Elastic Search Wildcard query with space failing 7.11 - elasticsearch

I am having my data indexed in elastic search in version 7.11. This is my mapping i got when i directly added documents to my index.
{"properties":{"name":{"type":"text","fields":{"keyword":{"type":"keyword","ignore_above":256}}}
I havent added the keyword part but no idea where it came from.
I am running a wild card query on the same. But unable to get data for keywords with spaces.
{
"query": {
"bool":{
"should":[
{"wildcard": {"name":"*hello world*"}}
]
}
}
}
Have seen many answers related to not_analyzed . And i have tried updating {"index":"true"} in mapping but with no help. How to make the wild card search work in this version of elastic search
Tried adding the wildcard field
PUT http://localhost:9001/indexname/_mapping
{
"properties": {
"name": {
"type" :"wildcard"
}
}
}
And got following response
{
"error": {
"root_cause": [
{
"type": "illegal_argument_exception",
"reason": "mapper [name] cannot be changed from type [text] to [wildcard]"
}
],
"type": "illegal_argument_exception",
"reason": "mapper [name] cannot be changed from type [text] to [wildcard]"
},
"status": 400
}
Adding a sample document to match
{
"_index": "accelerators",
"_type": "_doc",
"_id": "602ec047a70f7f30bcf75dec",
"_score": 1.0,
"_source": {
"acc_id": "602ec047a70f7f30bcf75dec",
"name": "hello world example",
"type": "Accelerator",
"description": "khdkhfk ldsjl klsdkl",
"teamMembers": [
{
"userId": "karthik.r#gmail.com",
"name": "Karthik Ganesh R",
"shortName": "KR",
"isOwner": true
},
{
"userId": "anand.sajan#gmail.com",
"name": "Anand Sajan",
"shortName": "AS",
"isOwner": false
}
],
"sectorObj": [
{
"item_id": 14,
"item_text": "Cross-sector"
}
],
"geographyObj": [
{
"item_id": 4,
"item_text": "Global"
}
],
"technologyObj": [
{
"item_id": 1,
"item_text": "Artificial Intelligence"
}
],
"themeColor": 1,
"mainImage": "assets/images/Graphics/Asset 35.svg",
"features": [
{
"name": "Ideation",
"icon": "Asset 1007.svg"
},
{
"name": "Innovation",
"icon": "Asset 1044.svg"
},
{
"name": "Strategy",
"icon": "Asset 1129.svg"
},
{
"name": "Intuitive",
"icon": "Asset 964.svg"
},
],
"logo": {
"actualFileName": "",
"fileExtension": "",
"fileName": "",
"fileSize": 0,
"fileUrl": ""
},
"customLogo": {
"logoColor": "#B9241C",
"logoText": "EC",
"logoTextColor": "#F6F6FA"
},
"collaborators": [
{
"userId": "muhammed.arif#gmail.com",
"name": "muhammed Arif P T",
"shortName": "MA"
},
{
"userId": "anand.sajan#gmail.com",
"name": "Anand Sajan",
"shortName": "AS"
}
],
"created_date": "2021-02-18T19:30:15.238000Z",
"modified_date": "2021-03-11T11:45:49.583000Z"
}
}

You cannot modify a field mapping once created. However, you can create another sub-field of type wildcard, like this:
PUT http://localhost:9001/indexname/_mapping
{
"properties": {
"name": {
"type": "text",
"fields": {
"wildcard": {
"type" :"wildcard"
},
"keyword": {
"type" :"keyword",
"ignore_above":256
}
}
}
}
}
When the mapping is updated, you need to reindex your data so that the new field gets indexed, like this:
POST http://localhost:9001/indexname/_update_by_query
And then when this finishes, you'll be able to query on this new field like this:
{
"query": {
"bool": {
"should": [
{
"wildcard": {
"name.wildcard": "*hello world*"
}
}
]
}
}
}

