Term Vectors/MLT Query: support for different analyzers than default at field
This adds a `per_field_analyzer` parameter to the Term Vectors API, which allows to override the default analyzer at the field. If the field already stores term vectors, then they will be re-generated. Since the MLT Query uses the Term Vectors API under its hood, this commits also adds the same ability to the MLT Query, thereby allowing users to fine grain how each field item should be processed and analyzed. Closes #7801
This commit is contained in:
Alex Ksikes
parent
d35d125ad8
commit
349b7a3a8b
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@ -249,7 +249,7 @@ curl -XGET 'http://localhost:9200/twitter/tweet/1/_termvector?pretty=true' -d '{
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[float]
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=== Example 3
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Additionally, term vectors can also be generated for artificial documents,
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Term vectors can also be generated for artificial documents,
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that is for documents not present in the index. The syntax is similar to the
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<<search-percolate,percolator>> API. For example, the following request would
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return the same results as in example 1. The mapping used is determined by the
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@ -271,3 +271,59 @@ curl -XGET 'http://localhost:9200/twitter/tweet/_termvector' -d '{
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}'
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--------------------------------------------------
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[float]
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[[docs-termvectors-per-field-analyzer]]
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=== Example 4 coming[1.5.0]
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Additionally, a different analyzer than the one at the field may be provided
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by using the `per_field_analyzer` parameter. This is useful in order to
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generate term vectors in any fashion, especially when using artificial
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documents. When providing an analyzer for a field that already stores term
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vectors, the term vectors will be re-generated.
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[source,js]
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--------------------------------------------------
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curl -XGET 'http://localhost:9200/twitter/tweet/_termvector' -d '{
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"doc" : {
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"fullname" : "John Doe",
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"text" : "twitter test test test"
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},
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"fields": ["fullname"],
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"per_field_analyzer" : {
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"fullname": "keyword"
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}
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}'
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--------------------------------------------------
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Response:
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[source,js]
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--------------------------------------------------
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{
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"_index": "twitter",
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"_type": "tweet",
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"_version": 0,
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"found": true,
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"term_vectors": {
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"fullname": {
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"field_statistics": {
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"sum_doc_freq": 1,
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"doc_count": 1,
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"sum_ttf": 1
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},
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"terms": {
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"John Doe": {
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"term_freq": 1,
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"tokens": [
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{
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"position": 0,
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"start_offset": 0,
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"end_offset": 8
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}
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]
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}
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}
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}
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}
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}
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--------------------------------------------------
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@ -19,7 +19,7 @@ running it against one or more fields.
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More Like This can find documents that are "like" a set of
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chosen documents. The syntax to specify one or more documents is similar to
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the <<docs-multi-get,Multi GET API>>, and supports the `ids` or `docs` array.
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If only one document is specified, the query behaves the same as the
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If only one document is specified, the query behaves the same as the
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<<search-more-like-this,More Like This API>>.
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[source,js]
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@ -115,9 +115,11 @@ for `ids` or `docs`.
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|`like_text` |The text to find documents like it, *required* if `ids` or `docs` are
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not specified.
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|`ids` or `docs` |A list of documents following the same syntax as the
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|`ids` or `docs` |A list of documents following the same syntax as the
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<<docs-multi-get,Multi GET API>> or <<docs-multi-termvectors,Multi Term Vectors API>>.
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The text is fetched from `fields` unless specified otherwise in each `doc`.
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The text is analyzed by the default analyzer at the field, unless specified by the
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`per_field_analyzer` parameter of the <<docs-termvectors-per-field-analyzer,Term Vectors API>>.
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|`include` |When using `ids` or `docs`, specifies whether the documents should be
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included from the search. Defaults to `false`.
