JSONata newbie checking in. I have reviewed all the questions in this forum and cannot find the answer so am asking here.
Given this source...
{
"Price": 34.45,
"Product Name": "Bowler Hat",
"ProductID": 858383,
"Quantity": 2,
"SKU": "0406654608"
}
I would like to reduce it to...
{
"Product Name": "Bowler Hat",
"ProductID": 858383,
"SKU": "0406654608"
}
...using the Transform operator to delete Price and Quantity. I've tried various permutations of this...
$ ~> |*|{}, ['Price', 'Quantity']|
..but am not getting the result I am looking for. Here is an Exerciser link.
Thanks in advance for any assistance.
Just a small modification needed - the 'matching' clause needs to match the object that you wish to modify, in your case it is the context item '$'. The wildcard '*' is going to return the sequence of values in that object rather than the object itself. So your expression should be:
$ ~> |$|{}, ['Price', 'Quantity']|
See https://try.jsonata.org/qUwOtT-pt
Related
I have a product nested document containing a list of prices associated to different wholesalers.
Here is a document example :
{
"sku": "065879",
"name": "My product",
"price": [
{
"wholesaler": "1",
"location": "drm3btev3",
"price": "12.34"
},
{
"wholesaler": "2",
"location": "gbsuv7ztq",
"price": "45.67"
},
]
}
Given a customer's geo point, what is the correct query to get a list of documents sorted by price, using only the closest price for each document ?
Thanks by advance !
It's not a real answer but the global approach is to use a nested sort. Nested sort will allow you to filter the nested document on which you want to apply your sorting.
Then you should in the nested sort filter add a script query that will determine the closest wholesaler. The problem is that you cant work with geohash in painless. But if you convert your geohash to geopoint data type in, you will be able to use script distance features ( example here )
Then you could compute the minimal distance by iterating on all nested document and only match the one with the minimal distance.
But I have no idea of the performance impact and detailed implementation.
Good luck !
Is it possible to score my searches according to the number of matches when using operator "or"?
Currently query looks like this:
"query": {
"function_score": {
"query": {
"match": {
"tags.eng": {
"query": "apples banana juice",
"operator": "or",
"fuzziness": "AUTO"
}
}
},
"script_score": {
"script": # TODO
},
"boost_mode": "replace"
}
}
I don't want to use "and" operator, since I want documents containing "apple juice" to be found, as well as documents containing only "juice", etc. However a document containing the three words should score more than documents containing two words or a single word, and so on.
I found a possible solution here https://github.com/elastic/elasticsearch/issues/13806
which uses bool queries. However I don't know how to access the tokens (in this example: apples, banana, juice) generated by the analyzer.
Any help?
Based on the discussions above I came up with the following solution, which is a bit different that I imagined when I asked the question, but works for my case.
First of all I defined a new similarity:
"settings": {
"similarity": {
"boost_similarity": {
"type": "scripted",
"script": {
"source": "return 1;"
}
}
}
...
}
Then I had the following problem:
a query for "apple banana juice" had the same score for a doc with tags ["apple juice", "apple"] and another doc with tag ["banana", "apple juice"]. Although I would like to score the second one higher.
From the this other discussion I found out that this issue was caused because I had a nested field. And I created a usual text field to address it.
But I also was wanted to distinguish between a doc with tags ["apple", "banana", "juice"] and another doc with tag ["apple banana juice"] (all three words in the same tag). The final solution was therefore to keep both fields (a nested and a text field) for my tags.
Finally the query consists of bool query with two should clauses: the first should clause is performed on the text field and uses an "or" operator. The second should clause is performed on the nested field and uses and "and operator"
Despite I found a solution for this specific issue, I still face a few other problems when using ES to search for tagged documents. The examples in the documentation seem to work very well when searching for full texts. But does someone know where I can find something more specific to tagged documents?
I am using MongoDB and Spring for an application
I am using a text index on my collection.
I found two methods:
matchingany
matchingphrase
But I am unable to understand the difference.
Please help me to understand them.
If you want a match on multiple words forming a phrase then use matchingPhrase, if you want a match on at least one word in a ist of words then use matchingAny.
For example, given these documents (and assuming the title attribute is text-indexed):
{ "id": 1, "title": "The days of the week"}
{ "id": 2, "title": "Once a week"}
{ "id": 3, "title": "Once a month"}
matchingAny("Once") will match the documents with id=2 and id=3
matchingAny("month", "foo' , "bar") will match the document with id=3
matchingPhrase("The days of the week") will match the document with id=1
More details in the docs.