Related

Cannot seem to use must and must_not together in an elastic search query

If I run the following query:
{
"query": {
"bool": {
"must": [
{
"multi_match": {
"query": "boxing",
"fuzziness": 2,
"minimum_should_match": 2
}
}
],
"must_not": [
{
"terms_set": {
"allowedCountries": {
"terms": ["gb", "mx"],
"minimum_should_match_script": {
"source": "2"
}
}
}
}
],
"filter": [
{
"range": {
"expireTime": {
"gt": 1674061907954
}
}
},
{
"term": {
"region": {
"value": "row"
}
}
},
{
"term": {
"sourceType": {
"value": "article"
}
}
}
]
}
}
}
against an index with articles that look like:
{
"_index": "content-items-v10",
"_type": "_doc",
"_id": "e7hm75ui4dma1mm4j8q5v7914",
"_score": 4.3724976,
"_source": {
"allowedCountries": ["gb", "ie"],
"body": "Both Joshua Buatsi and Craig Richards join The DAZN Boxing Show ahead of their clash at London's O2 Arena. Matchroom's Eddie Hearn also gives his take on the night, as well as Chantelle Cameron previewing her contest with Victoria Noelia Bustos.",
"competitions": [
{
"id": "8lo6205qyio0fksjx9glqbdhj",
"name": "Buatsi v Richards"
}
],
"contestants": [
{
"id": "7rq59j3eiamxlm12vhxcsgujj",
"name": "Joshua Buatsi"
},
{
"id": "boby9oqe23g6qyuwphrxh8su5",
"name": "Craig Richards"
}
],
"countries": [
{
"id": "7yasa43laq1nb2e6f8bfuvxed",
"name": "World"
},
{
"id": "258l9t5sm55592i08mdpqzr3t",
"name": "United Kingdom"
}
],
"dotsLastUpdateTime": 1673979749396,
"expireTime": 4800000000000,
"fixtureDate": {},
"headline": "Buatsi vs. Richards: Preview",
"id": "e7hm75ui4dma1mm4j8q5v7914",
"importance": 0,
"languageKeys": ["en"],
"languages": ["en"],
"lastUpdateTime": {
"ts": 1653088281000,
"iso8601": "2022-05-20T23:11:21.000Z"
},
"promoImageUrl": null,
"publication": {
"typeId": "1plcw0iyhx9vn1fcanbm2ja3rf",
"typeName": "Shoulder"
},
"publishedTime": {
"ts": 1653088281000,
"iso8601": "2022-05-20T23:11:21.000Z"
},
"region": "row",
"shortHeadline": null,
"sourceType": "article",
"sports": [
{
"id": "2x2oqzx60orpoeugkd754ga17",
"name": "Boxing"
}
],
"teaser": "",
"thumbnailImageUrl": "https://images.daznservices.com/di/library/babcock_canada/45/3e/the-dazn-boxing-show-20052022_xc4jbfqi022l1shq9lu641h9e.png?t=-477976832",
"translations": {}
}
}
I get the following validation error from elasticsearch:
{
"ok": false,
"errors": {
"validation": [
{
"message": "\"query.bool.must_not\" is not allowed",
"path": [
"query",
"bool",
"must_not"
],
"type": "object.unknown",
"context": {
"child": "must_not",
"label": "query.bool.must_not",
"value": [
{
"terms_set": {
"allowedCountries": {
"terms": [
"gb",
"mx"
],
"minimum_should_match_script": {
"source": "2"
}
}
}
}
],
"key": "must_not"
}
}
]
},
"correlationId": "d29e9275-9ab3-4ff8-944d-852b98d4b503"
}
And I cannot figure out what the issue might be! From the elastic docs it should be OK.
I'm using ElasticSearch 7.9.3 running in a local docker container.
I'm hoping someone out there will give me a clue!
Cheers!
I would expect this to just work.
I'm trying to filter out articles that have both of the country codes gb and mx in the field allowedCountries.
I can include them easily enough in the results when I add the terms_set query to the bool.must section of the query.
It works well, you just need to enclose your query in the query section
{
"query": { <--- add this
"bool": { <--- your query starts here
"must": [
...
Thank you for responding!
I was helping with a system I did not have full context on - it turns out there is a proxy in the mix with validation that was blocking the must_not query. So, with the proxy fixed, it now works.

