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Elasticsearch 8.5 Custom Analyzer Not Breaking Text as Expected with Special Characters

๐Ÿ‘€ Views: 42 ๐Ÿ’ฌ Answers: 1 ๐Ÿ“… Created: 2025-06-25
elasticsearch analyzer text-processing json

I'm currently working on an Elasticsearch 8.5 setup where I've defined a custom analyzer intended to handle text with special characters. However, the analyzer doesn't seem to break down the text as expected, specifically when special characters like `@`, `#`, and `&` are involved. I've defined the analyzer in my index settings like this: ```json { "settings": { "analysis": { "analyzer": { "custom_analyzer": { "type": "custom", "tokenizer": "standard", "filter": ["lowercase", "custom_char_filter"] } }, "char_filter": { "custom_char_filter": { "type": "pattern_replace", "pattern": "[\@\#\&]", "replacement": " " } } } } } ``` Despite this configuration, when I index a document containing the text "Hello @World#2023 & Developers", the analyzer does not split the tokens as I anticipated. It seems to ignore the custom character filter completely. I've tried reindexing the data after changing the analyzer settings, but the behavior remains unchanged. Here's how I'm verifying the analyzerโ€™s output: ```json GET /my_index/_analyze { "analyzer": "custom_analyzer", "text": "Hello @World#2023 & Developers" } ``` The response I get back is `"tokens": [{"token": "hello", "start_offset": 0, "end_offset": 5, "type": "<ALPHANUM>", "position": 0}, {"token": "world2023", "start_offset": 6, "end_offset": 17, "type": "<ALPHANUM>", "position": 1}, {"token": "developers", "start_offset": 18, "end_offset": 28, "type": "<ALPHANUM>", "position": 2}]`, which shows that the special characters are not being replaced by a space as I intended. I have also looked at the Elasticsearch documentation for custom analyzers and tokenizers, but Iโ€™m still stuck. Is there something Iโ€™m missing in the analyzer configuration? Any insights on how to resolve this would be greatly appreciated! I'm coming from a different tech stack and learning Json. Any help would be greatly appreciated!