In MongoDB, Java driver how to use "explain" with aggregate? - java

In MongoDB Java driver how to use the "explain" option ?
db.orders.aggregate([
{ $match: { status: "A" } },
{ $sort: { total: -1 } }
],
{ explain: true }
)
Collection.aggregate() does not accept options
orders.aggregate(Arrays.asList(
Aggregates.match(Filters.eq("status","A")),
Aggregates.sort(Sorts.descending("total"))
))

You can fall back to runCommand and use the explain command that way.
Something along the lines of
db.runCommand(new Document(myMap))
where myMap is (writing in JSON)
{"explain": {"aggregate": "my.collection", "pipeline": [{"$project": {"_id": 1}}]}}

Related

Springboot: How to execute custom mongodb query by springboot?

I want to find a list of models matched either field nameEnglish or nameChinese by a keyword. I spent more than an hour googling but I cannot do it. Please help.
Springboot Mongo starter example https://spring.io/guides/gs/accessing-data-mongodb/
The custom query I want to execute and return a list result
db.mymodel.aggregate([
{
$match: {
$or :[
{ nameChinese: /門/ },
{ nameEnglish: /cocina/i }
]
}
},
{ $sort: {nameEnglish: 1} }
])
My best trial so far
interface MyModelRepository : MongoRepository<MyModel, String> {
#Query(value = "{ '\$match': { \$or: [ {'nameEnglish': { \$regex: ?0 } }, {'nameChinese': { \$regex: ?0 } } ] }")
fun findByMyQuery(name: String): List<MyModel>
}
For the regex, I also want it to be case insensitive.
I found the answer after a hot water shower ( and one day of googling and reading documents). Hope this help someone in the future.
#Query(value = "{ \$or: [ {'nameEnglish': { \$regex: ?0, \$options: 'i'}}, {'nameChinese': { \$regex: ?0 }}] }", sort = "{nameEnglish: 1}")

Compare two json structure and get mismatch changes

Hi I have json structure #1 and #2 as follows. I would like to compare and capture the results.
Json #1.
{
"menu": {
"id": "file",
"popup": {
"menuitem": {
"menuitem-1": "sometext",
"menuitem-2": {
"menuitem-2.1": "sometext",
"menuitem-2.2": "sometext",
"menuitem-2.3": {
"menuitem-2.3.1": "sometext"
}
}
}
},
"value": "File"
}
}
Json #2
{
"menu": {
"id": "file",
"popup": {
"menuitem": {
"menuitem-2.3": {
"menuitem-2.3.1": "sometext"
}
"menuitem-1": "sometext",
"menuitem-2": {
"menuitem-2.1": "sometext",
"menuitem-2.2": "sometext"
},
}
},
"value": "File"
}
}
Am expecting that below JSON has been moved up in JSON #2. My goal here is identify any CREATE NEW / UPDATE / ADJUSTED / DELETE on JSON#2.
"menuitem-2.3": {
"menuitem-2.3.1": "sometext"
}
Is there any Spring / Java existing framework available to achieve above?
Use difference from org.apache.commons.lang.StringUtils.
Compares two Strings, and returns the portion where they differ. (More precisely, return the remainder of the second String, starting from where it's different from the first.)
For example,
difference("i am a machine", "i am a robot") -> "robot".
StringUtils.difference(null, null) = null
StringUtils.difference("", "") = ""
StringUtils.difference("", "abc") = "abc"
StringUtils.difference("abc", "") = ""
StringUtils.difference("abc", "abc") = ""
StringUtils.difference("ab", "abxyz") = "xyz"
StringUtils.difference("abcde", "abxyz") = "xyz"
StringUtils.difference("abcde", "xyz") = "xyz"
Parameters:
str1 - the first String, may be null
str2 - the second String, may be null
Try using Apache drill. It is easy to install and supports querying JSON. You can then execute a minus query and get the difference.
You can also query drill using java. Apache drill has a JDBC driver for that.
Hope it helps. :)

