Basically i'm trying to implement tags functionality on a model.
> db.event.distinct("tags")
[ "bar", "foo", "foobar" ]
Doing a simple distinct query retrieves me all distinct tags. However how would i go about getting all distinct tags that match a certain query? Say for example i wanted to get all tags matching foo and then expecting to get ["foo","foobar"] as a result?
The following queries is my failed attempts of achieving this:
> db.event.distinct("tags",/foo/)
[ "bar", "foo", "foobar" ]
> db.event.distinct("tags",{tags: {$regex: 'foo'}})
[ "bar", "foo", "foobar" ]
The aggregation framework and not the .distinct() command:
db.event.aggregate([
// De-normalize the array content to separate documents
{ "$unwind": "$tags" },
// Filter the de-normalized content to remove non-matches
{ "$match": { "tags": /foo/ } },
// Group the "like" terms as the "key"
{ "$group": {
"_id": "$tags"
}}
])
You are probably better of using an "anchor" to the beginning of the regex is you mean from the "start" of the string. And also doing this $match before you process $unwind as well:
db.event.aggregate([
// Match the possible documents. Always the best approach
{ "$match": { "tags": /^foo/ } },
// De-normalize the array content to separate documents
{ "$unwind": "$tags" },
// Now "filter" the content to actual matches
{ "$match": { "tags": /^foo/ } },
// Group the "like" terms as the "key"
{ "$group": {
"_id": "$tags"
}}
])
That makes sure you are not processing $unwind on every document in the collection and only those that possibly contain your "matched tags" value before you "filter" to make sure.
The really "complex" way to somewhat mitigate large arrays with possible matches takes a bit more work, and MongoDB 2.6 or greater:
db.event.aggregate([
{ "$match": { "tags": /^foo/ } },
{ "$project": {
"tags": { "$setDifference": [
{ "$map": {
"input": "$tags",
"as": "el",
"in": { "$cond": [
{ "$eq": [
{ "$substr": [ "$$el", 0, 3 ] },
"foo"
]},
"$$el",
false
]}
}},
[false]
]}
}},
{ "$unwind": "$tags" },
{ "$group": { "_id": "$tags" }}
])
So $map is a nice "in-line" processor of arrays but it can only go so far. The $setDifference operator negates the false matches, but ultimately you still need to process $unwind to do the remaining $group stage for distinct values overall.
The advantage here is that arrays are now "reduced" to only the "tags" element that matches. Just don't use this when you want a "count" of the occurrences when there are "multiple distinct" values in the same document. But again, there are other ways to handle that.
Related
I am currently trying to optimize some queries by using aggregation pipelines. Now I want to have a $match stage that filters out most of the collection documents in order to speed up the following stages.
The problem I am facing is that the documents in the collection do contain fields that represent regular expressions.
I now want to match strings against these regular expressions (preferably in the first $match stage).
This is how my current solution looks. But I am not really happy with this in terms of readability and probably performance.
[
{$match: {
name: "docName"
}
},
{$addFields: {
fieldAMatches: {$regexMatch: {input: "ABC", regex: '$fieldA'
}
}
}
},
{$match: {
fieldAMatches: true
}
}
]
A sample dataset would look the following:
[
{
"_id": 1,
"name": "docName",
"fieldA": ".*"
},
{
"_id": 2,
"name": "docName",
"fieldA": "AB.*"
},
{
"_id": 3,
"name": "docName",
"fieldA": "AB.+"
},
{
"_id": 4,
"name": "docName",
"fieldA": "BAC"
}
]
The result contains the following documents:
[
{
"_id": 1,
"name": "docName",
"fieldA": ".*"
},
{
"_id": 2,
"name": "docName",
"fieldA": "AB.*"
},
{
"_id": 3,
"name": "docName",
"fieldA": "AB.+"
},
]
You can use $expr do achieve this, from the docs:
$match takes a document that specifies the query conditions. The query syntax is identical to the read operation query syntax; i.e. $match does not accept raw aggregation expressions. Instead, use a $expr query expression to include aggregation expression in $match.
Meaning by using $expr we can include aggregation expression (and in our case $regexMatch) in $match stage like so:
db.collection.aggregate([
{
$match: {
name: "docName",
$expr: {
$regexMatch: {
input: "ABC",
regex: "$fieldA"
}
}
}
}
])
Mongo Playground
I have following json structure in my mongodb.
