I have a problem regarding searching in elasticsearch.
I have a index with multiple documents with several fields. I want to be able to search over all the fields running a query and want it to return all the documents that contains the value specified in the query. I Found that using simple_query_string
worked well for this. However, it does not return consistent results. In my index I have documents with several fields that contain dates. For example:
"revisionDate" : "2008-01-01T00:00:00",
"projectSmirCreationDate" : "2008-07-01T00:00:00",
"changedDate" : "1971-01-01T00:00:00",
"dueDate" : "0001-01-01T00:00:00",
Those are just a few examples, however when I index for example:
GET new_document-20_v2/_search
{
"size": 1000,
"query": {
"simple_query_string" : {
"query": "2008"
}
}
}
It only returns two documents, this is a problem because I have much more documents than just two that contains the value "2008" in their fields.
I also have problem searching file names. In my index there are fields that contain fileNames like this:
"fileName" : "testPDF.pdf",
"fileName" : "demo.pdf",
"fileName" : "demo.txt",
When i query:
GET new_document-20_v2/_search
{
"size": 1000,
"query": {
"simple_query_string" : {
"query": "demo"
}
}
}
I get no results But if i query:
GET new_document-20_v2/_search
{
"size": 1000,
"query": {
"simple_query_string" : {
"query": "demo.txt"
}
}
}
I get the proper result.
Is there any better way to search across all documents and fields than I did? I want it to return all the document matching the query and not just two or zero. Any help would be greatly appreciated.
Elasticsearch uses a standard analyzer if no analyzer is specified. Since no analyzer is specified on "fileName"
, demo.txt
gets tokenized to
{
"tokens": [
{
"token": "demo.txt",
"start_offset": 0,
"end_offset": 8,
"type": "<ALPHANUM>",
"position": 0
}
]
}
Now when you are searching for demo
it will not give any result, but searching for demo.txt
will give the result.
You can instead use a wildcard query to search for a document having demo
in fileName
{
"query": {
"wildcard": {
"fileName": {
"value": "demo*"
}
}
}
}
Search Result will be
"hits": [
{
"_index": "67303015",
"_type": "_doc",
"_id": "2",
"_score": 1.0,
"_source": {
"fileName": "demo.pdf"
}
},
{
"_index": "67303015",
"_type": "_doc",
"_id": "3",
"_score": 1.0,
"_source": {
"fileName": "demo.txt"
}
}
]
Since revisionDate
, projectSmirCreationDate
, changedDate
, dueDate
are all of type date
, so you cannot do a partial search on these dates.
You can use multi-fields, to add one more field (of text
type) in the above fields. Modify your index mapping as shown below
{
"mappings": {
"properties": {
"changedDate": {
"type": "date",
"fields": {
"raw": {
"type": "text"
}
}
},
"projectSmirCreationDate": {
"type": "date",
"fields": {
"raw": {
"type": "text"
}
}
},
"dueDate": {
"type": "date",
"fields": {
"raw": {
"type": "text"
}
}
},
"revisionDate": {
"type": "date",
"fields": {
"raw": {
"type": "text"
}
}
}
}
}
}
Index Data:
{
"revisionDate": "2008-02-01T00:00:00",
"projectSmirCreationDate": "2008-02-01T00:00:00",
"changedDate": "1971-01-01T00:00:00",
"dueDate": "0001-01-01T00:00:00"
}
{
"revisionDate": "2008-01-01T00:00:00",
"projectSmirCreationDate": "2008-07-01T00:00:00",
"changedDate": "1971-01-01T00:00:00",
"dueDate": "0001-01-01T00:00:00"
}
Search Query:
{
"query": {
"multi_match": {
"query": "2008"
}
}
}
Search Result:
"hits": [
{
"_index": "67303015",
"_type": "_doc",
"_id": "2",
"_score": 1.0,
"_source": {
"revisionDate": "2008-01-01T00:00:00",
"projectSmirCreationDate": "2008-07-01T00:00:00",
"changedDate": "1971-01-01T00:00:00",
"dueDate": "0001-01-01T00:00:00"
}
},
{
"_index": "67303015",
"_type": "_doc",
"_id": "1",
"_score": 0.18232156,
"_source": {
"revisionDate": "2008-02-01T00:00:00",
"projectSmirCreationDate": "2008-02-01T00:00:00",
"changedDate": "1971-01-01T00:00:00",
"dueDate": "0001-01-01T00:00:00"
}
}
]