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how can I have transformed my json
{
"clients": [
{
"id" : "qwerty",
"accounts" : [{"number" : "6666"}, {"number" : "7777"}]
},
{
"id" : "zxcvb",
"accounts" : [{"number" : "1111"}, {"number" : "2222"}]
}
]
}
into following type of json? using JQ
{
"items": [
{
"id" : "qwerty",
"number" : "6666"
},{
"id" : "qwerty",
"number" : "7777"
},{
"id" : "zxcvb",
"number" : "1111"
},{
"id" : "zxcvb",
"number" : "2222"
}]
}
What kind of tools from JQ can help me? I can't choose any possible way to do it
Something like this should do the trick:
{items: [.clients[] | {id} + .accounts[]]}
Online demo
I have the JSON that you can see below and I want to sum the values of the two objects, but when I make an aggregation it returns me 0.Here you can see the query that I use; really the first line I only use it to be sure that the path works, and it does. On the other hand,when I use this path in the aggregation query it gives me the "ID" and the "COUNT" with right values,but the "SUM" is always 0 when it must be 3600.Any idea?
db.getCollection('TEST').find({"prices.year.months.day.csv.price.valPrice":1800})
db.TEST.aggregate([
{ $match: {"location.cp":"20830"}},
{$group:{_id:"20830",total:{$sum:"$prices.year.months.day.csv.price.valPrice"}, count: { $sum: 1 }
}}])
And this is the JSON:
{
"_id" : "20830:cas:S:3639",
"lodgtype" : "Casa",
"lodg" : "Motrico: country holiday home - San sebastian",
"webid" : "6107939",
"location" : {
"thcod" : "20",
"cp" : "20830",
"th" : "Gipuzkoa",
"geometry" : {
"type" : "Point",
"coordinates" : [
43.31706238,
-2.40293598
]
}
},
"prices" : {
"year" : [
{
"valYear" : "2018",
"months" : [
{
"valMonth" : "02",
"day" : [
{
"valDay" : "13",
"csv" : [
{
"valCsv" : "20180205210908_223",
"price" : [
{
"valPrice" : 1800.0
}
]
}
]
}
]
}
]
}
]
},
"reg" : {
"created" : "20180213",
"updated" : "20180213",
"viewed" : "20180213"
}
},{
"_id" : "TEST20830:cas:S:3639",
"lodgtype" : "Casa",
"lodg" : "TESTMotrico: country holiday home - San sebastian",
"webid" : "6107930",
"location" : {
"thcod" : "20",
"cp" : "20830",
"th" : "Gipuzkoa",
"geometry" : {
"type" : "Point",
"coordinates" : [
43.31706238,
-2.40293598
]
}
},
"prices" : {
"year" : [
{
"valYear" : "2018",
"months" : [
{
"valMonth" : "02",
"day" : [
{
"valDay" : "13",
"csv" : [
{
"valCsv" : "20180205210908_223",
"price" : [
{
"valPrice" : 1800.0
}
]
}
]
}
]
}
]
}
]
},
"reg" : {
"created" : "20180213",
"updated" : "20180213",
"viewed" : "20180213"
}
}
Since you've deeply nested array you've to unwind to flatten to a document structure. To count the number of matches you've to use extra group after $match with $push with $$ROOT to keep the matching data.
db.TEST.aggregate([
{"$match":{"location.cp":"20830"}},
{"$group":{
"_id":"20830",
"data":{"$push":"$$ROOT"},
"count":{"$sum":1}
}},
{"$unwind":"$data.prices.year"},
{"$unwind":"$data.prices.year"},
{"$unwind":"$data.prices.year.months"},
{"$unwind":"$data.prices.year.months.day"},
{"$unwind":"$data.prices.year.months.day.csv"},
{"$unwind":"$data.prices.year.months.day.csv.price"},
{"$group":{
"_id":"20830",
"total":{"$sum":"$prices.year.months.day.csv.price.valPrice"},
"count":{"$first":"$count"}
}}
])
I am using Logstash 2.4 to read JSON messages from a Kafka topic and send them to an Elasticsearch Index.