{
"country": "spain",
"language": "spanish",
"words": [
{
"word": "hello1",
....
},
{
"word": "hello2",
....
},
{
"word": "test",
....
},
]
}
I am trying to get all the dictionaries inside 'words' list which have particular substring matched.
For example, If I have a substring 'hel', then how should I query my document using mongoengine that gives two dictionary with word : 'hello1' and 'hello2'
The following query works only for matched word not with the substring.
data = Data.objects.filter(words__match={"word":"hel"})
// data is empty in this case([])
Using $elemMatch (match in mongoengine) will return the first element that matches the criteria, from the array.
You need to use aggregation to return all matching elements from your array:
pipeline = [
{ "$unwind": "$words" },
{ "$match": {"words.word": {"$regex": "hel"} } },
{ "$project": {"word":"$words.word", "_id":0} },
]
Article.objects.aggregate(*pipeline)
result:
{u'word': u'hello1'}
{u'word': u'hello2'}
Note, using this project stage you need to know all the fields in advance so you can specify them in the projection to return them.
You can also use this project for a different output, to return all fields but wrapped in a 'words dict':
pipeline = [
{ "$unwind": "$words" },
{ "$match": {"words.word": {"$regex": "hel"} } },
{ "$project": {"words":1, "_id":0} },
]
result:
{u'words': {u'otherfield': 1.0, u'word': u'hello1'}}
{u'words': {u'otherfield': 1.0, u'word': u'hello2'}}
I would like to ask if exists some documentation which describe how to work with Elasticseach pattern regex.
I need to write Pattern Capture Token Filter which filter only tokes start with specific word. For example input tokens stream should be like ("abcefgh", "abc123" , "aabbcc", "abc", "abdef") and my tokenizer will return only tokes abcefgh , abc123, abc because those tokens start with "abc".
Can someone help me how to achieve this use-case?
Thanks.
I suggest something like this:
"analysis": {
"analyzer": {
"my_trim_keyword_analyzer": {
"type": "custom",
"tokenizer": "keyword",
"filter": [
"lowercase",
"trim",
"generate_tokens",
"eliminate_tokens",
"remove_empty"
]
}
},
"filter": {
"eliminate_tokens": {
"pattern": "^(?!abc)\\w+$",
"type": "pattern_replace",
"replacement": ""
},
"generate_tokens": {
"type": "pattern_capture",
"preserve_original": 1,
"patterns": [
"(([a-z]+)(\\d*))"
]
},
"remove_empty": {
"type": "stop",
"stopwords": [""]
}
}
}
If your tokens are the result of a pattern_capture filter, you'd need to add after this filter the one called eliminate_tokens in my example which basically matches token that don't start with abc. Those that don't match are replaced by empty string ("replacement": "").
After this, to remove the empty tokens I added the remove_empty filter which is basically a stop filter where the stopword is "" (empty string).
Mongodb allows regex expression of pattern /pattern/ without using $regex expression.
http://docs.mongodb.org/manual/reference/operator/query/in/
How can i do it using morphia ?
If i give Field criteria with field operator as in and value of type "java.util.regex.Pattern" then the equivalent query generated in
$in:[$regex: 'given pattern'] which wont return expected results at all.
Expectation: $in :[ /pattern1 here/,/pattern2 here/]
Actual using 'Pattern' object : $in : [$regex:/pattern1 here/,$regex:/pattern 2 here/]
I'm not entirely sure what to make of your code examples, but here's a working Morphia code snippet:
Pattern regexp = Pattern.compile("^" + email + "$", Pattern.CASE_INSENSITIVE);
mongoDatastore.find(EmployeeEntity.class).filter("email", regexp).get();
Note that this is really slow. It can't use an index and will always require a full collection scan, so avoid it at all cost!