How to use join at a same type or index in ElasticSearch like solr

Now I got a problem as I need to query some data from a type(or index) named 'product', and I have three parameters( $p1, $p2, $p3) which can determine some catagories,then I need get all the product in those catagories.
I know how it can be done in MySQL like this:
select *
from product
where catagory in (
select catagory
from product
where p1 = $p1 and p2=$p2 and p3=$p3
)
And I know I can do this in solr like
{!join from=catagory to=catagory}p1:$p1 AND p2:$p2 AND p3:$p3
But I want to know how can I do this in ElasticSearch.
BTW,sorry for my pool English. I do appreciate for your help.
after I look through official docs, this can be resolved like this:
1. create your index with a join type
put /product
{
"mappings":{
"cata" : {
"properties" : {
"join_field": {
"type": "join",
"relations": {
"header": "line"
}
}
}
}
}
}
create a header data
post /product
{
"p1":"1",
"p2":"2",
"p3":"3",
"join_field":"header"
}
return with "_id:"xxx"
create a line data
post /cata?routing=xxx (! routing must be header's '_id',so is 'parent' below)
{
"p1":"1",
"p2":"1",
"p3":"1",
"other":"others...",
"join_field":{
"name": "line",
"parent": "xxx"
}
}
4. query data
post /cata/_search
{
"query": {
"has_parent" : {
"parent_type" : "header",
"query" : {
"has_child" : {
"type" : "line",
"query" : {
"term" : {
"other" : "others..."
}
}
}
}
}
}
}
the way above fix my problem

Two Aggregate Totals in One Group

I wrote a query in MongoDB as follows:
db.getCollection('student').aggregate(
[
{
$match: { "student_age" : { "$ne" : 15 } }
},
{
$group:
{
_id: "$student_name",
count: {$sum: 1},
sum1: {$sum: "$student_age"}
}
}
])
In others words, I want to fetch the count of students that aren't 15 years old and the summary of their age. The query works fine and I get two data items.
In my application, I want to do the query by Spring Data.
I wrote the following code:
Criteria where = Criteria.where("AGE").ne(15);
Aggregation aggregation = Aggregation.newAggregation(
Aggregation.match(where),
Aggregation.group().sum("student_age").as("totalAge"),
count().as("countOfStudentNot15YearsOld"));
When this code is run, the output query will be:
"aggregate" : "MyDocument", "pipeline" :
[ { "$match" { "AGE" : { "$ne" : 15 } } },
{ "$group" : { "_id" : null, "totalAge" : { "$sum" : "$student_age" } } },
{ "$count" : "countOfStudentNot15YearsOld" }],
"cursor" : { "batchSize" : 2147483647 }
Unfortunately, the result is only countOfStudentNot15YearsOld item.
I want to fetch the result like my native query.
If your're asking to return the grouping for both "15" and "not 15" as a result then you're looking for the $cond operator which will allow a "branching" based on conditional evaluation.
From the "shell" content you would use it like this:
db.getCollection('student').aggregate([
{ "$group": {
"_id": null,
"countFiteen": {
"$sum": {
"$cond": [{ "$eq": [ "$student_age", 15 ] }, 1, 0 ]
}
},
"countNotFifteen": {
"$sum": {
"$cond": [{ "$ne": [ "$student_age", 15 ] }, 1, 0 ]
}
},
"sumNotFifteen": {
"$sum": {
"$cond": [{ "$ne": [ "$student_age", 15 ] }, "$student_age", 0 ]
}
}
}}
])
So you use the $cond to perform a logical test, in this case whether the "student_age" in the current document being considered is 15 or not, then you can return a numerical value in response which is 1 here for "counting" or the actual field value when that is what you want to send to the accumulator instead. In short it's a "ternary" operator or if/then/else condition ( which in fact can be shown in the more expressive form with keys ) you can use to test a condition and decide what to return.
For the spring mongodb implementation you use ConditionalOperators.Cond to construct the same BSON expressions:
import org.springframework.data.mongodb.core.aggregation.*;
ConditionalOperators.Cond isFifteen = ConditionalOperators.when(new Criteria("student_age").is(15))
.then(1).otherwise(0);
ConditionalOperators.Cond notFifteen = ConditionalOperators.when(new Criteria("student_age").ne(15))
.then(1).otherwise(0);
ConditionalOperators.Cond sumNotFifteen = ConditionalOperators.when(new Criteria("student_age").ne(15))
.thenValueOf("student_age").otherwise(0);
GroupOperation groupStage = Aggregation.group()
.sum(isFifteen).as("countFifteen")
.sum(notFifteen).as("countNotFifteen")
.sum(sumNotFifteen).as("sumNotFifteen");
Aggregation aggregation = Aggregation.newAggregation(groupStage);
So basically you just extend off of that logic, using .then() for a "constant" value such as 1 for the "counts", and .thenValueOf() where you actually need the "value" of a field from the document, so basically equal to the "$student_age" as shown for the common shell notation.
Since ConditionalOperators.Cond shares the AggregationExpression interface, this can be used with .sum() in the form that accepts an AggregationExpression as opposed to a string. This is an improvement on past releases of spring mongo which would require you to perform a $project stage so there were actual document properties for the evaluated expression prior to performing a $group.
If all you want is to replicate the original query for spring mongodb, then your mistake was using the $count aggregation stage rather than appending to the group():
Criteria where = Criteria.where("AGE").ne(15);
Aggregation aggregation = Aggregation.newAggregation(
Aggregation.match(where),
Aggregation.group()
.sum("student_age").as("totalAge")
.count().as("countOfStudentNot15YearsOld")
);

