I have an index, where each document represents a class, with list of students and a list of teachers.
Here is the mapping:
{
"properties" : {
"students" : {
"include_in_root" : 1,
"type" : "nested",
"properties" : {
"name" : {
"first" : "text",
"last" : "text",
},
},
"email" : { "type" : "string", "index" : "not_analyzed" },
},
"teachers" : {
"include_in_root" : 0,
"include_in_all" : 0,
"type" : "nested",
"properties" : {
"name" : {
"title" : { "type" : "string", "index" : "not_analyzed" },
"first" : "text",
"last" : "text",
},
},
},
},
}
I would like to influence Elastic Search score function, such that it will give higher score to documents with matched techers.
For example, if I have search for "Smith", I would like the documents with teacher Smith be with higher score than documents with students Smith.
Does anyone knows how it should be done in Elastic Search?
In other words, how can I return the results ordered by some logic?
Thanks in advance!
Answered here:
https://groups.google.com/forum/?fromgroups#!search/%22Use$20a$20bool$20query$20to$20run$20two$20nested$20queries%22/elasticsearch/XTAb7eHcbqI/UgnKDh7ou48J
Related
I have a table in my database as follows
my_table:jsonb
[ {
"name" : "world map",
"type" : "activated",
"map" : [ {
"displayOrder" : 0,
"value" : 123
}, {
"displayOrder" : 1,
"value" : 456
}, {
"displayOrder" : 2,
"value" : 789
} ]
}, {
"name" : "regional map",
"type" : "disabled"
} ]
I would like to create indices for the name, type and displayOrder fields, which would be the best way?
I have my json schema where all values are required. For example:
....
{
"properties" : {
"minimumDelay" : {
"type" : "number"
},
"length" : {
"type" : "number"
},
},
"required": {
"minimumDelay",
"length"
}
Here the json data will be valid if I enter both minimumDelay and length values.
But my requirement is json data must be valid when I enter either 1 of the values(like XOR case). How my schema must be modified to achieve the same?
In JSON Schema, the XOR operator is oneOf.
{
"properties" : {
"minimumDelay" : {
"type" : "number"
},
"length" : {
"type" : "number"
}
},
"oneOf": [
{ "required": ["minimumDelay"] },
{ "required": ["length"] }
]
}
My query in lucene 6.2.0 goes like:
query query = new PhraseQuery.Builder()
.add(new Term("country","russia"))
.setSlop(1)
.build();
Basically among all my documents which are:
{
"_id" : ObjectId("586b723b4b9a835db416fa26"),
"name" : "test",
"countries" : {
"country" : [
{
"name" : "russia"
},
{
"name" : "USA china"
}
]
}
}
{
"_id" : ObjectId("586b73f24b9a835fefb10ca5"),
"name" : "nitika jain",
"countries" : {
"country" : [
{
"name" : "russia and denmrk"
},
{
"name" : "USA china"
}
]
}
}
{
"_id" : ObjectId("586b744f4b9a835fefb10ca7"),
"name" : "arjun",
"countries" : {
"country" : [
{
"name" : "russia pakistan"
},
{
"name" : "india iraq"
}
]
}
}
I want a document which has only russia. Ideally it should be the one highest scored, but instead I get something like "Found 3 hits."
Document<stored,indexed,tokenized<id:586b723b4b9a835db416fa26> stored,indexed,tokenized,omitNorms,indexOptions=DOCS<name:test> stored,indexed,tokenized,omitNorms,indexOptions=DOCS<countries:{ "country" : [ { "name" : "russia"} , { "name" : "USA china"}]}> stored,indexed,tokenized<country:russia> stored,indexed,tokenized<country:USA china>>**0.12874341**
Document<stored,indexed,tokenized<id:586b73f24b9a835fefb10ca5> stored,indexed,tokenized,omitNorms,indexOptions=DOCS<name:nitika jain> stored,indexed,tokenized,omitNorms,indexOptions=DOCS<countries:{ "country" : [ { "name" : "russia and denmrk"} , { "name" : "USA china"}]}> stored,indexed,tokenized<country:russia and denmrk> stored,indexed,tokenized<country:USA china>>**0.12874341**
Document<stored,indexed,tokenized<id:586b744f4b9a835fefb10ca7> stored,indexed,tokenized,omitNorms,indexOptions=DOCS<name:arjun> stored,indexed,tokenized,omitNorms,indexOptions=DOCS<countries:{ "country" : [ { "name" : "russia pakistan"} , { "name" : "india iraq"}]}> stored,indexed,tokenized<country:russia pakistan> stored,indexed,tokenized<country:india iraq>>**0.12874341**
All 3 results are equally scored. How can I get the document with only russia to be highest scored?
In Phrase queries, the slop is zero by default, requiring exact matches. that means that if you modify your query in this way:
query query = new PhraseQuery.Builder()
.add(new Term("country","russia"))
.build();
you'll get what you're looking for.
I am using Elasticsearch with Haystacksearch and Django and want to search the follow structure:
{
{
"title": "book1",
"category" : ["Cat_1", "Cat_2"],
"key_values" :
[
{
"key_name" : "key_1",
"value" : "sample_value_1"
},
{
"key_name" : "key_2",
"value" : "sample_value_12"
}
]
},
{
"title": "book2",
"category" : ["Cat_3", "Cat_2"],
"key_values" :
[
{
"key_name" : "key_1",
"value" : "sample_value_1"
},
{
"key_name" : "key_3",
"value" : "sample_value_6"
},
{
"key_name" : "key_4",
"value" : "sample_value_5"
}
]
}
}
Right now I have set up an index model using Haystack with a "text" that put all the data together and runs a full text search! In my opinion this is not the a well established search 'cause I am not using my data set structure and hence this is some kind odd.