I have any Freebase mid such as: /m/0mgcr, which is The Offspring.
Whats the best way to use MQL to find related artists?
Or if I have a song mid such as: /m/0l_f7f, which is Original Prankster by The Offspring.
Whats the best way to use MQL to find related songs?
So, the revised question is, given a musical artist, find all other musical artists who share all of the same genres assigned to the first artist.
MQL doesn't have any operators which can work across parts of the query tree, so this can't be done in a single query, but given that you're likely doing this from a programming language, it be done pretty simply in two steps.
First, we'll get all genres for our subject artist, sorted by the number of artists that they contain using this query (although the last part isn't strictly necessary):
[{
"id": "/m/0mgcr",
"name": null,
"/music/artist/genre": [{
"name": null,
"id": null,
"artists": {
"return": "count"
},
"sort": "artists.count"
}]
}]
Then, using the genre with the smallest number of artists for maximum selectivity, we'll add in the other genres to make it even more specific. Here's a version of the query with the artists that match on the three most specific genres (the base genre plus two more):
[{
"id": "/m/0mgcr",
"name": null,
"/music/artist/genre": [{
"name": null,
"id": null,
"artists": {
"return": "count"
},
"sort": "artists.count",
"limit": 1,
"a:artists": [{
"name": null,
"id": null,
"a:genre": {
"id": "/en/ska_punk"
},
"b:genre": {
"id": "/en/melodic_hardcore"
}
}]
}]
}]
Which gives us: Authority Zero, Millencolin, Michael John Burkett, NOFX, Bigwig, Huelga de Hambre, Freygolo, The Vandals
The things to note about this query are that, this fragment:
"sort": "artists.count",
"limit": 1,
limits our initial genre selection to the single genre with the fewest artists (ie Skate Punk), while the prefix notation:
"a:genre": {"id": "/en/ska_punk"},
"b:genre": {"id": "/en/melodic_hardcore"}
is to get around the JSON limitation on not having more than one key with the same name. The prefixes are ignored and just need to be unique (this is the same reason for the a:artists elsewhere in the query.
So, having worked through that whole little exercise, I'll close by saying that there are probably better ways of doing this. Instead of an absolute match, you may get better results with a scoring function that looks at % overlap for the most specific genres or some other metric. Things like common band members, collaborations, contemporaneous recording history, etc, etc, could also be factored into your scoring. Of course this is all beyond the capabilities of raw MQL and you'd probably want to load the Freebase data for the music domain (or some subset) into a graph database to run these scoring algorithms.
In point of fact, both last.fm and Google think a better list would include bands like Sum 41, blink-182, Bad Religion, Green Day, etc.
I am using Codeigniter and Alex Bilbie's MongoDB library.
In my API that I am developing users can upload images and other users can comment on them.
I have chosen to include the comments as sub documents to the images.
Each comment contains:
Fullname (of author)
Comment
Created_at
So in other words. The users full name is "hard coded" into each comment so if they
later decides to change their names I have a problem.
I read that I can use atomic updates to update all occurrences of the name (like in comments) but how can I do this using Alex´s library? Can I update all places where the name is wrong?
UPDATE
This is how the image document looks like with the comments.
I think that it is pretty strange that MongoDB encourage the use of subdocuments but then does not include a way to update multiple items in an array.
{
"_id": ObjectId("4e9ead773dc793dc01020000"),
"description": "An image",
"category": "accident",
"comments": [
{
"id": ObjectId("4e96bd063dc7937202000000"),
"fullname": "James Bond",
"comment": "This is a comment.",
"created_at": "2011-10-19 13:02:40"
}
],
"created_at": "2011-10-19 12:59:03"
}
Thankful for all help!
I am not familiar with codeignitor, but mb mongodb shell syntax will help you:
db.comments.update( {"Fullname":"Andrew Orsich"},
{ $set : { Fullname: "New name"} }, false, true )
Last true flag indicate that you want update multiple documents. So it is possible to update all comments in one update operation.
BTW: denormalazing (not 'hard coding') data in mongodb and nosql in general is usual operation. Also operation that require update a lot of documents usually work async. But it is up to you.
Update:
db.comments.update( {"comments.Fullname":"Andrew Orsich"},
{ $set : { comments.$.Fullname: "New name"} }, false, true )
But, above query will update full name in first comment on nested array. If you need to affect changes to more than one array element you will need to use multiple update statements.