As I create entities in an Orion server, I can search by ID, as flat or using regular expressions:
http://<localhost>:1026/v1/queryContext
Content:
{
"entities": [
{
"type": "Sensor",
"isPattern": "true",
"id": "sensor_1.*"
}
],
"attributes": ["temperature","humidity"]
}
In the above example I'd get all objects of type "Sensor" whose ID starts with "sensor_1", and their attributes "temperature" and "humidity". I wonder if there is any way that would allow me to search by specific attribute value, for example to get those sensors whose humidity is over "60.2", or this selection must be done over the retrieved data queried by ID.
Not in the current Orion version (0.19.0) but it will be possible in the future. Have a look to the attribute::<name> filter with the = operator in this document.
Related
Using the FIWARE PointOfInterest data model I would like to filter by POI category which is an array. For instance
http://130.206.118.244:1027/v2/entities?type=PointOfInterest&options=keyValues&attrs=name,category&limit=100&q=category=="311"
having as entity instances something like
{
"id": "Museum-f85a8c66d617c23d33847f8110341a29",
"type": "PointOfInterest",
"name": "The Giant Squid Centre",
"category":
[
"311"
]
},
{
"id": "Museum-611f228f42c7fbfa4bd58bad94455055",
"type": "PointOfInterest",
"name": "Museo Extremeño e Iberoamericano de Arte Contemporáneo",
"category":
[
"311"
]
},
Looking to the NGSIv2 specification it seems that works in the way you mention:
Single element, e.g. temperature==40. For an entity to match, it must contain the target property (temperature) and the target property value must be the query value (40) (or include the value, in case the target property value is an array).
I mean, in particular the part that says:
...or include the value, in case the target property value is an array.
I'm very new to MongoDB, i tell you sorry for this question but i have a problem to understand how to create a document that can contain a value with different "type:
My document can contain data like this:
// Example ONE
{
"customer" : "aCustomer",
"type": "TYPE_ONE",
"value": "Value here"
}
// Example TWO
{
"customer": "aCustomer",
"type": "TYPE_TWO",
"value": {
"parameter1": "value for parameter one",
"parameter2": "value for parameter two"
}
}
// Example THREE
{
"customer": "aCustomer",
"type": "TYPE_THREE",
"value": {
"anotherParameter": "another value",
{
"someParameter": "value for some parameter",
...
}
}
}
Customer field will be even present, the type can be different (TYPE_ONE, TYPE_TWO and so on), based on the TYPE the value can be a string, an object, an array etc.
Looking this example, i should create three kind of collections (one for type) or the same collection (for example, a collection named "measurements") can contain differend kind of value on the field "value" ?
Trying some insert in my DB instance i dont get any error (i'm able to insert object, string and array on property value), but i would like to know if is the correct way...
I come from RDBMS, i'm a bit confused right now.. thanks a lot for your support.
You can find the answer here https://docs.mongodb.com/drivers/use-cases/product-catalog
MongoDB's dynamic schema means that each need not conform to the same schema.
I'm trying to figure out how to search a collection for every instance of a keyword. For example, I'd like to search a collection for every instance of the word "authenticated". Below is what one of the documents looks like in the collection that contains the keyword:
{
"_id": {
"$oid": "55945938d28f9f3809002afc"
},
"TAGS": ".source.s_net",
"SOURCEIP": "10.10.0.5",
"SEQNUM": "11004",
"PROGRAM": "Core",
"PRIORITY": "info",
"MESSAGE": "<pppoe-jjcutter>: authenticated",
"LEGACY_MSGHDR": "Core ",
"HOST_FROM": "10.10.0.5",
"HOST": "10.10.0.5",
"FACILITY": "syslog",
"DATE": "Jul 1 14:18:48"
}
Check my github https://github.com/parthaindia/CustomMongo,
getByCondition(String tableName, Map condition) ,call this method where you tableName is your collection name ,Map is the key-value.In your case map would be
Map condition =new HashMap();
condition.put("MESSAGE",": authenticated");//or whatever object
You would receive an Array List in Json format.Use Type Token to convert into Array List.
You can use a wildcard text index.
Test data
db.people.insert({name: "Martin", remarks: "great architector"})
db.people.insert({name: "John", remarks: "awesome SO user, great programmer"})
db.people.insert({name: "Tony The Great", remarks: "inventor"})
Wildcard Index
db.people.createIndex({"$**" : "text"})
Query
db.people.find({$text: {$search: "great"}})
You will get all 3 records.
