assertNotNull(normalizer);
    }

    @Test
    public void testCreateDefaultAnalyzer() {
        // Test creating default analyzer
        AnalyzerSettings.DefaultContentsAnalyzer analyzer = SuggestUtil.createDefaultAnalyzer(client, settings);
        assertNotNull(analyzer);
    }

    @Test
    public void testGetAsList() {
        // Test with null

 * in compliance with, at your election, the Elastic License 2.0 or the Server
 * Side Public License, v 1.
 */

package org.elasticsearch.benchmark.search.aggregations;

import org.apache.lucene.analysis.Analyzer;
import org.apache.lucene.search.IndexSearcher;
import org.apache.lucene.search.MatchAllDocsQuery;
import org.apache.lucene.search.Query;
import org.elasticsearch.common.breaker.CircuitBreaker;

        // Test with field config parameters
        configParameters = "field.config.analyzer=standard\nfield.config.store=true";
        result = ParameterUtil.createConfigParameterMap(configParameters);
        assertEquals(2, result.get(ConfigName.FIELD).size());
        assertEquals("standard", result.get(ConfigName.FIELD).get("analyzer"));
        assertEquals("true", result.get(ConfigName.FIELD).get("store"));

                .prepareIndex()
                .setIndex(suggester.settings().analyzer().getAnalyzerSettingsIndexName())
                .setSource(analyzerMapping)
                .setRefreshPolicy(WriteRequest.RefreshPolicy.WAIT_UNTIL)
                .execute()
                .actionGet();
        suggester.settings().analyzer().init();

        SuggestSettings settings = suggester.settings();

          }
        }
      },
      {
        "lang_cs": {
          "match": "*_cs",
          "mapping": {
            "type": "text",
            "analyzer": "czech_analyzer"
          }
        }
      },
      {
        "lang_da": {
          "match": "*_da",
          "mapping": {
            "type": "text",
            "analyzer": "danish_analyzer"
          }

          "token_chars": []
        },
        "bigram_tokenizer": {
          "type": "ngram",
          "min_gram": 2,
          "max_gram": 2,
          "token_chars": []
        }
      },
      "analyzer": {
        "arabic_analyzer": {
          "type": "custom",
          "tokenizer": "standard",
          "filter": [
            "truncate20_filter",
            "lowercase",
            "arabic_stop",

          }
        }
      },
      {
        "lang_cs": {
          "match": "*_cs",
          "mapping": {
            "type": "text",
            "analyzer": "czech_analyzer"
          }
        }
      },
      {
        "lang_da": {
          "match": "*_da",
          "mapping": {
            "type": "text",
            "analyzer": "danish_analyzer"
          }

important to a subset of users, especially if it requires extra dependencies.

The canonical example of this is the ICU analysis plugin. It is important for
folks who want the fairly language neutral ICU analyzer but the library to
implement the analyzer is 11MB so we don't ship it with Elasticsearch by
default.

Another example is the `discovery-gce` plugin. It is *vital* to folks running

        "discard_punctuation" : "false"
      },
      "fess_korean_normal": {
        "type": "seunjeon_tokenizer",
        "index_eojeol": false,
        "user_words": ["덕후", "버카충", "낄끼빠빠" ]
      }
    },
    "analyzer" : {
      "reading_analyzer" : {
        "type" : "custom",
        "tokenizer" : "fess_japanese_normal",
        "filter" : ["reading_form"]
      },
      "reading_term_analyzer" : {
        "type" : "custom",

      },
      "fess_korean_normal": {
        "type": "fess_korean_tokenizer",
        "decompound_mode": "mixed",
        "user_dict_path": "${fess.dictionary.path}ko/nori.txt"
      }
    },
    "analyzer" : {
      "reading_analyzer" : {
        "type" : "custom",
        "tokenizer" : "fess_japanese_normal",
        "filter" : ["reading_form"]
      },
      "reading_term_analyzer" : {
        "type" : "custom",