Elasticsearch - nested types vs collapse/aggs

I have a use case where I need to find the latest data based on some fields.
The fields are:
category.name
category.type
createdAt
For example: search for the newest data where category.name = 'John G.' AND category.type = 'A'. I expect the data with ID = 1 where it matches the criteria and is the newest one based on createdAt field ("createdAt": "2022-04-18 19:09:27.527+0200")
The problem is that category.* is a nested field and I can't aggs/collapse these fields because ES doesn't support it.
Mapping:
PUT data
{
"mappings": {
"properties": {
"createdAt": {
"type": "date",
"format": "yyyy-MM-dd HH:mm:ss.SSSZ"
},
"category": {
"type": "nested",
"properties": {
"name": {
"type": "text",
"analyzer": "keyword"
}
}
},
"approved": {
"type": "text",
"analyzer": "keyword"
}
}
}
}
Data:
POST data/_create/1
{
"category": [
{
"name": "John G.",
"level": "A"
},
{
"name": "Chris T.",
"level": "A"
}
],
"createdBy": "John",
"createdAt": "2022-04-18 19:09:27.527+0200",
"approved": "no"
}
POST data/_create/2
{
"category": [
{
"name": "John G.",
"level": "A"
},
{
"name": "Chris T.",
"level": "A"
}
],
"createdBy": "Max",
"createdAt": "2022-04-10 10:09:27.527+0200",
"approved": "no"
}
POST data/_create/3
{
"category": [
{
"name": "Rick J.",
"level": "B"
}
],
"createdBy": "Rick",
"createdAt": "2022-03-02 02:09:27.527+0200",
"approved": "no"
}
I'm looking for either a search query that can handle that in an acceptable performant way, or a new object design without nested type where I could take advantage of aggs/collapse feature.
Any suggestion will be really appreciated.
About your first question,
For example: search for the newest data where category.name = 'John G.' AND category.type = 'A'. I expect the data with ID = 1 where it matches the criteria and is the newest one based on createdAt field ("createdAt": "2022-04-18 19:09:27.527+0200")
I believe you can do something along those lines:
GET /72088168/_search
{
"query": {
"nested": {
"path": "category",
"query": {
"bool": {
"must": [
{
"match": {
"category.name": "John G."
}
},
{
"match": {
"category.level": "A"
}
}
]
}
}
}
},
"sort": [
{
"createdAt": {
"order": "desc"
}
}
],
"size":1
}
For the 2nd matter, it really depends on what you are aiming to do. could merge category.name and category.level in the same field. Such that you document would look like:
{
"category": ["John G. A","Chris T. A"],
"createdBy": "Max",
"createdAt": "2022-04-10 10:09:27.527+0200",
"approved": "no"
}
No more nested needed. Although I agree it feels like using tape to fix your issue.

