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    <p>You have various problems with what you pasted:</p> <p><strong>1) Incorrect mapping</strong></p> <p>When creating the index, you specify:</p> <pre><code>"mappings": { "files": { </code></pre> <p>But your type is actually <code>file</code>, not <code>files</code>. If you checked the mapping, you would see that immediately:</p> <pre><code>curl -XGET 'http://127.0.0.1:9200/files/_mapping?pretty=1' # { # "files" : { # "files" : { # "properties" : { # "filename" : { # "type" : "string", # "analyzer" : "filename_analyzer" # } # } # }, # "file" : { # "properties" : { # "filename" : { # "type" : "string" # } # } # } # } # } </code></pre> <p><strong>2) Incorrect analyzer definition</strong></p> <p>You have specified the <code>lowercase</code> tokenizer but that removes anything that isn't a letter, (see <a href="https://www.elastic.co/guide/en/elasticsearch/reference/current/analysis-lowercase-tokenizer.html">docs</a>), so your numbers are being completely removed.</p> <p>You can check this with the <a href="http://www.elasticsearch.org/guide/reference/api/admin-indices-analyze.html">analyze API</a>:</p> <pre><code>curl -XGET 'http://127.0.0.1:9200/_analyze?pretty=1&amp;text=My_file_2012.01.13.doc&amp;tokenizer=lowercase' # { # "tokens" : [ # { # "end_offset" : 2, # "position" : 1, # "start_offset" : 0, # "type" : "word", # "token" : "my" # }, # { # "end_offset" : 7, # "position" : 2, # "start_offset" : 3, # "type" : "word", # "token" : "file" # }, # { # "end_offset" : 22, # "position" : 3, # "start_offset" : 19, # "type" : "word", # "token" : "doc" # } # ] # } </code></pre> <p><strong>3) Ngrams on search</strong></p> <p>You include your ngram token filter in both the index analyzer and the search analyzer. That's fine for the index analyzer, because you want the ngrams to be indexed. But when you search, you want to search on the full string, not on each ngram.</p> <p>For instance, if you index <code>"abcd"</code> with ngrams of length 1 to 4, you will end up with these tokens: </p> <pre><code>a b c d ab bc cd abc bcd </code></pre> <p>But if you search on <code>"dcba"</code> (which shouldn't match) and you also analyze your search terms with ngrams, then you are actually searching on:</p> <pre><code>d c b a dc cb ba dbc cba </code></pre> <p>So <code>a</code>,<code>b</code>,<code>c</code> and <code>d</code> will match!</p> <p><strong>Solution</strong></p> <p>First, you need to choose the right analyzer. Your users will probably search for words, numbers or dates, but they probably won't expect <code>ile</code> to match <code>file</code>. Instead, it will probably be more useful to use <a href="http://www.elasticsearch.org/guide/reference/index-modules/analysis/edgengram-tokenizer.html">edge ngrams</a>, which will anchor the ngram to the start (or end) of each word.</p> <p>Also, why exclude <code>docx</code> etc? Surely a user may well want to search on the file type?</p> <p>So lets break up each filename into smaller tokens by removing anything that isn't a letter or a number (using the <a href="http://www.elasticsearch.org/guide/reference/index-modules/analysis/pattern-tokenizer.html">pattern tokenizer</a>):</p> <pre><code>My_first_file_2012.01.13.doc =&gt; my first file 2012 01 13 doc </code></pre> <p>Then for the index analyzer, we'll also use edge ngrams on each of those tokens:</p> <pre><code>my =&gt; m my first =&gt; f fi fir firs first file =&gt; f fi fil file 2012 =&gt; 2 20 201 201 01 =&gt; 0 01 13 =&gt; 1 13 doc =&gt; d do doc </code></pre> <p>We create the index as follows:</p> <pre><code>curl -XPUT 'http://127.0.0.1:9200/files/?pretty=1' -d ' { "settings" : { "analysis" : { "analyzer" : { "filename_search" : { "tokenizer" : "filename", "filter" : ["lowercase"] }, "filename_index" : { "tokenizer" : "filename", "filter" : ["lowercase","edge_ngram"] } }, "tokenizer" : { "filename" : { "pattern" : "[^\\p{L}\\d]+", "type" : "pattern" } }, "filter" : { "edge_ngram" : { "side" : "front", "max_gram" : 20, "min_gram" : 1, "type" : "edgeNGram" } } } }, "mappings" : { "file" : { "properties" : { "filename" : { "type" : "string", "search_analyzer" : "filename_search", "index_analyzer" : "filename_index" } } } } } ' </code></pre> <p>Now, test that the our analyzers are working correctly:</p> <p><strong>filename_search:</strong></p> <pre><code>curl -XGET 'http://127.0.0.1:9200/files/_analyze?pretty=1&amp;text=My_first_file_2012.01.13.doc&amp;analyzer=filename_search' [results snipped] "token" : "my" "token" : "first" "token" : "file" "token" : "2012" "token" : "01" "token" : "13" "token" : "doc" </code></pre> <p><strong>filename_index:</strong></p> <pre><code>curl -XGET 'http://127.0.0.1:9200/files/_analyze?pretty=1&amp;text=My_first_file_2012.01.13.doc&amp;analyzer=filename_index' "token" : "m" "token" : "my" "token" : "f" "token" : "fi" "token" : "fir" "token" : "firs" "token" : "first" "token" : "f" "token" : "fi" "token" : "fil" "token" : "file" "token" : "2" "token" : "20" "token" : "201" "token" : "2012" "token" : "0" "token" : "01" "token" : "1" "token" : "13" "token" : "d" "token" : "do" "token" : "doc" </code></pre> <p>OK - seems to be working correctly. So let's add some docs:</p> <pre><code>curl -X POST "http://localhost:9200/files/file" -d '{ "filename" : "My_first_file_created_at_2012.01.13.doc" }' curl -X POST "http://localhost:9200/files/file" -d '{ "filename" : "My_second_file_created_at_2012.01.13.pdf" }' curl -X POST "http://localhost:9200/files/file" -d '{ "filename" : "Another file.txt" }' curl -X POST "http://localhost:9200/files/file" -d '{ "filename" : "And_again_another_file.docx" }' curl -X POST "http://localhost:9200/files/file" -d '{ "filename" : "foo.bar.txt" }' curl -X POST "http://localhost:9200/files/_refresh" </code></pre> <p>And try a search:</p> <pre><code>curl -XGET 'http://127.0.0.1:9200/files/file/_search?pretty=1' -d ' { "query" : { "text" : { "filename" : "2012.01" } } } ' # { # "hits" : { # "hits" : [ # { # "_source" : { # "filename" : "My_second_file_created_at_2012.01.13.pdf" # }, # "_score" : 0.06780553, # "_index" : "files", # "_id" : "PsDvfFCkT4yvJnlguxJrrQ", # "_type" : "file" # }, # { # "_source" : { # "filename" : "My_first_file_created_at_2012.01.13.doc" # }, # "_score" : 0.06780553, # "_index" : "files", # "_id" : "ER5RmyhATg-Eu92XNGRu-w", # "_type" : "file" # } # ], # "max_score" : 0.06780553, # "total" : 2 # }, # "timed_out" : false, # "_shards" : { # "failed" : 0, # "successful" : 5, # "total" : 5 # }, # "took" : 4 # } </code></pre> <p>Success!</p> <p><strong>#### UPDATE ####</strong></p> <p>I realised that a search for <code>2012.01</code> would match both <code>2012.01.12</code> and <code>2012.12.01</code> so I tried changing the query to use a <a href="http://www.elasticsearch.org/guide/reference/query-dsl/text-query.html">text phrase</a> query instead. However, this didn't work. It turns out that the edge ngram filter increments the position count for each ngram (while I would have thought that the position of each ngram would be the same as for the start of the word).</p> <p>The issue mentioned in point (3) above is only a problem when using a <code>query_string</code>, <code>field</code>, or <code>text</code> query which tries to match ANY token. However, for a <code>text_phrase</code> query, it tries to match ALL of the tokens, and in the correct order.