As an example if for an object I have a key-value
{
"key_name": "key_1",
"value": "sample_value_1"
}
and for another object I have
{
"key_name": "key_2",
"value": "sample_value_1"
}
and we it gets a query like "Key_1 sample_value_1" comes I get a thoroughly mixed result of objects who have these words in their fields rather than using their structures.
P.S. I am totally new to ElasticSearch and better to say new to the search technologies and challenges. I have searched the web and SO button didn't find anything satisfying. Please let me know if there is something wrong with my thoughts and expectations from these search engines and if there is SO duplicate question! And also if there is a better approach to design a database for this kind of search
Read the es docs on nested mappings and do something like this:
"book_type" : {
"properties" : {
// title, cat mappings
"key_values" : {
"type" : "nested"
"properties": {
"key_name": {
"type": "string", "index": "not_analyzed"
},
"value": {
"type": "string"
}
}
}
}
}
Then query using a nested query
"nested" : {
"path" : "key_values",
"query" : {
"bool" : {
"must" : [
{
"term" : {"key_values.key_name" : "key_1"}
},
{
"match" : {"key_values.value" : "sample_value_1"}
}
]
}
}
}
I have a user document which contains many tags
Here is the mapping:
{
"user" : {
"properties" : {
"tags" : {
"type" : "nested",
"properties" : {
"id" : {
"type" : "string",
"index" : "not_analyzed",
"store" : "yes"
},
"current" : {
"type" : "boolean"
},
"type" : {
"type" : "string"
},
"value" : {
"type" : "multi_field",
"fields" : {
"value" : {
"type" : "string",
"analyzer" : "name_analyzer"
},
"value_untouched" : {
"type" : "string",
"index" : "not_analyzed",
"include_in_all" : false
}
}
}
}
}
}
}
}
Here are the sample user documents:
User 1
{
"created_at": 1317484762000,
"updated_at": 1367040856000,
"tags": [
{
"type": "college",
"value": "Dhirubhai Ambani Institute of Information and Communication Technology",
"id": "a6f51ef8b34eb8f24d1c5be5e4ff509e2a361829"
},
{
"type": "company",
"value": "alma connect",
"id": "58ad4afcc8415216ea451339aaecf311ed40e132"
},
{
"type": "company",
"value": "Google",
"id": "93bc8199c5fe7adfd181d59e7182c73fec74eab5",
"current": true
},
{
"type": "discipline",
"value": "B.Tech.",
"id": "a7706af7f1477cbb1ac0ceb0e8531de8da4ef1eb",
"institute_id": "4fb424a5addf32296f00013a"
},
]
}
User 2:
{
"created_at": 1318513355000,
"updated_at": 1364888695000,
"tags": [
{
"type": "college",
"value": "Dhirubhai Ambani Institute of Information and Communication Technology",
"id": "a6f51ef8b34eb8f24d1c5be5e4ff509e2a361829"
},
{
"type": "college",
"value": "Bharatiya Vidya Bhavan's Public School, Jubilee hills, Hyderabad",
"id": "d20730345465a974dc61f2132eb72b04e2f5330c"
},
{
"type": "company",
"value": "Alma Connect",
"id": "93bc8199c5fe7adfd181d59e7182c73fec74eab5"
},
{
"type": "sector",
"value": "Website and Software Development",
"id": "dc387d78fc99ab43e6ae2b83562c85cf3503a8a4"
}
]
}
User 3:
{
"created_at": 1318513355001,
"updated_at": 1364888695010,
"tags": [
{
"type": "college",
"value": "Dhirubhai Ambani Institute of Information and Communication Technology",
"id": "a6f51ef8b34eb8f24d1c5be5e4ff509e2a361821"
},
{
"type": "sector",
"value": "Website and Software Development",
"id": "dc387d78fc99ab43e6ae2b83562c85cf3503a8a1"
}
]
}
Using the above ES documents for search, I want to construct a query where I need to fetch users who have company tags in nested tag documents or the users who do not have any company tags. What will be my search query?
For example in above case, if search for google tag, then the returned documents should be 'user 1' and 'user 3' (as user 1 has company tag google and user 3 has no company tag). User 2 is not returned as it has a company tag other than google too.
Not trivial at all, mainly due to the not have a type:company tag clause. Here's what I came up with:
{
"or" : {
"filters" : [ {
"nested" : {
"filter" : {
"and" : {
"filters" : [ {
"term" : {
"tags.value" : "google"
}
}, {
"term" : {
"tags.type" : "company"
}
} ]
}
},
"path" : "tags"
}
}, {
"not" : {
"filter" : {
"nested" : {
"filter" : {
"term" : {
"tags.type" : "company"
}
},
"path" : "tags"
}
}
}
} ]
}
}
It contains an or filter with two nested clauses: the first one finds the documents that have tags.type:company and tags.value:google, while the second one finds all the documents that don't have any tags.type:company.
This needs to be optimized though since and/or/not filters don't take advantage of caching for filters that work with bitsets, like the term filter does. It would be best to take some more time to find a way to use a bool filter and obtain the same result. Have a lookt this article to know more.