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semantic_text - extract Index Metadata inference information to separate class #106328
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There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. This is the class that will hold inference information, and the one I'd like to have your early feedback on :) . There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. If I understand correctly, Do I have that right? There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Correct! A mapping update (or any cluster state change) means that we will have a new instance of |
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/* | ||
* Copyright Elasticsearch B.V. and/or licensed to Elasticsearch B.V. under one | ||
* or more contributor license agreements. Licensed under the Elastic License | ||
* 2.0 and the Server Side Public License, v 1; you may not use this file except | ||
* in compliance with, at your election, the Elastic License 2.0 or the Server | ||
* Side Public License, v 1. | ||
*/ | ||
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package org.elasticsearch.cluster.metadata; | ||
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import org.elasticsearch.cluster.Diff; | ||
import org.elasticsearch.cluster.Diffable; | ||
import org.elasticsearch.cluster.DiffableUtils; | ||
import org.elasticsearch.common.collect.ImmutableOpenMap; | ||
import org.elasticsearch.common.io.stream.StreamInput; | ||
import org.elasticsearch.common.io.stream.StreamOutput; | ||
import org.elasticsearch.index.mapper.MappingLookup; | ||
import org.elasticsearch.xcontent.ConstructingObjectParser; | ||
import org.elasticsearch.xcontent.ParseField; | ||
import org.elasticsearch.xcontent.ToXContentFragment; | ||
import org.elasticsearch.xcontent.XContentBuilder; | ||
import org.elasticsearch.xcontent.XContentParser; | ||
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import java.io.IOException; | ||
import java.util.Collections; | ||
import java.util.HashMap; | ||
import java.util.HashSet; | ||
import java.util.Map; | ||
import java.util.Objects; | ||
import java.util.Set; | ||
import java.util.stream.Collectors; | ||
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/** | ||
* Contains field inference information. This is necessary to add to cluster state as inference can be calculated in the coordinator | ||
* node, which not necessarily has mapping information. | ||
*/ | ||
public class FieldInferenceMetadata implements Diffable<FieldInferenceMetadata>, ToXContentFragment { | ||
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// Keys: field names. Values: Inference ID associated to the field name for calculating inference | ||
private final ImmutableOpenMap<String, String> inferenceIdForField; | ||
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// Keys: field names. Values: Field names that provide source for this field (either as copy_to or multifield sources) | ||
private final ImmutableOpenMap<String, Set<String>> sourceFields; | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. We may want to change this to There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. I don't think order is of consequence. There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. I bring it up because @benwtrent brought it up during multi-field/copy_to support discovery. Depending on how we handle inference generation for multi-valued fields in the bulk action, order could matter. For example, if we handle it by concatenating all the values, order could affect the chunks that are produced and therefore the inference results. |
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// Keys: inference IDs. Values: Field names that use the inference id for calculating inference. Reverse of inferenceForFields. | ||
private Map<String, Set<String>> fieldsForInferenceIds; | ||
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public static final FieldInferenceMetadata EMPTY = new FieldInferenceMetadata(ImmutableOpenMap.of(), ImmutableOpenMap.of()); | ||
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public static final ParseField INFERENCE_FOR_FIELDS_FIELD = new ParseField("inference_for_fields"); | ||
public static final ParseField SOURCE_FIELDS_FIELD = new ParseField("source_fields"); | ||
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public FieldInferenceMetadata( | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. I've prioritised using field -> inference IDs map, as it seems clearer from the mapping perspective as well. The class hides the actual implementation and we can calculate the reverse information on demand |
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ImmutableOpenMap<String, String> inferenceIdsForFields, | ||
ImmutableOpenMap<String, Set<String>> sourceFields | ||
) { | ||