DB script for changing the model of mongoDB collection [duplicate]

In MongoDB, is it possible to update the value of a field using the value from another field? The equivalent SQL would be something like:
UPDATE Person SET Name = FirstName + ' ' + LastName
And the MongoDB pseudo-code would be:
db.person.update( {}, { $set : { name : firstName + ' ' + lastName } );
The best way to do this is in version 4.2+ which allows using the aggregation pipeline in the update document and the updateOne, updateMany, or update(deprecated in most if not all languages drivers) collection methods.
MongoDB 4.2+
Version 4.2 also introduced the $set pipeline stage operator, which is an alias for $addFields. I will use $set here as it maps with what we are trying to achieve.
db.collection.<update method>(
{},
[
{"$set": {"name": { "$concat": ["$firstName", " ", "$lastName"]}}}
]
)
Note that square brackets in the second argument to the method specify an aggregation pipeline instead of a plain update document because using a simple document will not work correctly.
MongoDB 3.4+
In 3.4+, you can use $addFields and the $out aggregation pipeline operators.
db.collection.aggregate(
[
{ "$addFields": {
"name": { "$concat": [ "$firstName", " ", "$lastName" ] }
}},
{ "$out": <output collection name> }
]
)
Note that this does not update your collection but instead replaces the existing collection or creates a new one. Also, for update operations that require "typecasting", you will need client-side processing, and depending on the operation, you may need to use the find() method instead of the .aggreate() method.
MongoDB 3.2 and 3.0
The way we do this is by $projecting our documents and using the $concat string aggregation operator to return the concatenated string.
You then iterate the cursor and use the $set update operator to add the new field to your documents using bulk operations for maximum efficiency.
Aggregation query:
var cursor = db.collection.aggregate([
{ "$project": {
"name": { "$concat": [ "$firstName", " ", "$lastName" ] }
}}
])
MongoDB 3.2 or newer
You need to use the bulkWrite method.
var requests = [];
cursor.forEach(document => {
requests.push( {
'updateOne': {
'filter': { '_id': document._id },
'update': { '$set': { 'name': document.name } }
}
});
if (requests.length === 500) {
//Execute per 500 operations and re-init
db.collection.bulkWrite(requests);
requests = [];
}
});
if(requests.length > 0) {
db.collection.bulkWrite(requests);
}
MongoDB 2.6 and 3.0
From this version, you need to use the now deprecated Bulk API and its associated methods.
var bulk = db.collection.initializeUnorderedBulkOp();
var count = 0;
cursor.snapshot().forEach(function(document) {
bulk.find({ '_id': document._id }).updateOne( {
'$set': { 'name': document.name }
});
count++;
if(count%500 === 0) {
// Excecute per 500 operations and re-init
bulk.execute();
bulk = db.collection.initializeUnorderedBulkOp();
}
})
// clean up queues
if(count > 0) {
bulk.execute();
}
MongoDB 2.4
cursor["result"].forEach(function(document) {
db.collection.update(
{ "_id": document._id },
{ "$set": { "name": document.name } }
);
})
You should iterate through. For your specific case:
db.person.find().snapshot().forEach(
function (elem) {
db.person.update(
{
_id: elem._id
},
{
$set: {
name: elem.firstname + ' ' + elem.lastname
}
}
);
}
);
Apparently there is a way to do this efficiently since MongoDB 3.4, see styvane's answer.
Obsolete answer below
You cannot refer to the document itself in an update (yet). You'll need to iterate through the documents and update each document using a function. See this answer for an example, or this one for server-side eval().
For a database with high activity, you may run into issues where your updates affect actively changing records and for this reason I recommend using snapshot()
db.person.find().snapshot().forEach( function (hombre) {
hombre.name = hombre.firstName + ' ' + hombre.lastName;
db.person.save(hombre);
});
http://docs.mongodb.org/manual/reference/method/cursor.snapshot/
Starting Mongo 4.2, db.collection.update() can accept an aggregation pipeline, finally allowing the update/creation of a field based on another field:
// { firstName: "Hello", lastName: "World" }
db.collection.updateMany(
{},
[{ $set: { name: { $concat: [ "$firstName", " ", "$lastName" ] } } }]
)
// { "firstName" : "Hello", "lastName" : "World", "name" : "Hello World" }
The first part {} is the match query, filtering which documents to update (in our case all documents).
