_no_millis`::
+
+    A formatter for a full ordinal date and time without millis, using a four
+    digit year and three digit dayOfYear: `yyyy-DDD'T'HH:mm:ssZZ`.
+
+`time` or `strict_time`::
+
+    A formatter for a two digit hour of day, two digit minute of hour, two
+    digit second of minute, three digit fraction of second, and time zone
+    offset: `HH:mm:ss.SSSZZ`.
+
+`time_no_millis` or `strict_time_no_millis`::
+
+    A formatter for a two digit hour of day, two digit minute of hour, two
+    digit second of minute, and time zone offset: `HH:mm:ssZZ`.
+
+`t_time` or `strict_t_time`::
+
+    A formatter for a two digit hour of day, two digit minute of hour, two
+    digit second of minute, three digit fraction of second, and time zone
+    offset prefixed by 'T': `'T'HH:mm:ss.SSSZZ`.
+
+`t_time_no_millis` or `strict_t_time_no_millis`::
+
+    A formatter for a two digit hour of day, two digit minute of hour, two
+    digit second of minute, and time zone offset prefixed by 'T': `'T'HH:mm:ssZZ`.
+
+`week_date` or `strict_week_date`::
+
+    A formatter for a full date as four digit weekyear, two digit week of
+    weekyear, and one digit day of week: `xxxx-'W'ww-e`.
+
+`week_date_time` or `strict_week_date_time`::
+
+    A formatter that combines a full weekyear date and time, separated by a
+    'T': `xxxx-'W'ww-e'T'HH:mm:ss.SSSZZ`.
+
+`week_date_time_no_millis` or `strict_week_date_time_no_millis`::
+
+    A formatter that combines a full weekyear date and time without millis,
+    separated by a 'T': `xxxx-'W'ww-e'T'HH:mm:ssZZ`.
+
+`weekyear` or `strict_weekyear`::
+
+    A formatter for a four digit weekyear.
+
+`weekyear_week` or `strict_weekyear_week`::
+
+    A formatter for a four digit weekyear and two digit week of weekyear.
+
+`weekyear_week_day` or `strict_weekyear_week_day`::
+
+    A formatter for a four digit weekyear, two digit week of weekyear, and one
+    digit day of week.
+
+`year` or `strict_year`::
+
+    A formatter for a four digit year.
+
+`year_month` or `strict_year_month`::
+
+    A formatter for a four digit year and two digit month of year.
+
+`year_month_day` or `strict_year_month_day`::
+
+    A formatter for a four digit year, two digit month of year, and two digit
+    day of month.
+

docs/reference/mapping/params/geohash-precision.asciidoc

@@ -0,0 +1,60 @@
+[[geohash-precision]]
+=== `geohash_precision`
+
+Geohashes are a form of lat/lon encoding which divides the earth up into
+a grid. Each cell in this grid is represented by a geohash string. Each
+cell in turn can be further subdivided into smaller cells which are
+represented by a longer string. So the longer the geohash, the smaller
+(and thus more accurate) the cell is.
+
+The `geohash_precision` setting controls the length of the geohash that is
+indexed when the <<geohash,`geohash`>> option is enabled, and the maximum
+geohash length when the <<geohash-prefix,`geohash_prefix`>> option is enabled.
+
+It accepts:
+
+* a number between 1 and 12 (default), which represents the length of the geohash.
+* a <<distance-units,distance>>, e.g. `1km`.
+
+If a distance is specified, it will be translated to the smallest
+geohash-length that will provide the requested resolution.
+
+For example:
+
+[source,js]
+--------------------------------------------------
+PUT my_index
+{
+  "mappings": {
+    "my_type": {
+      "properties": {
+        "location": {
+          "type": "geo_point",
+          "geohash_prefix": true,
+          "geohash_precision": 6 <1>
+        }
+      }
+    }
+  }
+}
+
+PUT my_index/my_type/1
+{
+  "location": {
+    "lat": 41.12,
+    "lon": -71.34
+  }
+}
+
+GET my_index/_search?fielddata_fields=location.geohash
+{
+  "query": {
+    "term": {
+      "location.geohash": "drm3bt"
+    }
+  }
+}
+
+--------------------------------------------------
+// AUTOSENSE
+<1> A `geohash_precision` of 6 equates to geohash cells of approximately 1.26km x 0.6km

