de.spinscale.elasticsearch.ingest.opennlp.OpenNlpService Maven / Gradle / Ivy

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Ingest processor that uses OpenNLP for named entity extraction
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/*
 * Copyright [2016] [Alexander Reelsen]
 *
 * Licensed 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 de.spinscale.elasticsearch.ingest.opennlp;

import opennlp.tools.namefind.NameFinderME;
import opennlp.tools.namefind.TokenNameFinderModel;
import opennlp.tools.tokenize.SimpleTokenizer;
import opennlp.tools.util.Span;
import org.apache.logging.log4j.Logger;
import org.apache.logging.log4j.message.ParameterizedMessage;
import org.apache.logging.log4j.util.Supplier;
import org.elasticsearch.ElasticsearchException;
import org.elasticsearch.common.StopWatch;
import org.elasticsearch.common.logging.Loggers;
import org.elasticsearch.common.settings.Settings;
import org.elasticsearch.common.util.set.Sets;

import java.io.IOException;
import java.io.InputStream;
import java.nio.file.Files;
import java.nio.file.Path;
import java.util.Map;
import java.util.Set;
import java.util.concurrent.ConcurrentHashMap;

/**
 * OpenNLP name finders are not thread safe, so we load them via a thread local hack
 */
public class OpenNlpService {

    private final Path configDirectory;
    private final Logger logger;
    private Settings settings;

    private ThreadLocal threadLocal = new ThreadLocal<>();
    private Map nameFinderModels = new ConcurrentHashMap<>();

    public OpenNlpService(Path configDirectory, Settings settings) {
        this.logger = Loggers.getLogger(getClass(), settings);
        this.configDirectory = configDirectory;
        this.settings = settings;
    }

    public Set getModels() {
        return IngestOpenNlpPlugin.MODEL_FILE_SETTINGS.get(settings).getAsMap().keySet();
    }

    protected OpenNlpService start() {
        StopWatch sw = new StopWatch("models-loading");
        Map settingsMap = IngestOpenNlpPlugin.MODEL_FILE_SETTINGS.get(settings).getAsMap();
        for (Map.Entry entry : settingsMap.entrySet()) {
            String name = entry.getKey();
            sw.start(name);
            Path path = configDirectory.resolve(entry.getValue());
            try (InputStream is = Files.newInputStream(path)) {
                nameFinderModels.put(name, new TokenNameFinderModel(is));
            } catch (IOException e) {
                logger.error((Supplier) () -> new ParameterizedMessage("Could not load model [{}] with path [{}]", name, path), e);
            }
            sw.stop();
        }

        if (settingsMap.keySet().size() == 0) {
            logger.error("Did not load any models for ingest-opennlp plugin, none configured");
        } else {
            logger.info("Read models in [{}] for {}", sw.totalTime(), settingsMap.keySet());
        }

        return this;
    }

    public Set find(String content, String field) {
        try {
            if (!nameFinderModels.containsKey(field)) {
                throw new ElasticsearchException("Could not find field [{}], possible values {}", field, nameFinderModels.keySet());
            }
            TokenNameFinderModel finderModel= nameFinderModels.get(field);
            if (threadLocal.get() == null || !threadLocal.get().equals(finderModel)) {
                threadLocal.set(finderModel);
            }

            String[] tokens = SimpleTokenizer.INSTANCE.tokenize(content);
            Span spans[] = new NameFinderME(finderModel).find(tokens);
            String[] names = Span.spansToStrings(spans, tokens);
            return Sets.newHashSet(names);
        } finally {
            threadLocal.remove();
        }
    }
}