Elastic search array of objects nested range aggregation

I'm trying to make range aggregation on the following data set:
{
"ProductType": 1,
"ProductDefinition": "fc588f8e-14f2-4871-891f-c73a4e3d17ca",
"ParentProduct": null,
"Sku": "074617",
"VariantSku": null,
"Name": "Paraboot Avoriaz/Jannu Marron Brut Marron Brown Hiking Boot Shoes",
"AllowOrdering": true,
"Rating": null,
"ThumbnailImageUrl": "/media/1106/074617.jpg",
"PrimaryImageUrl": "/media/1106/074617.jpg",
"Categories": [
"399d7b20-18cc-46c0-b63e-79eadb9390c7"
],
"RelatedProducts": [],
"Variants": [
"84a7ff9f-edf0-4aab-87f9-ba4efd44db74",
"e2eb2c50-6abc-4fbe-8fc8-89e6644b23ef",
"a7e16ccc-c14f-42f5-afb2-9b7d9aefbc5c"
],
"PriceGroups": [
"86182755-519f-4e05-96ef-5f93a59bbaec"
],
"DisplayName": "Paraboot Avoriaz/Jannu Marron Brut Marron Brown Hiking Boot Shoes",
"ShortDescription": "",
"LongDescription": "<ul><li>Paraboot Avoriaz Mountaineering Boots</li><li>Marron Brut Marron (Brown)</li><li>Full leather inners and uppers</li><li>Norwegien Welted Commando Sole</li><li>Hand made in France</li><li>Style number : 074617</li></ul><p>As featured on Pritchards.co.uk</p>",
"UnitPrices": {
"EUR 15 pct": 343.85
},
"Taxes": {
"EUR 15 pct": 51.5775
},
"PricesInclTax": {
"EUR 15 pct": 395.4275
},
"Slug": "paraboot-avoriazjannu-marron-brut-marron-brown-hiking-boot-shoes",
"VariantsProperties": [
{
"Key": "ShoeSize",
"Value": "8"
},
{
"Key": "ShoeSize",
"Value": "10"
},
{
"Key": "ShoeSize",
"Value": "6"
}
],
"Guid": "0d4f6899-c66a-4416-8f5d-26822c3b57ae",
"Id": 178,
"ShowOnHomepage": true
}
I'm aggregating on VariantsProperties which have the following mapping
"VariantsProperties": {
"type": "nested",
"properties": {
"Key": {
"type": "keyword"
},
"Value": {
"type": "keyword"
}
}
}
Terms aggregations are working fine with following code:
{
"aggs": {
"Nest": {
"nested": {
"path": "VariantsProperties"
},
"aggs": {
"fieldIds": {
"terms": {
"field": "VariantsProperties.Key"
},
"aggs": {
"values": {
"terms": {
"field": "VariantsProperties.Value"
}
}
}
}
}
}
}
}
However when I try to do a range aggregation to get shoes in size between 8 - 12 such as:
{
"aggs": {
"Nest": {
"nested": {
"path": "VariantsProperties"
},
"aggs": {
"fieldIds": {
"range": {
"field": "VariantsProperties.Value",
"ranges": [ { "from": 8, "to": 12 }]
}
}
}
}
}
}
I get the following error:
{
"error": {
"root_cause": [
{
"type": "illegal_argument_exception",
"reason": "Field [VariantsProperties.Value] of type [keyword] is not supported for aggregation [range]"
}
],
"type": "search_phase_execution_exception",
"reason": "all shards failed",
"phase": "query",
"grouped": true,
"failed_shards": [
{
"shard": 0,
"index": "product-avenueproductindexdefinition-24476f82-en-us",
"node": "ejgN4XecT1SUfgrhzP8uZg",
"reason": {
"type": "illegal_argument_exception",
"reason": "Field [VariantsProperties.Value] of type [keyword] is not supported for aggregation [range]"
}
}
],
"caused_by": {
"type": "illegal_argument_exception",
"reason": "Field [VariantsProperties.Value] of type [keyword] is not supported for aggregation [range]",
"caused_by": {
"type": "illegal_argument_exception",
"reason": "Field [VariantsProperties.Value] of type [keyword] is not supported for aggregation [range]"
}
}
},
"status": 400
}
Is there a way to "transform" the terms aggregation into a range aggregation, without the need of changing the schema? I know I could build the ranges myself by extracting the data from the terms aggregation and building the ranges out of it, however, I would prefer a solution within the elastic itself.
There are two ways to solve this:
Option A: Use a script instead of a field. This option will work without having to reindex your data, but depending on your volume of data, the performance might suffer.
POST test/_search
{
"aggs": {
"Nest": {
"nested": {
"path": "VariantsProperties"
},
"aggs": {
"fieldIds": {
"range": {
"script": "Integer.parseInt(doc['VariantsProperties.Value'].value)",
"ranges": [
{
"from": 8,
"to": 12
}
]
}
}
}
}
}
}
Option B: Add an integer sub-field in your mapping.
PUT my-index/_mapping
{
"properties": {
"VariantsProperties": {
"type": "nested",
"properties": {
"Key": {
"type": "keyword"
},
"Value": {
"type": "keyword",
"fields": {
"numeric": {
"type": "integer",
"ignore_malformed": true
}
}
}
}
}
}
}
Once your mapping is modified, you can run _update_by_query on your index in order to reindex the VariantsProperties.Value data
PUT my-index/_update_by_query
Finally, when this last command is done, you can run the range aggregation on the VariantsProperties.Value.numeric field.
Also note that this second but will be more performant on the long term.

Elasticsearch: Why can't I use "5m" for precision in context queries?