docs/reference/mapping/params/geohash-prefix.asciidoc

@@ -0,0 +1,64 @@
+[[geohash-prefix]]
+=== `geohash_prefix`
+
+Geohashes are a form of lat/lon encoding which divides the earth up into
+a grid. Each cell in this grid is represented by a geohash string. Each
+cell in turn can be further subdivided into smaller cells which are
+represented by a longer string. So the longer the geohash, the smaller
+(and thus more accurate) the cell is.
+
+While the <<geohash,`geohash`>> option enables indexing the geohash that
+corresponds to the lat/lon point, at the specified
+<<geohash-precision,precision>>, the `geohash_prefix` option will also
+index all the enclosing cells as well.
+
+For instance, a geohash of `drm3btev3e86` will index all of the following
+terms: [ `d`, `dr`, `drm`, `drm3`, `drm3b`, `drm3bt`, `drm3bte`, `drm3btev`,
+`drm3btev3`, `drm3btev3e`, `drm3btev3e8`, `drm3btev3e86` ].
+
+The geohash prefixes can be used with the
+<<query-dsl-geohash-cell-query,`geohash_cell` query>> to find points within a
+particular geohash, or its neighbours:
+
+
+[source,js]
+--------------------------------------------------
+PUT my_index
+{
+  "mappings": {
+    "my_type": {
+      "properties": {
+        "location": {
+          "type": "geo_point",
+          "geohash_prefix": true,
+          "geohash_precision": 6
+        }
+      }
+    }
+  }
+}
+
+PUT my_index/my_type/1
+{
+  "location": {
+    "lat": 41.12,
+    "lon": -71.34
+  }
+}
+
+GET my_index/_search?fielddata_fields=location.geohash
+{
+  "query": {
+    "geohash_cell": {
+      "location": {
+        "lat": 41.02,
+        "lon": -71.48
+      },
+      "precision": 4, <1>
+      "neighbors": true <1>
+    }
+  }
+}
+--------------------------------------------------
+// AUTOSENSE
+

docs/reference/mapping/params/geohash.asciidoc

@@ -0,0 +1,70 @@
+[[geohash]]
+=== `geohash`
+
+Geohashes are a form of lat/lon encoding which divides the earth up into
+a grid. Each cell in this grid is represented by a geohash string. Each
+cell in turn can be further subdivided into smaller cells which are
+represented by a longer string. So the longer the geohash, the smaller
+(and thus more accurate) the cell is.
+
+Because geohashes are just strings, they can be stored in an inverted
+index like any other string, which makes querying them very efficient.
+
+If you enable the `geohash` option, a `geohash` ``sub-field'' will be indexed
+as, eg `.geohash`. The length of the geohash is controlled by the
+<<geohash-precision,`geohash_precision`>> parameter.
+
+If the <<geohash-prefix,`geohash_prefix`>> option is enabled, the `geohash`
+option will be enabled automatically.
+
+For example:
+
+[source,js]
+--------------------------------------------------
+PUT my_index
+{
+  "mappings": {
+    "my_type": {
+      "properties": {
+        "location": {
+          "type": "geo_point", <1>
+          "geohash": true
+        }
+      }
+    }
+  }
+}
+
+
+PUT my_index/my_type/1
+{
+  "location": {
+    "lat": 41.12,
+    "lon": -71.34
+  }
+}
+
+GET my_index/_search?fielddata_fields=location.geohash <2>
+{
+  "query": {
+    "prefix": {
+      "location.geohash": "drm3b" <3>
+    }
+  }
+}
+--------------------------------------------------
+// AUTOSENSE
+<1> A `location.geohash` field will be indexed for each geo-point.
+<2> The geohash can be retrieved with <<doc-values,`doc_values`>>.
+<3> A <<query-dsl-prefix-query,`prefix`>> query can find all geohashes which start with a particular prefix.
+
+[WARNING]
+============================================
+
+A `prefix` query on geohashes is expensive.  Instead, consider using the
+<<geohash-prefix,`geohash_prefix`>> to pay the expense once at index time
+instead of on every query.
+
+============================================
+
+

docs/reference/mapping/params/ignore-above.asciidoc

@@ -0,0 +1,61 @@
+[[ignore-above]]
+=== `ignore_above`
+
+Strings longer than the `ignore_above` setting will not be processed by the
+<<analyzer,analyzer>> and will not be indexed. This is mainly useful for
+<<mapping-index,`not_analyzed`>> string fields, which are typically used for
+filtering, aggregations, and sorting.  These are structured fields and it
+doesn't usually make sense to allow very long terms to be indexed in these
+fields.
+
+[source,js]
+--------------------------------------------------
+PUT my_index
+{
+  "mappings": {
+    "my_type": {
+      "properties": {
+        "message": {
+          "type": "string",
+          "index": "not_analyzed",
+          "ignore_above": 20 <1>
+        }
+      }
+    }
+  }
+}
+
+PUT my_index/my_type/1 <2>
+{
+  "message": "Syntax error"
+}
+
+PUT my_index/my_type/2 <3>
+{
+  "message": "Syntax error with some long stacktrace"
+}
+
+GET _search <4>
+{
+  "aggs": {
+    "messages": {
+      "terms": {
+        "field": "message"
+      }
+    }
+  }
+}
+--------------------------------------------------
+// AUTOSENSE
+<1> This field will ignore any string longer than 20 characters.
+<2> This document is indexed successfully.
+<3> This document will be indexed, but without indexing the `message` field.
+<4> Search returns both documents, but only the first is present in the terms aggregation.
+
+This option is also useful for protecting against Lucene's term byte-length
+limit of `32766`.
+
+NOTE: The value for `ignore_above` is the _character count_, but Lucene counts
+bytes. If you use UTF-8 text with many non-ASCII characters, you may want to
+set the limit to `32766 / 3 = 10922` since UTF-8 characters may occupy at most
+3 bytes.