this.inferenceIdForField = Objects.requireNonNull(inferenceIdsForFields); | ||
this.sourceFields = Objects.requireNonNull(sourceFields); | ||
} | ||
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public FieldInferenceMetadata( | ||
Map<String, String> inferenceIdsForFields, | ||
Map<String, Set<String>> sourceFields | ||
) { | ||
this.inferenceIdForField = ImmutableOpenMap.builder(Objects.requireNonNull(inferenceIdsForFields)).build(); | ||
this.sourceFields = ImmutableOpenMap.builder(Objects.requireNonNull(sourceFields)).build(); | ||
} | ||
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public FieldInferenceMetadata(MappingLookup mappingLookup) { | ||
this.inferenceIdForField = ImmutableOpenMap.builder(mappingLookup.getInferenceIdsForFields()).build(); | ||
ImmutableOpenMap.Builder<String, Set<String>> sourcePathsBuilder = ImmutableOpenMap.builder(inferenceIdForField.size()); | ||
inferenceIdForField.keySet().forEach(fieldName -> sourcePathsBuilder.put(fieldName, mappingLookup.sourcePaths(fieldName))); | ||
this.sourceFields = sourcePathsBuilder.build(); | ||
} | ||
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public FieldInferenceMetadata(StreamInput in) throws IOException { | ||
inferenceIdForField = in.readImmutableOpenMap(StreamInput::readString, StreamInput::readString); | ||
sourceFields = in.readImmutableOpenMap(StreamInput::readString, i -> i.readCollectionAsImmutableSet(StreamInput::readString)); | ||
} | ||
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@Override | ||
public void writeTo(StreamOutput out) throws IOException { | ||
out.writeMap(inferenceIdForField, StreamOutput::writeString); | ||
out.writeMap(sourceFields, StreamOutput::writeStringCollection); | ||
} | ||
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@Override | ||
public XContentBuilder toXContent(XContentBuilder builder, Params params) throws IOException { | ||
builder.field(INFERENCE_FOR_FIELDS_FIELD.getPreferredName(), inferenceIdForField); | ||
builder.field(SOURCE_FIELDS_FIELD.getPreferredName(), sourceFields); | ||
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return builder; | ||
} | ||
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@SuppressWarnings("unchecked") | ||
private static final ConstructingObjectParser<FieldInferenceMetadata, Void> PARSER = new ConstructingObjectParser<>( | ||
"field_inference_metadata_parser", | ||
false, | ||
(args, unused) -> new FieldInferenceMetadata((Map<String, String>) args[0], (Map<String, Set<String>>) args[1]) | ||
); | ||
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static { | ||
PARSER.declareObject(ConstructingObjectParser.constructorArg(), (p, c) -> p.mapStrings(), INFERENCE_FOR_FIELDS_FIELD); | ||
PARSER.declareObject( | ||
ConstructingObjectParser.constructorArg(), | ||
(p, c) -> p.map( | ||
HashMap::new, | ||
v -> v.list().stream().map(Object::toString).collect(Collectors.toSet()) | ||
), | ||
SOURCE_FIELDS_FIELD | ||
); | ||
} | ||
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public static FieldInferenceMetadata fromXContent(XContentParser parser) throws IOException { | ||
return PARSER.parse(parser, null); | ||
} | ||
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@Override | ||
public Diff<FieldInferenceMetadata> diff(FieldInferenceMetadata previousState) { | ||
return new FieldInferenceMetadataDiff(previousState, this); | ||
} | ||
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public String getInferenceIdForField(String field) { | ||
return inferenceIdForField.get(field); | ||
} | ||
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public Map<String, String> getInferenceIdForFields() { | ||
return inferenceIdForField; | ||
} | ||
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public Set<String> getSourceFields(String field) { | ||
return sourceFields.get(field); | ||
} | ||
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public Map<String, Set<String>> getFieldsForInferenceIds() { | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Could this method be accessed by multiple threads? Should we mark There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Yes, it can be accessed by multiple threads. I didn't want to overdo synchronization / early optimization, and have kept it light on purpose. I think it's preferrable to recalculate vs having the syncing overhead - but happy to hear your thoughts. There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Agree we don't need to go heavy on synchronization here. Worst case, a race condition causes this calculation to be performed in two (or more) threads simultaneously. I think it could be a good idea to mark There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Makes sense, adding that There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. We need to have a single version of this map that is immutable and final. It's a small map so there's no need to compute all the flavours preemptively or even to cache them. The consumer can rebuild data structures on top if their access pattern is different. There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Just to be clear I mean only keeping There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. I see that this is a similar pattern to other Index Metadata related structures. Changing it |
