I am working on search functionality and I need to execute a simple query that checks if there is anything matching the search string converted to lowercase. In simpler terms, user searches "SiteName", and I query if there is anything matching "sitename".
However, I get an error when I use LOWER() function in the query.
This is what I tried:
POST /_sql?format=json
{
"query":"SELECT siteid, sitename FROM zones WHERE
sitename LIKE LOWER('SiteFirst') ", "fetch_size" : 90
}
and I get this error:
{
"error" : {
"root_cause" : [
{
"type" : "parsing_exception",
"reason" : "line 1:70: mismatched input 'LOWER' expecting {'?',
STRING}"
}
],
"type" : "parsing_exception",
"reason" : "line 1:70: mismatched input 'LOWER' expecting {'?', STRING}",
"caused_by" : {
"type" : "input_mismatch_exception",
"reason" : null
}
},
"status" : 400
}
This same query works without LOWER().
Any suggestions about how to fix this error?
Thanks!
I'm pretty sure the LOWER is called LCASE in ES SQL.
More importantly, LIKE works only on exact fields, plus it's recommended to use MATCH instead of LIKE.
So try this:
POST /_sql?format=json
{
"query": "SELECT siteid, sitename FROM zones WHERE MATCH(sitename, 'SiteFirst')",
"fetch_size": 90
}
Related
Thank you for first.
MongoDB Version:4.2.11
I have a piece of data like this:
{
"name":...,
...
"administration" : [
{"name":...,"job":...},
{"name":...,"job":...}
],
"shareholder" : [
{"name":...,"proportion":...},
{"name":...,"proportion":...},
]
}
I want to match some specified data through regular expressions:
For a example：
db.collection.aggregate([
{"$match" :
{
"$or" :
[
{"name" : {"$regex": "Keyword"}}
{"administration.name": {"$regex": "Keyword"}},
{"shareholder.name": {"$regex": "Keyword"}},
]
}
},
])
I want to set a flag when the $or operator successfully matches any condition, which is represented by a custom field, for example:{"name" : {"$regex": "Keyword"}}Execute on success:
{"$project" :
{
"_id":false,
"name" : true,
"__regex_type__" : "name"
}
},
{"administration.name" : {"$regex": "Keyword"}}Execute on success:"__regex_type__" : "administration.name"
I try do this:
{"$project" :
{
"_id":false,
"name" : true,
"__regex_type__" :
{
"$switch":
{
"branches":
[
{"case": {"$regexMatch":{"input":"$name","regex": "Keyword"}},"then" : "name"},
{"case": {"$regexMatch":{"input":"$administration.name","regex": "Keyword"}},"then" : "administration.name"},
{"case": {"$regexMatch":{"input":"$shareholder.name","regex": "Keyword"}},"then" : "shareholder.name"},
],
"default" : "Other matches"
}
}
}
},
But $regexMatch cannot match the array,I tried to use $unwind again, but returned the number of many array members, which did not meet my starting point.
I want to implement the same function as mysql this SQL statement in mongodb, like this:
SELECT name,administration.name,shareholder.name,(
CASE
WHEN name REGEXP("Keyword") THEN "name"
WHEN administration.name REGEXP("Keyword") THEN "administration.name"
WHEN shareholder.name REGEXP("Keyword") THEN "shareholder.name"
END
)AS __regex_type__ FROM db.mytable WHERE
name REGEXP("Keyword") OR
shareholder.name REGEXP("Keyword") OR
administration.name REGEXP("Keyword");
Maybe this method is stupid, but I don’t have a better solution.
If you have a better solution, I would appreciate it!!!
Thank you!!!
Since $regexMatch does not handle arrays, use $filter to filter individual array elements with $regexMatch, then use $size to see how many elements matched.
[{"$match"=>{"$or"=>[{"a"=>"test"}, {"arr.a"=>"test"}]}},
{"$project"=>
{"a"=>1,
"arr"=>1,
"src"=>
{"$switch"=>
{"branches"=>
[{"case"=>{"$regexMatch"=>{"input"=>"$a", "regex"=>"test"}},
"then"=>"a"},
{"case"=>
{"$gte"=>
[{"$size"=>
{"$filter"=>
{"input"=>"$arr.a",
"cond"=>
{"$regexMatch"=>{"input"=>"$$this", "regex"=>"test"}}}}},
1]},
"then"=>"arr.a"}],
"default"=>"def"}}}}]
[{"_id"=>BSON::ObjectId('5ffb2df748966813f82f15ad'), "a"=>"test", "src"=>"a"},
{"_id"=>BSON::ObjectId('5ffb2df748966813f82f15ae'),
"arr"=>[{"a"=>"test"}],
"src"=>"arr.a"}]
I am trying to make a Mongodb query in Mule with the $in function, but mule says Invalid input '$', expected Namespace or NameIdentifier
have a collection that stores user authorization
{
"_id" : ObjectId("584a0dea073d4c3e976140a9"),
"partnerDataAccess" : [
{
"factoryID" : "Fac-1",
"partnerID" : "Part-1"
}
],
"userID" : "z12",
}
{
"_id" : ObjectId("584f5eba073d4c3e976140ab"),
"partnerDataAccess" : [
{
"factoryID" : "Fac-1",
"partnerID" : "Part-2"
},
{
"factoryID" : "Fac-2",
"partnerID" : "Part-2"
}
],
"userID" : "w12",
}
the flow will submit a userID and partnerID and query the database to see if authorization exist
when I query from Robo 3T, I write queries like this
e.g. user w12 and partner Part-2
db.getCollection('user').find({
userID:"w12", "partnerDataAccess.partnerID": {$in : ["Part-2", "ALL"]}
})
The $in was used because there is the "ALL" setting for admins
but while I try to put the find part into the Mongodb connector, Mule gives error during development and runtime
Hardcoded:
<mongo:find-one-document collectionName="user" doc:name="Find one document" doc:id="a03a6689-6b9d-473c-b8a6-3b8d1e989e38" config-ref="MongoDB_Config">
<mongo:find-query ><![CDATA[#[{
userID:"w12",