docs/reference/mapping/params/ignore-malformed.asciidoc

@@ -0,0 +1,83 @@
+[[ignore-malformed]]
+=== `ignore_malformed`
+
+Sometimes you don't have much control over the data that you receive.  One
+user may send a `login` field that is a <<date,`date`>>, and another sends a
+`login` field that is an email address.
+
+Trying to index the wrong datatype into a field throws an exception by
+default, and rejects the whole document.  The `ignore_malformed` parameter, if
+set to `true`, allows the exception to be ignored.  The malformed field is not
+indexed, but other fields in the document are processed normally.
+
+For example:
+
+[source,js]
+--------------------------------------------------
+PUT my_index
+{
+  "mappings": {
+    "my_type": {
+      "properties": {
+        "number_one": {
+          "type": "integer"
+        },
+        "number_two": {
+          "type": "integer",
+          "ignore_malformed": true
+        }
+      }
+    }
+  }
+}
+
+PUT my_index/my_type/1
+{
+  "text":       "Some text value",
+  "number_one": "foo" <1>
+}
+
+PUT my_index/my_type/2
+{
+  "text":       "Some text value",
+  "number_two": "foo" <2>
+}
+--------------------------------------------------
+// AUTOSENSE
+<1> This document will be rejected because `number_one` does not allow malformed values.
+<2> This document will have the `text` field indexed, but not the `number_two` field.
+
+
+[[ignore-malformed-setting]]
+==== Index-level default
+
+The `index.mapping.ignore_malformed` setting can be set on the index level to
+allow to ignore malformed content globally across all mapping types.
+
+[source,js]
+--------------------------------------------------
+PUT my_index
+{
+  "settings": {
+    "index.mapping.ignore_malformed": true <1>
+  },
+  "mappings": {
+    "my_type": {
+      "properties": {
+        "number_one": { <1>
+          "type": "byte"
+        },
+        "number_two": {
+          "type": "integer",
+          "ignore_malformed": false <2>
+        }
+      }
+    }
+  }
+}
+--------------------------------------------------
+// AUTOSENSE
+
+<1> The `number_one` field inherits the index-level setting.
+<2> The `number_two` field overrides the index-level setting to turn off `ignore_malformed`.
+

docs/reference/mapping/params/include-in-all.asciidoc

@@ -0,0 +1,83 @@
+[[include-in-all]]
+=== `include_in_all`
+
+The `include_in_all` parameter provides per-field control over which fields
+are included in the <<mapping-all-field,`_all`>> field.  It defaults to `true`, unless <<mapping-index,`index`>> is set to `no`.
+
+This example demonstrates how to exclude the `date` field from the `_all` field:
+
+[source,js]
+--------------------------------
+PUT my_index
+{
+  "mappings": {
+    "my_type": {
+      "properties": {
+        "title": { <1>
+          "type": "string"
+        }
+        "content": { <1>
+          "type": "string"
+        },
+        "date": { <2>
+          "type": "date",
+          "include_in_all": false
+        }
+      }
+    }
+  }
+}
+--------------------------------
+// AUTOSENSE
+
+<1> The `title` and `content` fields with be included in the `_all` field.
+<2> The `date` field will not be included in the `_all` field.
+
+The `include_in_all` parameter can also be set at the type level and on
+<<object,`object`>> or <<nested,`nested`>> fields, in which case all sub-
+fields inherit that setting.  For instance:
+
+[source,js]
+--------------------------------
+PUT my_index
+{
+  "mappings": {
+    "my_type": {
+      "include_in_all": false, <1>
+      "properties": {
+        "title":          { "type": "string" },
+        "author": {
+          "include_in_all": true, <2>
+          "properties": {
+            "first_name": { "type": "string" },
+            "last_name":  { "type": "string" }
+          }
+        },
+        "editor": {
+          "properties": {
+            "first_name": { "type": "string" }, <3>
+            "last_name":  { "type": "string", "include_in_all": true } <3>
+          }
+        }
+      }
+    }
+  }
+}
+--------------------------------
+// AUTOSENSE
+
+<1> All fields in `my_type` are excluded from `_all`.
+<2> The `author.first_name` and `author.last_name` fields are included in `_all`.
+<3> Only the `editor.last_name` field is included in `_all`.
+    The `editor.first_name` inherits the type-level setting and is excluded.
+
+[NOTE]
+.Multi-fields and `include_in_all`
+=================================
+
+The original field value is added to the `_all` field, not the terms produced
+by a field's analyzer.  For this reason, it makes no sense to set
+`include_in_all` to `true` on <<multi-fields,multi-fields>>, as each
+multi-field has exactly the same value as its parent.
+
+=================================