I'm running on Elasticsearch 5.5
I have a document with the following mapping
"mappings": {
"shops": {
"properties": {
"locations": {
"type": "geo_point"
},
"name": {
"type": "keyword"
},
"suggest": {
"type": "completion",
"contexts": [
{
"name": "location",
"type": "GEO",
"precision": "10m",
"path": "locations"
}
]
}
}
}
I'll add a document as follows:
PUT my_index/shops
{
"name":"random shop",
"suggest":{
"input":"random shop"
},
"locations":[
{
"lat":42.38471212,
"lon":-71.12612357
}
]
}
I try to query for the document with the follow JSON call
GET my_shops/_search
{
"suggest": {
"result": {
"prefix": "random",
"completion": {
"field": "suggest",
"size": 5,
"fuzzy": true,
"contexts": {
"location": [{
"lat": 42.38471212,
"lon": -71.12612357,
"precision": "10mi"
}]
}
}
}
}
}
I get the following errors:
(source: discourse.org)
But when I change the "precision" field to an int, I get the intended search results.
I'm confused on two fronts.
Why is there a context error? The documentation seems to say that this is ok
https://www.elastic.co/guide/en/elasticsearch/reference/5.5/suggester-context.html
Why can't I use string values for the precision values?
At the bottom of the page, I see that the precision values can take either distances or numeric values.