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@ -19,7 +19,9 @@
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package org.elasticsearch.action.termvector;
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import com.google.common.collect.Maps;
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import com.google.common.collect.Sets;
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import org.elasticsearch.ElasticsearchException;
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import org.elasticsearch.ElasticsearchParseException;
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import org.elasticsearch.Version;
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import org.elasticsearch.action.ActionRequestValidationException;
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@ -65,6 +67,8 @@ public class TermVectorRequest extends SingleShardOperationRequest<TermVectorReq
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Boolean realtime;
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private Map<String, String> perFieldAnalyzer;
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private EnumSet<Flag> flagsEnum = EnumSet.of(Flag.Positions, Flag.Offsets, Flag.Payloads,
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Flag.FieldStatistics);
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@ -314,6 +318,21 @@ public class TermVectorRequest extends SingleShardOperationRequest<TermVectorReq
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return this;
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}
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/**
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* Return the overridden analyzers at each field
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*/
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public Map<String, String> perFieldAnalyzer() {
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return perFieldAnalyzer;
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}
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/**
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* Override the analyzer used at each field when generating term vectors
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*/
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public TermVectorRequest perFieldAnalyzer(Map<String, String> perFieldAnalyzer) {
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this.perFieldAnalyzer = perFieldAnalyzer != null && perFieldAnalyzer.size() != 0 ? Maps.newHashMap(perFieldAnalyzer) : null;
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return this;
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}
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private void setFlag(Flag flag, boolean set) {
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if (set && !flagsEnum.contains(flag)) {
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flagsEnum.add(flag);
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@ -375,6 +394,9 @@ public class TermVectorRequest extends SingleShardOperationRequest<TermVectorReq
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}
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}
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if (in.getVersion().onOrAfter(Version.V_1_5_0)) {
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if (in.readBoolean()) {
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perFieldAnalyzer = readPerFieldAnalyzer(in.readMap());
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}
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this.realtime = in.readBoolean();
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}
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}
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@ -411,6 +433,10 @@ public class TermVectorRequest extends SingleShardOperationRequest<TermVectorReq
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out.writeVInt(0);
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}
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if (out.getVersion().onOrAfter(Version.V_1_5_0)) {
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out.writeBoolean(perFieldAnalyzer != null);
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if (perFieldAnalyzer != null) {
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out.writeGenericValue(perFieldAnalyzer);
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}
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out.writeBoolean(realtime());
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}
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}
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@ -451,6 +477,8 @@ public class TermVectorRequest extends SingleShardOperationRequest<TermVectorReq
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termVectorRequest.termStatistics(parser.booleanValue());
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} else if (currentFieldName.equals("field_statistics") || currentFieldName.equals("fieldStatistics")) {
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termVectorRequest.fieldStatistics(parser.booleanValue());
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} else if (currentFieldName.equals("per_field_analyzer") || currentFieldName.equals("perFieldAnalyzer")) {
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termVectorRequest.perFieldAnalyzer(readPerFieldAnalyzer(parser.map()));
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} else if ("_index".equals(currentFieldName)) { // the following is important for multi request parsing.
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termVectorRequest.index = parser.text();
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} else if ("_type".equals(currentFieldName)) {
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@ -478,4 +506,17 @@ public class TermVectorRequest extends SingleShardOperationRequest<TermVectorReq
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termVectorRequest.selectedFields(fields.toArray(fieldsAsArray));
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}
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}
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private static Map<String, String> readPerFieldAnalyzer(Map<String, Object> map) {
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Map<String, String> mapStrStr = new HashMap<>();
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for (Map.Entry<String, Object> e : map.entrySet()) {
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if (e.getValue() instanceof String) {
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mapStrStr.put(e.getKey(), (String) e.getValue());
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} else {
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throw new ElasticsearchException(
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"The analyzer at " + e.getKey() + " should be of type String, but got a " + e.getValue().getClass() + "!");
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}
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}
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return mapStrStr;
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}
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}
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@ -24,6 +24,8 @@ import org.elasticsearch.action.ActionRequestBuilder;
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import org.elasticsearch.client.Client;
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import org.elasticsearch.common.xcontent.XContentBuilder;