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if (fieldsForInferenceIds != null) { | ||
return fieldsForInferenceIds; | ||
} | ||
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// Cache the result as a field | ||
Map<String, Set<String>> fieldsForInferenceIdsMap = new HashMap<>(); | ||
for (Map.Entry<String, String> entry : inferenceIdForField.entrySet()) { | ||
String inferenceId = entry.getValue(); | ||
String fieldName = entry.getKey(); | ||
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// Get or create the set associated with the inferenceId | ||
Set<String> fields = fieldsForInferenceIdsMap.computeIfAbsent(inferenceId, k -> new HashSet<>()); | ||
fields.add(fieldName); | ||
} | ||
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fieldsForInferenceIds = Collections.unmodifiableMap(fieldsForInferenceIdsMap); | ||
return fieldsForInferenceIds; | ||
} | ||
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@Override | ||
public boolean equals(Object o) { | ||
if (this == o) return true; | ||
if (o == null || getClass() != o.getClass()) return false; | ||
FieldInferenceMetadata that = (FieldInferenceMetadata) o; | ||
return Objects.equals(inferenceIdForField, that.inferenceIdForField) && Objects.equals(sourceFields, that.sourceFields); | ||
} | ||
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@Override | ||
public int hashCode() { | ||
return Objects.hash(inferenceIdForField, sourceFields); | ||
} | ||
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public static class FieldInferenceMetadataDiff implements Diff<FieldInferenceMetadata> { | ||
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private final Diff<ImmutableOpenMap<String, String>> inferenceForFields; | ||
private final Diff<ImmutableOpenMap<String, Set<String>>> copyFromFields; | ||
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private static final DiffableUtils.NonDiffableValueSerializer<String, String> STRING_VALUE_SERIALIZER = | ||
new DiffableUtils.NonDiffableValueSerializer<>() { | ||
@Override | ||
public void write(String value, StreamOutput out) throws IOException { | ||
out.writeString(value); | ||
} | ||
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@Override | ||
public String read(StreamInput in, String key) throws IOException { | ||
return in.readString(); | ||
} | ||
}; | ||
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FieldInferenceMetadataDiff(FieldInferenceMetadata before, FieldInferenceMetadata after) { | ||
inferenceForFields = DiffableUtils.diff( | ||
before.inferenceIdForField, | ||
after.inferenceIdForField, | ||
DiffableUtils.getStringKeySerializer(), | ||
STRING_VALUE_SERIALIZER); | ||
copyFromFields = DiffableUtils.diff( | ||
before.sourceFields, | ||
after.sourceFields, | ||
DiffableUtils.getStringKeySerializer(), | ||
DiffableUtils.StringSetValueSerializer.getInstance() | ||
); | ||
} | ||
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FieldInferenceMetadataDiff(StreamInput in) throws IOException { | ||
inferenceForFields = DiffableUtils.readImmutableOpenMapDiff( | ||
in, | ||
DiffableUtils.getStringKeySerializer(), | ||
STRING_VALUE_SERIALIZER | ||
); | ||
copyFromFields = DiffableUtils.readImmutableOpenMapDiff( | ||
in, | ||
DiffableUtils.getStringKeySerializer(), | ||
DiffableUtils.StringSetValueSerializer.getInstance() | ||
); | ||
} | ||
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public static final FieldInferenceMetadataDiff EMPTY = new FieldInferenceMetadataDiff( | ||
FieldInferenceMetadata.EMPTY, | ||
FieldInferenceMetadata.EMPTY | ||
) { | ||
@Override | ||
public FieldInferenceMetadata apply(FieldInferenceMetadata part) { | ||
return part; | ||
} | ||
}; | ||
@Override | ||
public FieldInferenceMetadata apply(FieldInferenceMetadata part) { | ||
ImmutableOpenMap<String, String> modelForFields = this.inferenceForFields.apply(part.inferenceIdForField); | ||
ImmutableOpenMap<String, Set<String>> copyFromFields = this.copyFromFields.apply(part.sourceFields); | ||
return new FieldInferenceMetadata(modelForFields, copyFromFields); | ||
} | ||
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@Override | ||
public void writeTo(StreamOutput out) throws IOException { | ||
inferenceForFields.writeTo(out); | ||
copyFromFields.writeTo(out); | ||
} | ||
} | ||
} |
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I've done some renamings to start using inference ids vs model