The second part [{ $set: { name: { ... } }] is the update aggregation pipeline (note the squared brackets signifying the use of an aggregation pipeline). $set is a new aggregation operator and an alias of $addFields.
Regarding this answer, the snapshot function is deprecated in version 3.6, according to this update. So, on version 3.6 and above, it is possible to perform the operation this way:
db.person.find().forEach(
function (elem) {
db.person.update(
{
_id: elem._id
},
{
$set: {
name: elem.firstname + ' ' + elem.lastname
}
}
);
}
);
I tried the above solution but I found it unsuitable for large amounts of data. I then discovered the stream feature:
MongoClient.connect("...", function(err, db){
var c = db.collection('yourCollection');
var s = c.find({/* your query */}).stream();
s.on('data', function(doc){
c.update({_id: doc._id}, {$set: {name : doc.firstName + ' ' + doc.lastName}}, function(err, result) { /* result == true? */} }
});
s.on('end', function(){
// stream can end before all your updates do if you have a lot
})
})
update() method takes aggregation pipeline as parameter like
db.collection_name.update(
{
// Query
},
[
// Aggregation pipeline
{ "$set": { "id": "$_id" } }
],
{
// Options
"multi": true // false when a single doc has to be updated
}
)
The field can be set or unset with existing values using the aggregation pipeline.
Note: use $ with field name to specify the field which has to be read.
Here's what we came up with for copying one field to another for ~150_000 records. It took about 6 minutes, but is still significantly less resource intensive than it would have been to instantiate and iterate over the same number of ruby objects.
js_query = %({
$or : [
{
'settings.mobile_notifications' : { $exists : false },
'settings.mobile_admin_notifications' : { $exists : false }
}
]
})
js_for_each = %(function(user) {
if (!user.settings.hasOwnProperty('mobile_notifications')) {
user.settings.mobile_notifications = user.settings.email_notifications;
}
if (!user.settings.hasOwnProperty('mobile_admin_notifications')) {
user.settings.mobile_admin_notifications = user.settings.email_admin_notifications;
}
db.users.save(user);
})
js = "db.users.find(#{js_query}).forEach(#{js_for_each});"
Mongoid::Sessions.default.command('$eval' => js)
With MongoDB version 4.2+, updates are more flexible as it allows the use of aggregation pipeline in its update, updateOne and updateMany. You can now transform your documents using the aggregation operators then update without the need to explicity state the $set command (instead we use $replaceRoot: {newRoot: "$$ROOT"})
Here we use the aggregate query to extract the timestamp from MongoDB's ObjectID "_id" field and update the documents (I am not an expert in SQL but I think SQL does not provide any auto generated ObjectID that has timestamp to it, you would have to automatically create that date)
var collection = "person"
agg_query = [
{
"$addFields" : {
"_last_updated" : {
"$toDate" : "$_id"
}
}
},
{
$replaceRoot: {
newRoot: "$$ROOT"
}
}
]
db.getCollection(collection).updateMany({}, agg_query, {upsert: true})
(I would have posted this as a comment, but couldn't)
For anyone who lands here trying to update one field using another in the document with the c# driver...
I could not figure out how to use any of the UpdateXXX methods and their associated overloads since they take an UpdateDefinition as an argument.
// we want to set Prop1 to Prop2
class Foo { public string Prop1 { get; set; } public string Prop2 { get; set;} }
void Test()
{
var update = new UpdateDefinitionBuilder<Foo>();
update.Set(x => x.Prop1, <new value; no way to get a hold of the object that I can find>)
}
As a workaround, I found that you can use the RunCommand method on an IMongoDatabase (https://docs.mongodb.com/manual/reference/command/update/#dbcmd.update).
var command = new BsonDocument
{
{ "update", "CollectionToUpdate" },
{ "updates", new BsonArray
{
new BsonDocument
{
// Any filter; here the check is if Prop1 does not exist
{ "q", new BsonDocument{ ["Prop1"] = new BsonDocument("$exists", false) }},
// set it to the value of Prop2
{ "u", new BsonArray { new BsonDocument { ["$set"] = new BsonDocument("Prop1", "$Prop2") }}},
{ "multi", true }
}
}
}
};
database.RunCommand<BsonDocument>(command);
MongoDB 4.2+ Golang
result, err := collection.UpdateMany(ctx, bson.M{},
mongo.Pipeline{
bson.D{{"$set",
bson.M{"name": bson.M{"$concat": []string{"$lastName", " ", "$firstName"}}}
}},
)

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