"partnerDataAccess.partnerID": {$in : ["Part-2", "ALL"]}
}]]]></mongo:find-query>
</mongo:find-one-document>
parametized
<mongo:find-one-document collectionName="user" doc:name="Find one document" doc:id="a03a6689-6b9d-473c-b8a6-3b8d1e989e38" config-ref="MongoDB_Config">
<mongo:find-query ><![CDATA[#[{
userID: payload.User,
"partnerDataAccess.partnerID": {$in : [ payload.partner, "ALL"]}
}]]]></mongo:find-query>
</mongo:find-one-document>
Error:
during development:
Invalid input '$', expected } or ~ or , (line 3, column 38):
Runtime:
Message : "Script '{
userID:"w12",
"partnerDataAccess.partnerID": {$in : ["Part-2", "ALL"]}
} ' has errors:
Invalid input '$', expected Namespace or NameIdentifier (line 3, column 38):
at 3 : 3" evaluating expression:
I have tried removing the $ or escaping the $ with backslash but it does not work
I know my query is not actually complex, welcome any help
seems to have found the correct way
><![CDATA[#[{
userID:"w12",
"partnerDataAccess.partnerID": {"\$in" : ["Part-2", "ALL"]}
}]]]>
I have been trying multiple queries but still can't figure it out. I have multiple documents that look like this:
{
"_id" : ObjectId("5b51f519a33e7f54161a0efb"),
"assigneesEmail" : [
"felipe#gmail.com"
],
"organizationId" : "5b4e0de37accb41f3ac33c00",
"organizationName" : "PaidUp Volleyball Club",
"type" : "athlete",
"firstName" : "Mylo",
"lastName" : "Fernandes",
"description" : "",
"status" : "active",
"createOn" : ISODate("2018-07-20T14:43:37.610Z"),
"updateOn" : ISODate("2018-07-20T14:43:37.610Z"),
"__v" : 0
}
I need help writing a query where I can find this document by looking up the email in any part of the array element assigneeEmail. Any suggestions? I have tried $elemMatch but still could not get it to work.
Looks like my query was just incorrect. I figured it out.
Hi when working in Backand I try to run the following query:
{
"object": "dr_persons",
"q": {
"person_type" : "4"
},
"fields": ["first_name", "last_name"]
}
person_type is a table in mysql db with "4" as a value.
When I run it I get this error:
Errors in Query
Please fix the following errors in the query:
not a valid constant for field person_type of object dr_persons
The only thing I can see is that when I sync my db it makes it a "float" which I can't change. Can anyone give me some direction on this?
The error message is due to the constant "4" being a string. According to the field type, float, it should be a number. Hence your query should be:
{
"object": "dr_persons",
"q": {
"person_type" : 4
},
"fields": ["first_name", "last_name"]
}
I am using Facet Terms to get all the unique values and their count for a field. And I am getting wrong results.
term: web
Count: 1191979
term: misc
Count: 1191979
term: passwd
Count: 1191979
term: etc
Count: 1191979
While the actual result should be:
term: WEB-MISC /etc/passwd
Count: 1191979
Here is my sample query:
{
"facets": {
"terms1": {
"terms": {
"field": "message"
}
}
}
}
If reindexing is an option, it would be the best to change mapping and mark this fields as not_analyzed
"your_field" : { "type": "string", "index" : "not_analyzed" }
You can use multi field type if keeping an analyzed version of the field is desired:
"your_field" : {
"type" : "multi_field",
"fields" : {
"your_field" : {"type" : "string", "index" : "analyzed"},
"untouched" : {"type" : "string", "index" : "not_analyzed"}
}
}
This way, you can continue using your_field in the queries, while running facet searches using your_field.untouched.
Alternatively, if this field is stored, you can use a script field facet instead:
"facets" : {
"term" : {
"terms" : {
"script_field" : "_fields.your_field.value"
}
}
}
As the last resort, if this field is not stored, but record source is stored in the index, you can try this:
"facets" : {
"term" : {
"terms" : {
"script_field" : "_source.your_field"
}
}
}
The first solution is the most efficient. The last solution is the least efficient and may take a lot of time on a large index.
Wow, I also got this same issue today while term aggregating in the recent elastic-search. After googling and some partial understanding, found how this geeky indexing works(which is very simple).
Queries can find only terms that actually exist in the inverted index
When you index the following string
"WEB-MISC /etc/passwd"
it will be passed to an analyzer. The analyzer might tokenize it into
"WEB", "MISC", "etc" and "passwd"
with its position details. And this tokens might filtered to lowercase such as
"web", "misc", "etc" and "passwd"
So, after indexing,the search query can see the above 4 only. not the complete word "WEB-MISC /etc/passwd". For your requirement the following are my options you can use
1.Change the Default Analyzer used by elasticsearch([link][1])
2.If it is not need, just TurnOff the analyzer by setting 'not_analyzed' for the fields you need
3.To convert the already indexed data searchable, re-indexing is the only option
I have briefly explained this problem and proposed two solutions here.
I have talked about multiple approaches here.
One is use of not_analyzed to preserve the string as it is. But then as it has the drawback of being case insensitive , a better approach would be use keyword tokenizer + lowercase filter