docs/reference/mapping/params/index-options.asciidoc

@@ -0,0 +1,70 @@
+[[index-options]]
+=== `index_options`
+
+The `index_options` parameter controls what information is added to the
+inverted index, for search and highlighting purposes.  It accepts the
+following settings:
+
+[horizontal]
+`docs`::
+
+    Only the doc number is indexed.  Can answer the question _Does this term
+    exist in this field?_
+
+`freqs`::
+
+    Doc number and term frequencies are indexed.  Term frequencies are used to
+    score repeated terms higher than single terms.
+
+`positions`::
+
+    Doc number, term frequencies, and term positions (or order) are indexed.
+    Positions can be used for
+    <<query-dsl-match-query-phrase,proximity or phrase queries>>.
+
+`offsets`::
+
+    Doc number, term frequencies, positions, and start and end character
+    offsets (which map the term back to the original string) are indexed.
+    Offsets are used by the <<postings-highlighter,postings highlighter>>.
+
+<<mapping-index,Analyzed>> string fields use `positions` as the default, and
+<<all other fields use `docs` as the default.
+
+[source,js]
+--------------------------------------------------
+PUT my_index
+{
+  "mappings": {
+    "my_type": {
+      "properties": {
+        "text": {
+          "type": "string",
+          "index_options": "offsets"
+        }
+      }
+    }
+  }
+}
+
+PUT my_index/my_type/1
+{
+  "text": "Quick brown fox"
+}
+
+GET my_index/_search
+{
+  "query": {
+    "match": {
+      "text": "brown fox"
+    }
+  },
+  "highlight": {
+    "fields": {
+      "text": {} <1>
+    }
+  }
+}
+--------------------------------------------------
+// AUTOSENSE
+<1> The `text` field will use the postings highlighter by default because `offsets` are indexed.

docs/reference/mapping/params/index.asciidoc

@@ -0,0 +1,48 @@
+[[mapping-index]]
+=== `index`
+
+The `index` option controls how field values are indexed and, thus, how they
+are searchable.  It accepts three values:
+
+[horizontal]
+`no`::
+
+    Do not add this field value to the index. With this setting, the field
+    will not be queryable.
+
+`not_analyzed`::
+
+    Add the field value to the index unchanged, as a single term.  This is the
+    default for all fields that support this option except for
+    <<string,`string`>> fields.  `not_analyzed` fields are usually used with
+    <<term-level-queries,term-level queries>> for structured search.
+
+`analyzed`::
+
+    This option applies only to `string` fields, for which it is the default.
+    The string field value is first <<analysis,analyzed>> to convert the
+    string into terms (e.g. a list of individual words), which are then
+    indexed.  At search time, the the query string is passed through
+    (<<search-analyzer,usually>>) the same analyzer to generate terms
+    in the same format as those in the index.  It is this process that enables
+    <<full-text-queries,full text search>>.
+
+For example, you can create a `not_analyzed` string field with the following:
+
+[source,js]
+--------------------------------------------------
+PUT /my_index
+{
+  "mappings": {
+    "my_type": {
+      "properties": {
+        "status_code": {
+          "type": "string",
+          "index": "not_analyzed"
+        }
+      }
+    }
+  }
+}
+--------------------------------------------------
+// AUTOSENSE

docs/reference/mapping/params/lat-lon.asciidoc

@@ -0,0 +1,63 @@
+[[lat-lon]]
+=== `lat_lon`
+
+<<geo-queries,Geo-queries>> are usually performed by plugging the value of
+each <<geo-point,`geo_point`>> field into a formula to determine whether it
+falls into the required area or not. Unlike most queries, the inverted index
+is not involved.
+
+Setting `lat_lon` to `true` causes the latitude and longitude values to be
+indexed as numeric fields (called `.lat` and `.lon`). These fields can be used
+by the <<query-dsl-geo-bounding-box-query,`geo_bounding_box`>> and
+<<query-dsl-geo-distance-query,`geo_distance`>> queries instead of
+performing in-memory calculations.
+
+[source,js]
+--------------------------------------------------
+PUT my_index
+{
+  "mappings": {
+    "my_type": {
+      "properties": {
+        "location": {
+          "type": "geo_point",
+          "lat_lon": true <1>
+        }
+      }
+    }
+  }
+}
+
+PUT my_index/my_type/1
+{
+  "location": {
+    "lat": 41.12,
+    "lon": -71.34
+  }
+}
+
+
+GET my_index/_search
+{
+  "query": {
+    "geo_distance": {
+      "location": {
+        "lat": 41,
+        "lon": -71
+      },
+      "distance": "50km",
+      "optimize_bbox": "indexed" <2>
+    }
+  }
+}
+--------------------------------------------------
+// AUTOSENSE
+<1> Setting `lat_lon` to true indexes the geo-point in the `location.lat` and `location.lon` fields.
+<2> The `indexed` option tells the geo-distance query to use the inverted index instead of the in-memory calculation.
+
+Whether the in-memory or indexed operation performs better depends both on
+your dataset and on the types of queries that you are running.
+
+NOTE: The `lat_lon` option only makes sense for single-value `geo_point`
+fields. It will not work with arrays of geo-points.
+