MongoDB documentation on wildcard indexes
Use $regex in find as below :
db.messages.find({"MESSAGE":{"$regex":"(\\s|^)authenticated(\\s|$)"}})
Or if you want to find out exact match of authenticated values then used below query :
db.messages.find({"MESSAGE":"authenticated"})
I want to retrive record which are matching to booking's client id & want to show it to client. I am doing the following:
$mongoDb = $mongoDb->selectCollection('booking');
$bookingInfo = $mongoDb->find(array("client.id" => $_SESSION['client_id']));
My mongo database record looks like this:
"paymentDue": "",
"client": {
"contacts": [
{
"name": "loy furison",
"email": "loy#hotmail.com"
}
],
"id": "5492abba64363df013000029",
"name": "Birdfire"
},
want to fire the query with key value as client.id in find function. But this query doesnt work..whats the issue
I got a little logic that is different by key name only. If i find it with client.name then i shows me records & there i need to insert these in json object & then through foreach loop each record if i retrive & compare then it works...got it but the expected doesnt work why?????...didnt get:-!
I have different types of data that would be difficult to model and scale with a relational database (e.g., a product type)
I'm interested in using Mongodb to solve this problem.
I am referencing the documentation at mongodb's website:
http://docs.mongodb.org/manual/tutorial/model-referenced-one-to-many-relationships-between-documents/
For the data type that I am storing, I need to also maintain a relational list of id's where this particular product is available (e.g., store location id's).
In their example regarding "one-to-many relationships with embedded documents", they have the following:
{
name: "O'Reilly Media",
founded: 1980,
location: "CA",
books: [12346789, 234567890, ...]
}
I am currently importing the data with a spreadsheet, and want to use a batchInsert.
To avoid duplicates, I assume that:
1) I need to do an ensure index on the ID, and ignore errors on the insert?
2) Do I then need to loop through all the ID's to insert a new related ID to the books?
Your question could possibly be defined a little better, but let's consider the case that you have rows in a spreadsheet or other source that are all de-normalized in some way. So in a JSON representation the rows would be something like this:
{
"publisher": "O'Reilly Media",
"founded": 1980,
"location": "CA",
"book": 12346789
},
{
"publisher": "O'Reilly Media",
"founded": 1980,
"location": "CA",
"book": 234567890
}
So in order to get those sort of row results into the structure you wanted, one way to do this would be using the "upsert" functionality of the .update() method:
So assuming you have some way of looping the input values and they are identified with some structure then an analog to this would be something like:
books.forEach(function(book) {
db.publishers.update(
{
"name": book.publisher
},
{
"$setOnInsert": {
"founded": book.founded,
"location": book.location,
},
"$addToSet": { "books": book.book }
},
{ "upsert": true }
);
})
This essentially simplified the code so that MongoDB is doing all of the data collection work for you. So where the "name" of the publisher is considered to be unique, what the statement does is first search for a document in the collection that matches the query condition given, as the "name".
In the case where that document is not found, then a new document is inserted. So either the database or driver will take care of creating the new _id value for this document and your "condition" is also automatically inserted to the new document since it was an implied value that should exist.
The usage of the $setOnInsert operator is to say that those fields will only be set when a new document is created. The final part uses $addToSet in order to "push" the book values that have not already been found into the "books" array (or set).
The reason for the separation is for when a document is actually found to exist with the specified "publisher" name. In this case, all of the fields under the $setOnInsert will be ignored as they should already be in the document. So only the $addToSet operation is processed and sent to the server in order to add the new entry to the "books" array (set) and where it does not already exist.
So that would be simplified logic compared to aggregating the new records in code before sending a new insert operation. However it is not very "batch" like as you are still performing some operation to the server for each row.
This is fixed in MongoDB version 2.6 and above as there is now the ability to do "batch" updates. So with a similar analog:
var batch = [];
books.forEach(function(book) {
batch.push({
"q": { "name": book.publisher },
"u": {
"$setOnInsert": {
"founded": book.founded,
"location": book.location,
},
"$addToSet": { "books": book.book }
},
"upsert": true
});
if ( ( batch.length % 500 ) == 0 ) {
db.runCommand( "update", "updates": batch );
batch = [];
}
});
db.runCommand( "update", "updates": batch );
So what is doing in setting up all of the constructed update statements into a single call to the server with a sensible size of operations sent in the batch, in this case once every 500 items processed. The actual limit is the BSON document maximum of 16MB so this can be altered appropriate to your data.
If your MongoDB version is lower than 2.6 then you either use the first form or do something similar to the second form using the existing batch insert functionality. But if you choose to insert then you need to do all the pre-aggregation work within your code.
All of the methods are of course supported with the PHP driver, so it is just a matter of adapting this to your actual code and which course you want to take.