Highlight on ElasticSearch autocomplete

I have the following data to be indexed on ElasticSearch.
I want to implement an autocomplete feature, and highlight why a specific document matched a query.
This are the settings of my index:
{
"settings": {
"number_of_shards": 1,
"analysis": {
"filter": {
"autocomplete_filter": {
"type": "edge_ngram",
"min_gram": 1,
"max_gram": 15
}
},
"analyzer": {
"autocomplete": {
"type": "custom",
"tokenizer": "standard",
"filter": [
"autocomplete_filter"
]
}
}
}
}
}
Index Analyzing
Splits text on word boundaries.
Removes pontuation.
Lowercases
Edge NGrams each token
So the Inverted Index looks like:
This is how i defined the mappings for a name field:
{
"index_type": {
"properties": {
"name": {
"type": "string",
"index_analyzer": "autocomplete",
"search_analyzer": "standard"
}
}
}
}
When I query:
GET http://localhost:9200/index/type/_search
{
"query": {
"match": {
"name": "soft"
}
},
"highlight": {
"fields" : {
"name" : {}
}
}
}
Search for: soft
Applying the Standard Tokenizer, the "soft" is the term, to find on the inverted index. This search matches the Documents: 1, 3, 4, 5, 6, 7 which is correct, but the highlighted part I would expect to be "soft" and not the whole word:
{
"hits": [
{
"_source": {
"name": "SoftwareRocks everytime"
},
"highlight": {
"name": [
"<em>SoftwareRocks</em> everytime"
]
}
},
{
"_source": {
"name": "Software AG"
},
"highlight": {
"name": [
"<em>Software</em> AG"
]
}
},
{
"_source": {
"name": "Software AG2"
},
"highlight": {
"name": [
"<em>Software</em> AG2"
]
}
},
{
"_source": {
"name": "Op Software AG good software better"
},
"highlight": {
"name": [
"Op <em>Software</em> AG good <em>software</em> better"
]
}
},
{
"_source": {
"name": "Op Software AG"
},
"highlight": {
"name": [
"Op <em>Software</em> AG"
]
}
},
{
"_source": {
"name": "is soft ware ok"
},
"highlight": {
"name": [
"is <em>soft</em> ware ok"
]
}
}
]
}
Search for: software ag
Applying the Standard Tokenizer, the "software ag" is transformed into "software" and "ag", to find on the inverted index. This search matches the Documents: 1, 3, 4, 5, 6, which is correct, but the highlighted part I would expect to be "software" and "ag" and not the whole word around "software" and "ag":
{
"hits": [
{
"_source": {
"name": "Software AG"
},
"highlight": {
"name": [
"<em>Software</em> <em>AG</em>"
]
}
},
{
"_source": {
"name": "Software AG2"
},
"highlight": {
"name": [
"<em>Software</em> <em>AG2</em>"
]
}
},
{
"_source": {
"name": "Op Software AG"
},
"highlight": {
"name": [
"Op <em>Software</em> <em>AG</em>"
]
}
},
{
"_source": {
"name": "Op Software AG good software better"
},
"highlight": {
"name": [
"Op <em>Software</em> <em>AG</em> good <em>software</em> better"
]
}
},
{
"_source": {
"name": "SoftwareRocks everytime"
},
"highlight": {
"name": [
"<em>SoftwareRocks</em> everytime"
]
}
}
]
}
I read the highlight documentation on elasticsearch, but I cannot understand how the highlighting is performed. For the two examples above I expect only the matched token on the inverted index to be highlighted and not the whole word.
Can anyone help how to highlight only the passed value?
Update
So, in seems that on ElasticSearch website, the autocomplete on the server side is similar to my implementation. However it seems that they highlight the matched query on the client.
If they do like this, I started to think that there is not a proper solution to do it on ElasticSearch side, so I implemented the highlight feature on server side instead of on client side(as they seem to do).
My implementation on server side(using PHP) is:
public function search($term)
{
$params = [
'index' => $this->getIndexName(),
'type' => $this->getIndexType(),
'body' => [
'query' => [
'match' => [
'name' => $term
]
]
]
];
$results = $this->client->search($params);
$hits = $results['hits']['hits'];
$data = [];
$wrapBefore = '<strong>';
$wrapAfter = '</strong>';
foreach ($hits as $hit) {
$data[] = [
$hit['_source']['id'],
$hit['_source']['name'],
preg_replace("/($term)/i", "$wrapBefore$1$wrapAfter", strip_tags($hit['_source']['name']))
];
}
return $data;
}
Outputs what I aimed with this question:
I added a bounty to see if there is a solution at ElasticSearch level to achive what I described above.
As of now with latest version of elastic this is not possible as highligh documentation don't refer any settings or query for this. I checked elastic autocomplete example in browser console under xhr requests tab and found the response for "att" autocomplete response for keyword as follows.
url - https://search.elastic.co/suggest?q=att
{
"current_page": 1,
"last_page": 4,
"total_hits": 49,
"hits": [
{
"tags": [],
"url": "/elasticon/tour/2016/jp/not-attending",
"section": "Elasticon",
"title": "Not <em>Attending</em> - JP"
},
{
"section": "Elasticon",
"title": "<em>Attending</em> from Training - JP",
"tags": [],
"url": "/elasticon/tour/2016/jp/attending-training"
},
{
"tags": [],
"url": "/elasticon/tour/2016/jp/attending-keynote",
"title": "<em>Attending</em> from Keynote - JP",
"section": "Elasticon"
},
{
"tags": [],
"url": "/elasticon/tour/2016/not-attending",
"section": "Elasticon",
"title": "Thank You - Not <em>Attending</em>"
},
{
"tags": [],
"url": "/elasticon/tour/2016/attending",
"section": "Elasticon",
"title": "Thank You - <em>Attending</em>"
},
{
"section": "Blog",
"title": "What It's Like to <em>Attend</em> Elastic Training",
"tags": [],
"url": "/blog/what-its-like-to-attend-elastic-training"
},
{
"tags": "Elasticsearch",
"url": "/guide/en/elasticsearch/plugins/5.0/mapper-attachments-highlighting.html",
"section": "Docs/",
"title": "Highlighting <em>attachments</em>"
},
{
"title": "<em>attachments</em> » email",
"section": "Docs/",
"tags": "Logstash",
"url": "/guide/en/logstash/5.0/plugins-outputs-email.html#plugins-outputs-email-attachments"
},
{
"section": "Docs/",
"title": "Configuring Email <em>Attachments</em> » Actions",
"tags": "Watcher",
"url": "/guide/en/watcher/2.4/actions.html#configuring-email-attachments"
},
{
"url": "/guide/en/watcher/2.4/actions.html#hipchat-action-attributes",
"tags": "Watcher",
"title": "HipChat Action <em>Attributes</em> » Actions",
"section": "Docs/"
},
{
"title": "Slack Action <em>Attributes</em> » Actions",
"section": "Docs/",
"tags": "Watcher",
"url": "/guide/en/watcher/2.4/actions.html#slack-action-attributes"
}
],
"aggs": {
"sections": [
{
"Elasticon": 5
},
{
"Blog": 1
},
{
"Docs/": 43
}
],
"top_tags": [
{
"XPack": 14
},
{
"Elasticsearch": 12
},
{
"Watcher": 9
},
{
"Logstash": 4
},
{
"Clients": 3
},
{
"Shield": 1
}
]
}
}
But on frontend they are showing "att" only highlighted on in the autosuggest results. Hence they are handling the highlight stuff on browser layer.

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