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import java.util.Map;
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/**
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*/
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public class TermVectorRequestBuilder extends ActionRequestBuilder<TermVectorRequest, TermVectorResponse, TermVectorRequestBuilder, Client> {
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@ -131,6 +133,11 @@ public class TermVectorRequestBuilder extends ActionRequestBuilder<TermVectorReq
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return this;
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}
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public TermVectorRequestBuilder setPerFieldAnalyzer(Map<String, String> perFieldAnalyzer) {
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request.perFieldAnalyzer(perFieldAnalyzer);
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return this;
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}
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@Override
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protected void doExecute(ActionListener<TermVectorResponse> listener) {
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client.termVector(request, listener);
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@ -26,6 +26,7 @@ import org.elasticsearch.ElasticsearchException;
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import org.elasticsearch.action.termvector.TermVectorRequest;
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import org.elasticsearch.action.termvector.TermVectorResponse;
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import org.elasticsearch.cluster.action.index.MappingUpdatedAction;
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import org.elasticsearch.common.Nullable;
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import org.elasticsearch.common.Strings;
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import org.elasticsearch.common.bytes.BytesReference;
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import org.elasticsearch.common.collect.Tuple;
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@ -107,9 +108,14 @@ public class ShardTermVectorService extends AbstractIndexShardComponent {
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else if (docIdAndVersion != null) {
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// fields with stored term vectors
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Fields termVectorsByField = docIdAndVersion.context.reader().getTermVectors(docIdAndVersion.docId);
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Set<String> selectedFields = request.selectedFields();
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// generate tvs for fields where analyzer is overridden
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if (selectedFields == null && request.perFieldAnalyzer() != null) {
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selectedFields = getFieldsToGenerate(request.perFieldAnalyzer(), termVectorsByField);
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}
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// fields without term vectors
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if (request.selectedFields() != null) {
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termVectorsByField = addGeneratedTermVectors(get, termVectorsByField, request);
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if (selectedFields != null) {
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termVectorsByField = addGeneratedTermVectors(get, termVectorsByField, request, selectedFields);
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}
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termVectorResponse.setFields(termVectorsByField, request.selectedFields(), request.getFlags(), topLevelFields);
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termVectorResponse.setDocVersion(docIdAndVersion.version);
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@ -146,16 +152,17 @@ public class ShardTermVectorService extends AbstractIndexShardComponent {
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return true;
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}
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private Fields addGeneratedTermVectors(Engine.GetResult get, Fields termVectorsByField, TermVectorRequest request) throws IOException {
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private Fields addGeneratedTermVectors(Engine.GetResult get, Fields termVectorsByField, TermVectorRequest request, Set<String> selectedFields) throws IOException {
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/* only keep valid fields */
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Set<String> validFields = new HashSet<>();
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for (String field : request.selectedFields()) {
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for (String field : selectedFields) {
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FieldMapper fieldMapper = indexShard.mapperService().smartNameFieldMapper(field);
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if (!isValidField(fieldMapper)) {
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continue;
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}
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// already retrieved
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if (fieldMapper.fieldType().storeTermVectors()) {
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// already retrieved, only if the analyzer hasn't been overridden at the field
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if (fieldMapper.fieldType().storeTermVectors() &&
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(request.perFieldAnalyzer() == null || !request.perFieldAnalyzer().containsKey(field))) {
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continue;
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}
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validFields.add(field);
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@ -168,25 +175,47 @@ public class ShardTermVectorService extends AbstractIndexShardComponent {
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/* generate term vectors from fetched document fields */
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GetResult getResult = indexShard.getService().get(
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get, request.id(), request.type(), validFields.toArray(Strings.EMPTY_ARRAY), null, false);
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Fields generatedTermVectors = generateTermVectors(getResult.getFields().values(), request.offsets());
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Fields generatedTermVectors = generateTermVectors(getResult.getFields().values(), request.offsets(), request.perFieldAnalyzer());
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/* merge with existing Fields */
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if (termVectorsByField == null) {
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return generatedTermVectors;
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} else {
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return mergeFields(request.selectedFields().toArray(Strings.EMPTY_ARRAY), termVectorsByField, generatedTermVectors);
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return mergeFields(termVectorsByField, generatedTermVectors);
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}
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}