docs/reference/mapping/params/multi-fields.asciidoc

@@ -0,0 +1,132 @@
+[[multi-fields]]
+=== `fields`
+
+It is often useful to index the same field in different ways for different
+purposes.  This is the purpose of _multi-fields_. For instance, a `string`
+field could be <<mapping-index,indexed>> as an `analyzed` field for full-text
+search, and as a `not_analyzed` field for sorting or aggregations:
+
+[source,js]
+--------------------------------------------------
+PUT /my_index
+{
+  "mappings": {
+    "my_type": {
+      "properties": {
+        "city": {
+          "type": "string",
+          "fields": {
+            "raw": { <1>
+              "type":  "string",
+              "index": "not_analyzed"
+            }
+          }
+        }
+      }
+    }
+  }
+}
+
+PUT /my_index/my_type/1
+{
+  "city": "New York"
+}
+
+PUT /my_index/my_type/2
+{
+  "city": "York"
+}
+
+GET /my_index/_search
+{
+  "query": {
+    "match": {
+      "city": "york" <2>
+    }
+  },
+  "sort": {
+    "city.raw": "asc" <3>
+  },
+  "aggs": {
+    "Cities": {
+      "terms": {
+        "field": "city.raw" <3>
+      }
+    }
+  }
+}
+--------------------------------------------------
+// AUTOSENSE
+<1> The `city.raw` field is a `not_analyzed` version of the `city` field.
+<2> The analyzed `city` field can be used for full text search.
+<3> The `city.raw` field can be used for sorting and aggregations
+
+NOTE: Multi-fields do not change the original `_source` field.
+
+==== Multi-fields with multiple analyzers
+
+Another use case of multi-fields is to analyze the same field in different
+ways for better relevance. For instance we could index a field with the
+<<analysis-standard-analyzer,`standard` analyzer>> which breaks text up into
+words, and again with the <<english-analyzer,`english` analyzer>>
+which stems words into their root form:
+
+[source,js]
+--------------------------------------------------
+PUT my_index
+{
+  "mappings": {
+    "my_type": {
+      "properties": {
+        "text": { <1>
+          "type": "string"
+        },
+        "fields": {
+          "english": { <2>
+            "type":     "string",
+            "analyzer": "english"
+          }
+        }
+      }
+    }
+  }
+}
+
+PUT my_index/my_type/1
+{ "text": "quick brown fox" } <3>
+
+PUT my_index/my_type/2
+{ "text": "quick brown foxes" } <3>
+
+GET my_index/_search
+{
+  "query": {
+    "multi_match": {
+      "query": "quick brown foxes",
+      "fields": [ <4>
+        "text",
+        "text.english"
+      ],
+      "type": "most_fields" <4>
+    }
+  }
+}
+--------------------------------------------------
+// AUTOSENSE
+
+<1> The `text` field uses the `standard` analyzer.
+<2> The `text.english` field uses the `english` analyzer.
+<3> Index two documents, one with `fox` and the other with `foxes`.
+<4> Query both the `text` and `text.english` fields and combine the scores.
+
+The `text` field contains the term `fox` in the first document and `foxes` in
+the second document.  The `text.english` field contains `fox` for both
+documents, because `foxes` is stemmed to `fox`.
+
+The query string is also analyzed by the `standard` analyzer for the `text`
+field, and by the `english` analyzer` for the `text.english` field.  The
+stemmed field allows a query for `foxes` to also match the document containing
+just `fox`.  This allows us to match as many documents as possible.  By also
+querying the unstemmed `text` field, we improve the relevance score of the
+document which matches `foxes` exactly.
+

docs/reference/mapping/params/norms.asciidoc

@@ -0,0 +1,64 @@
+[[norms]]
+=== `norms`
+
+Norms store various normalization factors -- a number to represent the
+relative field length and the <<index-boost,index time `boost`>> setting --
+that are later used at query time in order to compute the score of a document
+relatively to a query.
+
+Although useful for scoring, norms also require quite a lot of memory
+(typically in the order of one byte per document per field in your index, even
+for documents that don't have this specific field). As a consequence, if you
+don't need scoring on a specific field, you should disable norms on that
+field. In  particular, this is the case for fields that are used solely for
+filtering or aggregations.
+
+Norms can be disabled (but not reenabled) after the fact, using the
+<<indices-put-mapping,PUT mapping API>> like so:
+
+[source,js]
+------------
+PUT my_index/_mapping/my_type
+{
+  "properties": {
+    "title": {
+      "type": "string",
+      "norms": {
+        "enabled": false
+      }
+    }
+  }
+}
+------------
+// AUTOSENSE
+
+NOTE: Norms will not be removed instantly, but will be removed as old segments
+are merged into new segments as you continue indexing new documents. Any score
+computation on a field that has had norms removed might return inconsistent
+results since some documents won't have norms anymore while other documents
+might still have norms.
+
+==== Lazy loading of norms
+
+Norms can be loaded into memory eagerly (`eager`), whenever a new segment
+comes online, or they can loaded lazily (`lazy`, default), only when the field
+is queried.
+
+Eager loading can be configured as follows:
+
+[source,js]
+------------
+PUT my_index/_mapping/my_type
+{
+  "properties": {
+    "title": {
+      "type": "string",
+      "norms": {
+        "loading": "eager"
+      }
+    }
+  }
+}
+------------
+// AUTOSENSE
+

