I am working on a golang project with database MongoDB. I have a collection with following records:
[
{
"_id": 1,
"vals": [
"110",
"2211"
]
},
{
"_id": 1,
"vals": [
"Abcd",
"102"
]
}
]
I want to perform a search like if I pass "11001" then 1st record will return. But I have not found any solution to do the same. I have tried the following query:
db.getCollection('ColName').find({"vals":{"$regex": "^11001", "$options": "i"}})
Characters that are saved in db are less that I passed in the search. If I pass the "110" or "11" then it will gives the result, but my requirement is different I have full string and need to match with 2,3, or 4 characters.
It is about regex.
db.getCollection('ColName').find({"vals":{"$regex": "^110(01)?", "$options": "i"}})
will work for you.
"?" in regex means match 0 or 1.
Related
I have a simple string and hash stored in redis
get test
"1"
hget htest first
"first hash"
I'm able to see the "table" test, but there are no columns
trino> show columns from redis.default.test;
Column | Type | Extra | Comment
--------+------+-------+---------
(0 rows)
and obviously I can't get result from select
trino> select * from redis.default.test;
Query 20210918_174414_00006_dmp3x failed: line 1:8: SELECT * not allowed from relation
that has no columns
I see in the documentation that I might need to create a table definition file, but I wasn't able to create one that will work.
I had few variations of this, but this is the one for example:
{
"tableName": "test",
"schemaName": "default",
"value": {
"dataFormat": "json",
"fields": [
{
"name": "number",
"mapping": 0,
"type": "INT"
}
]
}
}
any idea what am I doing wrong?
I focused on the string since it's simpler, but I also need to query the hash
Background:
I wish to locate the entire JSON document that has a condition where "state" = "new" and where length(Features.id) > 4
{
"id": "123"
"feedback": {
"Features": [
{
"state": "new"
"id": "12345"
}
]
}
}
This is what I have tried to do:
Since this is a nested document. My query looks like this:
A stackoverflow member has helped me to access the nested contents within the query, but is there a way to obtain the full document
I have used:
SELECT VALUE t.id FROM t IN f.feedback.Features where t.state = 'new' and length(t.id)>4
This will give me the ids.
My desire is to have access to the full document with this condition?
{
"id": "123"
"feedback": {
"Features": [
{
"state": "new"
"id": "12345"
}
]
}
}
Any help is appreciated
Try this
SELECT *
FROM f
WHERE
f.feedback.Features[0].state = 'new'
AND length(f.feedback.Features[0].id)>4
Here is the SELECT spec for CosmosDB for more details
https://learn.microsoft.com/en-us/azure/cosmos-db/sql-query-select
Also, check out "working with JSON" in CosmosDB notes
https://learn.microsoft.com/en-us/azure/cosmos-db/sql-query-working-with-json
If the Features array has more than 1 value, you can use EXISTS clause to search within them. See specs of EXISTS here with examples:
https://learn.microsoft.com/en-us/azure/cosmos-db/sql-query-subquery#exists-expression
I am new to MongoDb and have a query which I am struggling with..
I have a collection of reported users which looks like this:
{
"_id": 1,
"userId": 1,
"reason": "some reason",
"date": "2017-07-22"
}
I need a query which will add to each report the number of reports for that userId.
meaning if the collection has 3 records with userId=1. the query will return three records and each of them will also include a field
count=3 meaning the record above will now look like this:
{
"_id": 1
"userId": 1,
"reason": "some reason",
"date": "2017-07-22",
"count": 3
}
I tried using $project and $addFields aggregations but was not able to add a field which is a result of a query over the whole collection.
any ideas?