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private Fields generateTermVectors(Collection<GetField> getFields, boolean withOffsets) throws IOException {
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private Analyzer getAnalyzerAtField(String field, @Nullable Map<String, String> perFieldAnalyzer) {
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MapperService mapperService = indexShard.mapperService();
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Analyzer analyzer;
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if (perFieldAnalyzer != null && perFieldAnalyzer.containsKey(field)) {
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analyzer = mapperService.analysisService().analyzer(perFieldAnalyzer.get(field).toString());
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} else {
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analyzer = mapperService.smartNameFieldMapper(field).indexAnalyzer();
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}
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if (analyzer == null) {
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analyzer = mapperService.analysisService().defaultIndexAnalyzer();
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}
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return analyzer;
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}
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private Set<String> getFieldsToGenerate(Map<String, String> perAnalyzerField, Fields fieldsObject) {
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Set<String> selectedFields = new HashSet<>();
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for (String fieldName : fieldsObject) {
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if (perAnalyzerField.containsKey(fieldName)) {
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selectedFields.add(fieldName);
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}
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}
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return selectedFields;
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}
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private Fields generateTermVectors(Collection<GetField> getFields, boolean withOffsets, @Nullable Map<String, String> perFieldAnalyzer)
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throws IOException {
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/* store document in memory index */
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MemoryIndex index = new MemoryIndex(withOffsets);
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for (GetField getField : getFields) {
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String field = getField.getName();
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Analyzer analyzer = indexShard.mapperService().smartNameFieldMapper(field).indexAnalyzer();
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if (analyzer == null) {
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analyzer = indexShard.mapperService().analysisService().defaultIndexAnalyzer();
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}
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Analyzer analyzer = getAnalyzerAtField(field, perFieldAnalyzer);
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for (Object text : getField.getValues()) {
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index.addField(field, text.toString(), analyzer);
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}
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@ -223,7 +252,7 @@ public class ShardTermVectorService extends AbstractIndexShardComponent {
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String[] values = doc.getValues(field.name());
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getFields.add(new GetField(field.name(), Arrays.asList((Object[]) values)));
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}
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return generateTermVectors(getFields, request.offsets());
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return generateTermVectors(getFields, request.offsets(), request.perFieldAnalyzer());
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}
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private ParsedDocument parseDocument(String index, String type, BytesReference doc) {
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@ -239,15 +268,21 @@ public class ShardTermVectorService extends AbstractIndexShardComponent {
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return parsedDocument;
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}
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private Fields mergeFields(String[] fieldNames, Fields... fieldsObject) throws IOException {
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private Fields mergeFields(Fields fields1, Fields fields2) throws IOException {
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ParallelFields parallelFields = new ParallelFields();
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for (Fields fieldObject : fieldsObject) {
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assert fieldObject != null;
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for (String fieldName : fieldNames) {
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Terms terms = fieldObject.terms(fieldName);
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if (terms != null) {
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parallelFields.addField(fieldName, terms);
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}
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for (String fieldName : fields2) {
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Terms terms = fields2.terms(fieldName);
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if (terms != null) {
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parallelFields.addField(fieldName, terms);
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}
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}
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for (String fieldName : fields1) {
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if (parallelFields.fields.containsKey(fieldName)) {
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continue;
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}
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Terms terms = fields1.terms(fieldName);
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if (terms != null) {
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parallelFields.addField(fieldName, terms);
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}
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}
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return parallelFields;
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@ -28,6 +28,7 @@ import org.elasticsearch.ElasticsearchException;
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import org.elasticsearch.action.ActionFuture;
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import org.elasticsearch.action.admin.indices.alias.Alias;
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import org.elasticsearch.action.index.IndexRequestBuilder;
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import org.elasticsearch.common.Strings;
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import org.elasticsearch.common.settings.ImmutableSettings;
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import org.elasticsearch.common.xcontent.ToXContent;