</p> <p>To demonstrate the issue, index another doc with a different date:</p> <pre><code>curl -X POST "http://localhost:9200/files/file" -d '{ "filename" : "My_third_file_created_at_2012.12.01.doc" }' curl -X POST "http://localhost:9200/files/_refresh" </code></pre> <p>And do a the same search as above:</p> <pre><code>curl -XGET 'http://127.0.0.1:9200/files/file/_search?pretty=1' -d ' { "query" : { "text" : { "filename" : { "query" : "2012.01" } } } } ' # { # "hits" : { # "hits" : [ # { # "_source" : { # "filename" : "My_third_file_created_at_2012.12.01.doc" # }, # "_score" : 0.22097087, # "_index" : "files", # "_id" : "xmC51lIhTnWplOHADWJzaQ", # "_type" : "file" # }, # { # "_source" : { # "filename" : "My_first_file_created_at_2012.01.13.doc" # }, # "_score" : 0.13137488, # "_index" : "files", # "_id" : "ZUezxDgQTsuAaCTVL9IJgg", # "_type" : "file" # }, # { # "_source" : { # "filename" : "My_second_file_created_at_2012.01.13.pdf" # }, # "_score" : 0.13137488, # "_index" : "files", # "_id" : "XwLNnSlwSeyYtA2y64WuVw", # "_type" : "file" # } # ], # "max_score" : 0.22097087, # "total" : 3 # }, # "timed_out" : false, # "_shards" : { # "failed" : 0, # "successful" : 5, # "total" : 5 # }, # "took" : 5 # } </code></pre> <p>The first result has a date <code>2012.12.01</code> which isn't the best match for <code>2012.01</code>. So to match only that exact phrase, we can do:</p> <pre><code>curl -XGET 'http://127.0.0.1:9200/files/file/_search?pretty=1' -d ' { "query" : { "text_phrase" : { "filename" : { "query" : "2012.01", "analyzer" : "filename_index" } } } } ' # { # "hits" : { # "hits" : [ # { # "_source" : { # "filename" : "My_first_file_created_at_2012.01.13.doc" # }, # "_score" : 0.55737644, # "_index" : "files", # "_id" : "ZUezxDgQTsuAaCTVL9IJgg", # "_type" : "file" # }, # { # "_source" : { # "filename" : "My_second_file_created_at_2012.01.13.pdf" # }, # "_score" : 0.55737644, # "_index" : "files", # "_id" : "XwLNnSlwSeyYtA2y64WuVw", # "_type" : "file" # } # ], # "max_score" : 0.55737644, # "total" : 2 # }, # "timed_out" : false, # "_shards" : { # "failed" : 0, # "successful" : 5, # "total" : 5 # }, # "took" : 7 # } </code></pre> <p>Or, if you still want to match all 3 files (because the user might remember some of the words in the filename, but in the wrong order), you can run both queries but increase the importance of the filename which is in the correct order:</p> <pre><code>curl -XGET 'http://127.0.0.1:9200/files/file/_search?pretty=1' -d ' { "query" : { "bool" : { "should" : [ { "text_phrase" : { "filename" : { "boost" : 2, "query" : "2012.01", "analyzer" : "filename_index" } } }, { "text" : { "filename" : "2012.01" } } ] } } } ' # [Fri Feb 24 16:31:02 2012] Response: # { # "hits" : { # "hits" : [ # { # "_source" : { # "filename" : "My_first_file_created_at_2012.01.13.doc" # }, # "_score" : 0.56892186, # "_index" : "files", # "_id" : "ZUezxDgQTsuAaCTVL9IJgg", # "_type" : "file" # }, # { # "_source" : { # "filename" : "My_second_file_created_at_2012.01.13.pdf" # }, # "_score" : 0.56892186, # "_index" : "files", # "_id" : "XwLNnSlwSeyYtA2y64WuVw", # "_type" : "file" # }, # { # "_source" : { # "filename" : "My_third_file_created_at_2012.12.01.doc" # }, # "_score" : 0.012931341, # "_index" : "files", # "_id" : "xmC51lIhTnWplOHADWJzaQ", # "_type" : "file" # } # ], # "max_score" : 0.56892186, # "total" : 3 # }, # "timed_out" : false, # "_shards" : { # "failed" : 0, # "successful" : 5, # "total" : 5 # }, # "took" : 4 # } </code></pre>
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    1. COWow, this is not just a solution. It's a tutorial I was looking for :D THX
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    3. COThat's an awesome answer. Where the +20 button on SO?
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