docs/reference/mapping/params/null-value.asciidoc

@@ -0,0 +1,58 @@
+[[null-value]]
+=== `null_value`
+
+A `null` value cannot be indexed or searched.  When a field is set to `null`,
+(or an empty array or an array of `null` values)  it is treated as though that
+field has no values.
+
+The `null_value` parameter allows you to replace explicit `null` values with
+the specified value so that it can be indexed and searched.  For instance:
+
+[source,js]
+--------------------------------------------------
+PUT my_index
+{
+  "mappings": {
+    "my_type": {
+      "properties": {
+        "status_code": {
+          "type":       "string",
+          "index":      "not_analyzed",
+          "null_value": "NULL" <1>
+        }
+      }
+    }
+  }
+}
+
+PUT my_index/my_type/1
+{
+  "status_code": null
+}
+
+PUT my_index/my_type/2
+{
+  "status_code": [] <2>
+}
+
+GET my_index/_search
+{
+  "query": {
+    "term": {
+      "status_code": "NULL" <3>
+    }
+  }
+}
+--------------------------------------------------
+// AUTOSENSE
+<1> Replace explicit `null` values with the term `NULL`.
+<2> An empty array does not contain an explicit `null`, and so won't be replaced with the `null_value`.
+<3> A query for `NULL` returns document 1, but not document 2.
+
+IMPORTANT: The `null_value` needs to be the same datatype as the field.  For
+instance, a `long` field cannot have a string `null_value`.  String fields
+which are `analyzed` will also pass the `null_value` through the configured
+analyzer.
+
+Also see the <<query-dsl-missing-query,`missing` query>> for its `null_value` support.
+

docs/reference/mapping/params/position-offset-gap.asciidoc

@@ -0,0 +1,68 @@
+[[position-offset-gap]]
+=== `position_offset_gap`
+
+<<mapping-index,Analyzed>> string fields take term <<index-options,positions>>
+into account, in order to be able to support
+<<query-dsl-match-query-phrase,proximity or phrase queries>>.
+When indexing an array of strings, each string of the array is indexed
+directly after the previous one, almost as though all the strings in the array
+had been concatenated into one big string.
+
+This can result in matches from phrase queries spanning two array elements.
+For instance:
+
+[source,js]
+--------------------------------------------------
+PUT /my_index/groups/1
+{
+    "names": [ "John Abraham", "Lincoln Smith"]
+}
+
+GET /my_index/groups/_search
+{
+    "query": {
+        "match_phrase": {
+            "names": "Abraham Lincoln" <1>
+        }
+    }
+}
+--------------------------------------------------
+// AUTOSENSE
+<1> This phrase query matches our document, even though `Abraham` and `Lincoln` are in separate strings.
+
+The `position_offset_gap` can introduce a fake gap between each array element.  For instance:
+
+[source,js]
+--------------------------------------------------
+PUT my_index
+{
+  "mappings": {
+    "my_type": {
+      "properties": {
+        "names": {
+          "type": "string",
+          "position_offset_gap": 50 <1>
+        }
+      }
+    }
+  }
+}
+
+PUT /my_index/groups/1
+{
+    "names": [ "John Abraham", "Lincoln Smith"]
+}
+
+GET /my_index/groups/_search
+{
+    "query": {
+        "match_phrase": {
+            "names": "Abraham Lincoln" <2>
+        }
+    }
+}
+--------------------------------------------------
+// AUTOSENSE
+<1> The first term in the next array element will be 50 terms apart from the
+    last term in the previous array element.
+<2> The phrase query no longer matches our document.

