# Partial substring search that contains whitespaces or special chars like file contains "1 - document" doesnt work **URL:** \ **Category:** Elasticsearch\ **Created:** [December 3, 2021, 11:47am UTC](https://discuss.elastic.co/t/partial-substring-search-that-contains-whitespaces-or-special-chars-like-file-contains-1-document-doesnt-work/290883 "2021-12-03T11:47:06Z")\ **Posts on this page:** 3\ **Page:** 1
**Author:** ![agonzalez](https://avatars.discourse-cdn.com/v4/letter/a/ba8739/32.png) [@agonzalez](https://discuss.elastic.co/u/agonzalez)\ **Post date:** [December 3, 2021, 11:47am UTC](https://discuss.elastic.co/t/partial-substring-search-that-contains-whitespaces-or-special-chars-like-file-contains-1-document-doesnt-work/290883/1 "2021-12-03T11:47:06Z")
We have an application that store and query data in Elasticsearch. We have a problem when searching for partial substrings that contains a word with special chats like "notepad++.exe" or "/folder1/file1.txt" or "new text doc". Per example searching for "1 document" the search return strange things like file with names as "1 - copy.rtf", "1.rtf", etc I think this is very common scenario for searches of files with spaces and special chars but looks like there is no out of the box solution for this? We have tried these analyzer but looks like they always split the the string in tokens when there is a special char: ana\_s\_lc ana\_w\_lc ana\_s\_lc\_st Sample query to search all document that match or contais _1 document_ : ```auto GET /fileevents-*/_search { "from":0, "_source":{"includes":["fileName"]}, "query":{ "bool":{ "must":[ { "query_string":{ "allow_leading_wildcard":true, "default_field":"fileName", "query":"* 1 document *" } } ] } } } ``` result: ```auto { "took" : 18, "timed_out" : false, "_shards" : { "total" : 4, "successful" : 4, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : { "value" : 10000, "relation" : "gte" }, "max_score" : 8.271101, "hits" : [ { "_index" : "fileevents-2021.11", "_type" : "_doc", "_id" : "80229def-0c8d-4471-a352-a711f6e212e2", "_score" : 8.271101, "_source" : { "fileName" : "1.rtf" } }, { "_index" : "fileevents-2021.11", "_type" : "_doc", "_id" : "cd8edb43-47de-4213-a2f1-7a2f97b84221", "_score" : 8.271101, "_source" : { "fileName" : "1 - Copy.rtf" } }, { "_index" : "fileevents-2021.11", "_type" : "_doc", "_id" : "a366be45-440c-44ea-8c19-dc9516877ce8", "_score" : 8.271101, "_source" : { "fileName" : "1.rtf" } }, { "_index" : "fileevents-2021.11", "_type" : "_doc", "_id" : "e4a8dd40-7ce5-4981-a99c-0050d1e36b68", "_score" : 8.271101, "_source" : { "fileName" : "1 - Copy.rtf" } }, { "_index" : "fileevents-2021.11", "_type" : "_doc", "_id" : "6ab91de1-60ed-4bd5-88f1-b907c67d6edc", "_score" : 8.271101, "_source" : { "fileName" : "1.txt" } }, { "_index" : "fileevents-2021.11", "_type" : "_doc", "_id" : "df29ca8a-d26c-49b6-a7e3-b07c86a16bc5", "_score" : 8.271101, "_source" : { "fileName" : "1.txt" } }, { "_index" : "fileevents-2021.11", "_type" : "_doc", "_id" : "ae724e3e-f773-4b5d-a6e0-f4249a7f0086", "_score" : 7.0889215, "_source" : { "fileName" : "Document sin etiquetar manual.docx" } }, { "_index" : "fileevents-2021.11", "_type" : "_doc", "_id" : "e856f160-1d85-4598-be0d-3e8a7dff6574", "_score" : 7.0889215, "_source" : { "fileName" : "Document sin etiquetar manual.docx" } }, { "_index" : "fileevents-2021.11", "_type" : "_doc", "_id" : "d330fad1-490a-4d60-a6c1-39d92aeede59", "_score" : 7.0129147, "_source" : { "fileName" : "msword_file@1.docx" } }, { "_index" : "fileevents-2021.11", "_type" : "_doc", "_id" : "62ba1863-80a8-43a9-b5e9-147f92288225", "_score" : 7.0129147, "_source" : { "fileName" : "msword_file@1.docx" } } ] } } ``` index settings ```auto { "fileevents-2021.12" : { "settings" : { "index" : { "routing" : { "allocation" : { "include" : { "_tier_preference" : "data_content" } } }, "number_of_shards" : "1", "provided_name" : "fileevents-2021.12", "creation_date" : "1638452525018", "analysis" : { "filter" : { "lowercase" : { "type" : "lowercase" } }, "normalizer" : { "nor_lc" : { "filter" : [ "lowercase" ], "type" : "custom" } }, "analyzer" : { "ana_path_lc" : { "filter" : [ "lowercase" ], "type" : "custom", "tokenizer" : "tok_path" }, "ana_w_lc" : { "filter" : [ "lowercase" ], "type" : "custom", "tokenizer" : "whitespace" }, "ana_s_lc" : { "filter" : [ "lowercase" ], "type" : "custom", "tokenizer" : "standard" } }, "tokenizer" : { "tok_path" : { "type" : "path_hierarchy", "delimiter" : """\""" } } }, "number_of_replicas" : "1", "uuid" : "Jcq710KrR0yxxhzCf9qpzA", "version" : { "created" : "7130299" } } } } } ``` So any search we do for a partial string that contains special chars or whitespaces doesnt work. ---
**Author:** ![Mark\_Harwood](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/mark_harwood/32/10538_2.png) [@Mark\_Harwood](https://discuss.elastic.co/u/Mark_Harwood)\ **Post date:** [December 3, 2021, 4:49pm UTC](https://discuss.elastic.co/t/partial-substring-search-that-contains-whitespaces-or-special-chars-like-file-contains-1-document-doesnt-work/290883/2 "2021-12-03T16:49:06Z")
Perhaps a tokenised text field is not as useful as the keyword or wildcard fields for file names etc. see [Find strings within strings faster with the Elasticsearch wildcard field | Elastic Blog](https://www.elastic.co/blog/find-strings-within-strings-faster-with-the-new-elasticsearch-wildcard-field) ---
**Author:** ![system](https://us1.discourse-cdn.com/elastic/original/3X/1/a/1ac57faf039f6b580b3f104ef42a2a89e41014de.png) [@system](https://discuss.elastic.co/u/system)\ **Post date:** [December 31, 2021, 4:49pm UTC](https://discuss.elastic.co/t/partial-substring-search-that-contains-whitespaces-or-special-chars-like-file-contains-1-document-doesnt-work/290883/3 "2021-12-31T16:49:24Z")
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