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import org.elasticsearch.common.xcontent.XContentBuilder;
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@ -35,10 +36,7 @@ import org.elasticsearch.index.mapper.core.AbstractFieldMapper;
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import org.junit.Test;
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import java.io.IOException;
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import java.util.ArrayList;
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import java.util.HashMap;
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import java.util.List;
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import java.util.Map;
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import java.util.*;
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import java.util.concurrent.ExecutionException;
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import static org.elasticsearch.common.settings.ImmutableSettings.settingsBuilder;
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@ -924,6 +922,99 @@ public class GetTermVectorTests extends AbstractTermVectorTests {
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}
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}
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@Test
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public void testPerFieldAnalyzer() throws ElasticsearchException, IOException {
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int numFields = 25;
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// setup mapping and document source
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Set<String> withTermVectors = new HashSet<>();
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XContentBuilder mapping = jsonBuilder().startObject().startObject("type1").startObject("properties");
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XContentBuilder source = jsonBuilder().startObject();
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for (int i = 0; i < numFields; i++) {
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String fieldName = "field" + i;
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if (randomBoolean()) {
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withTermVectors.add(fieldName);
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}
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mapping.startObject(fieldName)
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.field("type", "string")
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.field("term_vector", withTermVectors.contains(fieldName) ? "yes" : "no")
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.endObject();
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source.field(fieldName, "some text here");
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}
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source.endObject();
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mapping.endObject().endObject().endObject();
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// setup indices with mapping
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ImmutableSettings.Builder settings = settingsBuilder()
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.put(indexSettings())
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.put("index.analysis.analyzer", "standard");
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assertAcked(prepareCreate("test")
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.addAlias(new Alias("alias"))
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.setSettings(settings)
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.addMapping("type1", mapping));
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ensureGreen();
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// index a single document with prepared source
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client().prepareIndex("test", "type1", "0").setSource(source).get();
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refresh();
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// create random per_field_analyzer and selected fields
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Map<String, String> perFieldAnalyzer = new HashMap<>();
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Set<String> selectedFields = new HashSet<>();
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for (int i = 0; i < numFields; i++) {
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if (randomBoolean()) {
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perFieldAnalyzer.put("field" + i, "keyword");
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}
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if (randomBoolean()) {
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perFieldAnalyzer.put("non_existing" + i, "keyword");
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}
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if (randomBoolean()) {
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selectedFields.add("field" + i);
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}
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if (randomBoolean()) {
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selectedFields.add("non_existing" + i);
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}
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}
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// selected fields not specified
|
||||
TermVectorResponse response = client().prepareTermVector(indexOrAlias(), "type1", "0")
|
||||
.setPerFieldAnalyzer(perFieldAnalyzer)
|
||||
.get();
|
||||
|
||||
// should return all fields that have terms vectors, some with overridden analyzer
|
||||
checkAnalyzedFields(response.getFields(), withTermVectors, perFieldAnalyzer);
|
||||
|
||||
// selected fields specified including some not in the mapping
|
||||
response = client().prepareTermVector(indexOrAlias(), "type1", "0")
|
||||
.setSelectedFields(selectedFields.toArray(Strings.EMPTY_ARRAY))
|
||||
.setPerFieldAnalyzer(perFieldAnalyzer)
|
||||
.get();
|
||||
|
||||
// should return only the specified valid fields, with some with overridden analyzer
|
||||
checkAnalyzedFields(response.getFields(), selectedFields, perFieldAnalyzer);
|
||||
}
|
||||
|
||||
private void checkAnalyzedFields(Fields fieldsObject, Set<String> fieldNames, Map<String, String> perFieldAnalyzer) throws IOException {
|
||||
Set<String> validFields = new HashSet<>();
|
||||
for (String fieldName : fieldNames){
|
||||
if (fieldName.startsWith("non_existing")) {
|
||||
assertThat("Non existing field\"" + fieldName + "\" should not be returned!", fieldsObject.terms(fieldName), nullValue());
|
||||
continue;
|
||||
}
|
||||
Terms terms = fieldsObject.terms(fieldName);
|
||||
assertThat("Existing field " + fieldName + "should have been returned", terms, notNullValue());
|
||||
// check overridden by keyword analyzer ...
|
||||
if (perFieldAnalyzer.containsKey(fieldName)) {
|
||||
TermsEnum iterator = terms.iterator(null);
|
||||
assertThat("Analyzer for " + fieldName + " should have been overridden!", iterator.next().utf8ToString(), equalTo("some text here"));
|
||||
assertThat(iterator.next(), nullValue());
|
||||
}
|
||||
validFields.add(fieldName);
|
||||
}
|
||||
// ensure no other fields are returned
|
||||
assertThat("More fields than expected are returned!", fieldsObject.size(), equalTo(validFields.size()));
|
||||
}
|
||||
|
||||
private static String indexOrAlias() {
|
||||
return randomBoolean() ? "test" : "alias";
|
||||
}
|
||||
|
|
|
|||
Loading…
Reference in New Issue