docs/reference/mapping/params/precision-step.asciidoc

@@ -0,0 +1,56 @@
+[[precision-step]]
+=== `precision_step`
+
+Most <<number,numeric>> datatypes index extra terms representing numeric
+ranges for each number to make <<query-dsl-range-query,`range` queries>>
+faster.  For instance, this `range` query:
+
+[source,js]
+--------------------------------------------------
+  "range": {
+    "number": {
+      "gte": 0
+      "lte": 321
+    }
+  }
+--------------------------------------------------
+
+might be executed internally as a <<query-dsl-terms-query,`terms` query>> that
+looks something like this:
+
+[source,js]
+--------------------------------------------------
+  "terms": {
+    "number": [
+      "0-255",
+      "256-319"
+      "320",
+      "321"
+    ]
+  }
+--------------------------------------------------
+
+These extra terms greatly reduce the number of terms that have to be examined,
+at the cost of increased disk space.
+
+The default value for `precision_step` depends on the `type` of the numeric field:
+
+[horizontal]
+`long`, `double`, `date`, `ip`::  `16` (3 extra terms)
+`integer`, `float`, `short`::     `8` (3 extra terms)
+`byte`::                          `2147483647` (0 extra terms)
+`token_count`::                   `32` (0 extra terms)
+
+The value of the `precision_step` setting indicates the number of bits that
+should be compressed into an extra term.  A `long` value consists of 64 bits,
+so a `precision_step` of 16 results in the following terms:
+
+[horizontal]
+Bits 0-15:: `value & 1111111111111111 0000000000000000 0000000000000000 0000000000000000`
+Bits 0-31:: `value & 1111111111111111 1111111111111111 0000000000000000 0000000000000000`
+Bits 0-47:: `value & 1111111111111111 1111111111111111 1111111111111111 0000000000000000`
+Bits 0-63:: `value`
+
+
+
+

docs/reference/mapping/params/properties.asciidoc

@@ -0,0 +1,101 @@
+[[properties]]
+=== `properties`
+
+Type mappings, <<object,`object` fields>> and <<nested,`nested` fields>>
+contain sub-fields, called `properties`. These properties may be of any
+<<mapping-types,datatype>>, including `object` and `nested`.  Properties can
+be added:
+
+* explicitly by defining them when <<indices-create-index,creating an index>>.
+* explicitily by defining them when adding or updating a mapping type with the <<indices-put-mapping,PUT mapping>> API.
+* <<dynamic-mapping,dynamically>> just by indexing documents containing new fields.
+
+Below is an example of adding `properties` to a mapping type, an `object`
+field, and a `nested` field:
+
+[source,js]
+--------------------------------------------------
+PUT my_index
+{
+  "mappings": {
+    "my_type": { <1>
+      "properties": {
+        "manager": { <2>
+          "properties": {
+            "age":  { "type": "integer" },
+            "name": { "type": "string"  }
+          }
+        },
+        "employees": { <3>
+          "type": "nested",
+          "properties": {
+            "age":  { "type": "integer" },
+            "name": { "type": "string"  }
+          }
+        }
+      }
+    }
+  }
+}
+
+PUT my_index/my_type/1 <4>
+{
+  "region": "US",
+  "manager": {
+    "name": "Alice White",
+    "age": 30
+  },
+  "employees": [
+    {
+      "name": "John Smith",
+      "age": 34
+    },
+    {
+      "name": "Peter Brown",
+      "age": 26
+    }
+  ]
+}
+--------------------------------------------------
+// AUTOSENSE
+<1> Properties under the `my_type` mapping type.
+<2> Properties under the `manager` object field.
+<3> Properties under the `employees` nested field.
+<4> An example document which corresponds to the above mapping.
+
+==== Dot notation
+
+Inner fields can be referred to in queries, aggregations, etc., using _dot
+notation_:
+
+[source,js]
+--------------------------------------------------
+GET my_index/_search
+{
+  "query": {
+    "match": {
+      "manager.name": "Alice White" <1>
+    }
+  },
+  "aggs": {
+    "Employees": {
+      "nested": {
+        "path": "employees"
+      },
+      "aggs": {
+        "Employee Ages": {
+          "histogram": {
+            "field": "employees.age", <2>
+            "interval": 5
+          }
+        }
+      }
+    }
+  }
+}
+--------------------------------------------------
+// AUTOSENSE
+
+IMPORTANT: The full path to the inner field must be specified.
+
+

docs/reference/mapping/params/search-analyzer.asciidoc

@@ -0,0 +1,79 @@
+[[search-analyzer]]
+=== `search_analyzer`
+
+Usually, the same <<analyzer,analyzer>> should be applied at index time and at
+search time, to ensure that the terms in the query are in the same format as
+the terms in the inverted index.
+
+Sometimes, though, it can make sense to use a different analyzer at search
+time, such as when using the  <<analysis-edgengram-tokenizer,`edge_ngram`>>
+tokenizer for autocomplete.
+
+By default, queries will use the `analyzer` defined in the field mapping, but
+this can be overridden with the `search_analyzer` setting:
+
+[source,js]
+--------------------------------------------------
+PUT /my_index
+{
+  "settings": {
+    "analysis": {
+      "filter": {
+        "autocomplete_filter": {
+          "type": "edge_ngram",
+          "min_gram": 1,
+          "max_gram": 20
+        }
+      },
+      "analyzer": {
+        "autocomplete": { <1>
+          "type": "custom",
+          "tokenizer": "standard",
+          "filter": [
+            "lowercase",
+            "autocomplete_filter"
+          ]
+        }
+      }
+    }
+  },
+  "mappings": {
+    "my_type": {
+      "properties": {
+        "text": {
+          "type": "string",
+          "analyzer": "autocomplete", <2>
+          "search_analyzer": "standard" <2>
+        }
+      }
+    }
+  }
+}
+
+PUT my_index/my_type/1
+{
+  "text": "Quick Brown Fox" <3>
+}
+
+GET my_index/_search
+{
+  "query": {
+    "match": {
+      "text": {
+        "query": "Quick Br", <4>
+        "operator": "and"
+      }
+    }
+  }
+}
+
+--------------------------------------------------
+// AUTOSENSE
+
+<1> Analysis settings to define the custom `autocomplete` analyzer.
+<2> The `text` field uses the `autocomplete` analyzer at index time, but the `standard` analyzer at search time.
+<3> This field is indexed as the terms: [ `q`, `qu`, `qui`, `quic`, `quick`, `b`, `br`, `bro`, `brow`, `brown`, `f`, `fo`, `fox` ]
+<4> The query searches for both of these terms: [ `quick`, `br` ]
+
+See {defguide}/_index_time_search_as_you_type.html[Index time search-as-you-
+type] for a full explanation of this example.