The answer provided by Veeram is correct, just that if you are running mongodb version less than 3.6, in the last stage of aggregate you might want to replace the $replaceRoot operator with a $project
aggregate([
{$group:{_id:"$userId", "data":{"$push":"$$ROOT"}, count:{$sum:1} } },
{"$unwind":"$data"},
{$project:{_id:"$data._id", userId:"$data.userId", reason:"$data.reason", date:"$data.date", count:1}}
])
I have my mapping like this:
{
"doc": {
"mappings": {
"mydocument": {
"properties": {
"file": {
"type": "attachment",
"path": "full",
"fields": {
"file": {
"type": "string",
"store": true,
"term_vector": "with_positions_offsets"
},
"author": {
...
When I search for a complete word I get the result:
"query": {
"fuzzy_like_this" : {
"fields" : ["file"],
"like_text" : "This_is_something_I_want_to_search_for",
"max_query_terms" : 12
}
},
"highlight" : {
"number_of_fragments" : 3,
"fragment_size" : 650,
"fields" : {
"file" : { }
}
}
But if I change the search term to "This_is_something_I_want" I get nothing. What am I missing?
To implement a partial match, we must first understand what fuzzy like this does and then decide what you want partial matching to return. fuzzy like this will perform 2 key functions.
The like_text will be analyzed using the default analyzer. All the resulting tokens will then be used to find documents based on term frequency, or tf-idf
This typically means that the input term will be be split on space and lowercased. This_is_something_I_want will therefore be tokenized to this_is_something_i_want. Unless you have files with this exact term, no documents will match.
Secondly, all terms will be fuzzified. Fuzzy searches score terms based on how many character changes needs to made to a word to match another word. For instance to get from bat to hat we will need to make 1 character change.
For our case to get from this_is_something_i_want to this_is_something_i_want_to_search_for, we will need to make 14 character changes (adding _to_search_for.) Standard fuzzy search only allows for 3 character changes when working with terms longer that 5 or 6 characters. Increasing the fuzzy limit to 14 will however produce severely skewed results
So neither of these functions will help produce the results you seek.
Here is what I can suggest:
You can implement an analyzer that splits on underscore similar to this. Tokens produced will then be ['this', 'is', 'something', 'i', 'want'] which can correctly be matched to to the sample case
Alternatively, if all you want is a document that starts with the specified text, you can use a phrase prefix query instead of fuzzy like this. Documentations here
I am trying to do a simple facet request over a field containing more than one word (Eg: 'Name1 Name2', sometimes with dots and commas inside) but what I get is...
"terms" : [{
"term" : "Name1",
"count" : 15
},
{
"term" : "Name2",
"count" : 15
}]
so my field value is split by spaces and then runs the facet request...
Query example:
curl -XGET http://my_server:9200/idx_occurrence/Occurrence/_search?pretty=true -d '{
"query": {
"query_string": {
"fields": [
"dataset"
],
"query": "2",
"default_operator": "AND"
}
},
"facets": {
"test": {
"terms": {
"field": [
"speciesName"
],
"size": 50000
}
}
}
}'
Your field shouldn't be analyzed, or at least not tokenized. You need to update your mapping and then reindex if you want to index the field without tokenizing it.
First of all, javanna provided a very good answer from a practical perspective. However, for the sake of completeness, I want to mention that in some cases there is a way to do it without reindexing the data.
If the speciesName field is stored and your queries produce relatively small number of results, you can use script_field to retrieve stored field values:
curl -XGET http://my_server:9200/idx_occurrence/Occurrence/_search?pretty=true -d '{
"query": {
"query_string": {
"fields": ["dataset"],
"query": "2",
"default_operator": "AND"
}
},
"facets": {
"test": {
"terms": {
"script_field": "_fields['\''speciesName'\''].value",
"size": 50000
}
}
}
}
'
As a result of this query, elasticsearch will retrieve the speciesName field for every record in your result set and it will construct facets from these values. Needless to say, if your result set contains millions of records, performance of this query might be sluggish.
Similarly, if the field is not stored, but record source is stored, you can use script_field facet to retrieve field values from the source:
......
"script_field": "_source['\''speciesName'\'']",
......
Again, source for each record in the result list will be retrieved and parsed, so you might need some patience to run this query on a large set of records.