Update: I've added a specific code example. The $in is not required to search inside an array. Simply use /^I/ as you would in string:
> db.profile.find()
{
"_id": ObjectId("54f3ac3fa63f282f56de64bd"),
"tags": [
"India",
"Australia",
"Indonesia"
]
}
{
"_id": ObjectId("54f3ac4da63f282f56de64be"),
"tags": [
"Island",
"Antigua"
]
}
{
"_id": ObjectId("54f3ac5ca63f282f56de64bf"),
"tags": [
"Spain",
"Mexico"
]
}
{
"_id": ObjectId("54f3ac6da63f282f56de64c0"),
"tags": [
"Israel"
]
}
{
"_id": ObjectId("54f3ad17a63f282f56de64c1"),
"tags": [
"Germany",
"Indonesia"
]
}
{
"_id": ObjectId("54f3ad56a63f282f56de64c2"),
"tags": [
"ireland"
]
}
> db.profile.find({ tags: /^I/ })
{
"_id": ObjectId("54f3ac3fa63f282f56de64bd"),
"tags": [
"India",
"Australia",
"Indonesia"
]
}
{
"_id": ObjectId("54f3ac4da63f282f56de64be"),
"tags": [
"Island",
"Antigua"
]
}
{
"_id": ObjectId("54f3ac6da63f282f56de64c0"),
"tags": [
"Israel"
]
}
{
"_id": ObjectId("54f3ad17a63f282f56de64c1"),
"tags": [
"Germany",
"Indonesia"
]
}
Note: The position in the array makes no difference, but the search is case sensitive. Use /^I/i if this is not desired or Pattern.CASE_INSENSITIVE in Java.
Single RegEx Filter
use .filter(), .criteria(), or .field()
query.filter("email", Pattern.compile("reg.*exp"));
// or
query.criteria("email").contains("reg.*exp");
// or
query.field("email").contains("reg.*exp");
Morphia converts this into:
find({"email": { $regex: "reg.*exp" } })
Multiple RegEx Filters
query.or(
query.criteria("email").contains("reg.*exp"),
query.criteria("email").contains("reg.*exp.*2"),
query.criteria("email").contains("reg.*exp.*3")
);
Morphia converts this into:
find({"$or" : [
{"email": {"$regex": "reg.*exp"}},
{"email": {"$regex": "reg.*exp.*2"}},
{"email": {"$regex": "reg.*exp.*3"}}
]
})
Unfortunately,
You cannot use $regex operator expressions inside an $in.
MongoDB Manual 3.4
Otherwise, we could do:
Pattern[] patterns = new Pattern[] {
Pattern.compile("reg.*exp"),
Pattern.compile("reg.*exp.*2"),
Pattern.compile("reg.*exp.*3"),
};
query.field().in(patterns);
hopefully, one day morphia will support that :)
My collection contains the following two documents
{
"BornYear": 2000,
"Type": "Zebra",
"Owners": [
{
"Name": "James Bond",
"Phone": "007"
}
]
}
{
"BornYear": 2012,
"Type": "Dog",
"Owners": [
{
"Name": "James Brown",
"Phone": "123"
},
{
"Name": "Sarah Frater",
"Phone": "345"
}
]
}
I would like to find all the animals whichs have an owner called something with James.
I try to unwind the Owners array, but cannot get access to the Name variable.
Bit of a misnomer here. To just find the "objects" or items in a "collection" then all you really need to do is match the "object/item"
db.collection.find({
"Owners.Name": /^James/
})
Which works, but does not of course limit the results to the "first" match of "James", which would be:
db.collection.find(
{ "Owners.Name": /^James/ },
{ "Owners.$": 1 }
)
As a basic projection. But that does not give any more than a "single" match, which means you need the .aggregate() method instead like so:
db.collection.aggregate([
// Match the document
{ "$match": {
"Owners.Name": /^James/
}},
// Flatten or de-normalize the array
{ "$unwind": "Owners" },
// Filter th content
{ "$match": {
"Owners.Name": /^James/
}},
// Maybe group it back
{ "$group": {
"_id": "$_id",
"BornYear": { "$first": "$BornYear" },
"Type": { "$first": "$Type" },
"Ownners": { "$push": "$Owners" }
}}
])
And that allows more than one match in a sub-document array while filtering.
The other point is the "anchor" or "^" caret on the regular expression. You really need it where you can, to make matches at the "start" of the string where an index can be properly used. Open ended regex operations cannot use an index.
You can use dot notation to match against the fields of array elements:
db.test.find({'Owners.Name': /James/})