docs/reference/mapping/params/similarity.asciidoc

@@ -0,0 +1,54 @@
+[[similarity]]
+=== `similarity`
+
+Elasticsearch allows you to configure a scoring algorithm or _similarity_ per
+field. The `similarity` setting provides a simple way of choosing a similarity
+algorithm other than the default TF/IDF, such as `BM25`.
+
+Similarities are mostly useful for <<string,`string`>> fields, especially
+`analyzed` string fields, but can also apply to other field types.
+
+Custom similarites can be configured by tuning the parameters of the built-in
+similarities. For more details about this expert options, see the
+<<index-modules-similarity,similarity module>>.
+
+The only similarities which can be used out of the box, without any further
+configuration are:
+
+`default`::
+        The Default TF/IDF algorithm used by Elasticsearch and
+        Lucene. See {defguide}/practical-scoring-function.html[Lucene’s Practical Scoring Function]
+        for more information.
+
+`BM25`::
+        The Okapi BM25 algorithm.
+        See {defguide}/pluggable-similarites.html[Plugggable Similarity Algorithms]
+        for more information.
+
+
+The `similarity` can be set on the field level when a field is first created,
+as follows:
+
+[source,js]
+--------------------------------------------------
+PUT my_index
+{
+  "mappings": {
+    "my_type": {
+      "properties": {
+        "default_field": { <1>
+          "type": "string"
+        },
+        "bm25_field": {
+          "type": "string",
+          "similarity": "BM25" <2>
+        }
+      }
+    }
+  }
+}
+--------------------------------------------------
+// AUTOSENSE
+<1> The `default_field` uses the `default` similarity (ie TF/IDF).
+<2> The `bm25_field` uses the `BM25` similarity.
+

docs/reference/mapping/params/store.asciidoc

@@ -0,0 +1,73 @@
+[[mapping-store]]
+=== `store`
+
+By default, field values <<mapping-index,indexed>> to make them searchable,
+but they are not _stored_.  This means that the field can be queried, but the
+original field value cannot be retrieved.
+
+Usually this doesn't matter.  The field value is already part of the
+<<mapping-source-field,`_source` field>>, which is stored by default. If you
+only want to retrieve the value of a single field or of a few fields, instead
+of the whole `_source`, then this can be achieved with
+<<search-request-source-filtering,source filtering>>.
+
+In certain situations it can make sense to `store` a field.  For instance, if
+you have a document with a `title`, a `date`, and a very large `content`
+field, you may want to retrieve just the `title` and the `date` without having
+to extract those fields from a large `_source` field:
+
+[source,js]
+--------------------------------------------------
+PUT /my_index
+{
+  "mappings": {
+    "my_type": {
+      "properties": {
+        "title": {
+          "type": "string",
+          "store": true <1>
+        },
+        "date": {
+          "type": "date",
+          "store": true <1>
+        },
+        "content": {
+          "type": "string"
+        }
+      }
+    }
+  }
+}
+
+PUT /my_index/my_type/1
+{
+  "title":   "Some short title",
+  "date":    "2015-01-01",
+  "content": "A very long content field..."
+}
+
+GET my_index/_search
+{
+  "fields": [ "title", "date" ] <2>
+}
+--------------------------------------------------
+// AUTOSENSE
+<1> The `title` and `date` fields are stored.
+<2> This request will retrieve the values of the `title` and `date` fields.
+
+[NOTE]
+.Stored fields returned as arrays
+======================================
+
+For consistency, stored fields are always returned as an _array_ because there
+is no way of knowing if the original field value was a single value, multiple
+values, or an empty array.
+
+If you need the original value, you should retrieve it from the `_source`
+field instead.
+
+======================================
+
+Another situation where it can make sense to make a field stored is for those
+that don't appear in the `_source` field (such as <<copy-to,`copy_to` fields>>).
+