The JSON format is as below --
{
"schema":
{
"type": "struct",
"fields": [
{
"type":"string",
"optional":false,
"field":"reloadID"
},
{
"type":"string",
"optional":false,
"field":"externalAccountID"
},
{
"type":"int64",
"optional":false,
"name":"org.apache.kafka.connect.data.Timestamp",
"version":1,
"field":"reloadDate"
},
{
"type":"int32",
"optional":false,
"field":"reloadAmount"
},
{
"type":"string",
"optional":true,
"field":"reloadChannel"
}
],
"optional":false,
"name":"reload"
},
"payload":
{
"reloadID":"328424295",
"externalAccountID":"9831200013",
"reloadDate":1446242463000,
"reloadAmount":240,
"reloadChannel":"C1"
}
}
Without any filter in my config file, the target documents from the ES index look like below --
{
"_index" : "kafka_reloads",
"_type" : "logs",
"_id" : "AVfcyTU4SyCFNFP2z5-l",
"_score" : 1.0,
"_source" : {
"schema" : {
"type" : "struct",
"fields" : [ {
"type" : "string",
"optional" : false,
"field" : "reloadID"
}, {
"type" : "string",
"optional" : false,
"field" : "externalAccountID"
}, {
"type" : "int64",
"optional" : false,
"name" : "org.apache.kafka.connect.data.Timestamp",
"version" : 1,
"field" : "reloadDate"
}, {
"type" : "int32",
"optional" : false,
"field" : "reloadAmount"
}, {
"type" : "string",
"optional" : true,
"field" : "reloadChannel"
} ],
"optional" : false,
"name" : "reload"
},
"payload" : {
"reloadID" : "155559213",
"externalAccountID" : "9831200014",
"reloadDate" : 1449529746000,
"reloadAmount" : 140,
"reloadChannel" : "C1"
},
"#version" : "1",
"#timestamp" : "2016-10-19T11:56:09.973Z",
}
}
But, I want only the value part of the "payload" field to move to my ES index as the target JSON body. So I tried to use the 'mutate' filter in the config file as below --
input {
kafka {
zk_connect => "zksrv-1:2181,zksrv-2:2181,zksrv-4:2181"
group_id => "logstash"
topic_id => "reload"
consumer_threads => 3
}
}
filter {
mutate {
remove_field => [ "schema","#version","#timestamp" ]
}
}
output {
elasticsearch {
hosts => ["datanode-6:9200","datanode-2:9200"]
index => "kafka_reloads"
}
}
With this filter, the ES documents now look like below --
{
"_index" : "kafka_reloads",
"_type" : "logs",
"_id" : "AVfch0yhSyCFNFP2z59f",
"_score" : 1.0,
"_source" : {
"payload" : {
"reloadID" : "850846698",
"externalAccountID" : "9831200013",
"reloadDate" : 1449356706000,
"reloadAmount" : 30,
"reloadChannel" : "C1"
}
}
}
But actually It should be like below --
{
"_index" : "kafka_reloads",
"_type" : "logs",
"_id" : "AVfch0yhSyCFNFP2z59f",
"_score" : 1.0,
"_source" : {
"reloadID" : "850846698",
"externalAccountID" : "9831200013",
"reloadDate" : 1449356706000,
"reloadAmount" : 30,
"reloadChannel" : "C1"
}
}
Is there a way to do this? Can anyone help me on this?
I also tried the below filter --
filter {
json {
source => "payload"
}
}
But that is giving me errors like --
Error parsing json {:source=>"payload", :raw=>{"reloadID"=>"572584696", "externalAccountID"=>"9831200011", "reloadDate"=>1449093851000, "reloadAmount"=>180, "reloadChannel"=>"C1"}, :exception=>java.lang.ClassCastException: org.jruby.RubyHash cannot be cast to org.jruby.RubyIO, :level=>:warn}
Any help will be much appreciated.
Thanks
Gautam Ghosh
You can achieve what you want using the following ruby filter:
ruby {
code => "
event.to_hash.delete_if {|k, v| k != 'payload'}
event.to_hash.update(event['payload'].to_hash)
event.to_hash.delete_if {|k, v| k == 'payload'}
"
}
What it does is:
remove all fields but the payload one
copy all payload inner fields at the root level
delete the payload field itself
You'll end up with what you need.
It's been a while but here there is a valid workaround, hope it would be useful.
json_encode {
source => "json"
target => "json_string"
}
json {
source => "json_string"
}
I'm trying to find objects using the built it queries and It just doesn't work..
My JSON file is something like this:
{ "Text1":
{
"id":"2"
},
"Text2":
{
"id":"2,3"
},
"Text3":
{
"id":"1"
}
}
And I write this db.myCollection.find({"id":2})
And it doesn't find anything.
When I write db.myCollection.find() it shows all the data as it should.
Anyone knows how to do it correctly?
Its hard to change the data-structure but as you want just your matching sub-document and you don't know where is your target sub-document (for example the query should be on Text1 or Text2 , ...) there is a good data structure for this:
{
"_id" : ObjectId("548dd9261a01c68fab8d67d7"),
"pair" : [
{
"id" : "2",
"key" : "Text1"
},
{
"id" : [
"2",
"3"
],
"key" : "Text2"
},
{
"id" : "1",
"key" : "Text3"
}
]
}
and your query is:
db.myCollection.findOne({'pair.id' : "2"} , {'pair.$':1, _id : -1}).pair // there is better ways (such as aggregation instead of above query)
as result you will have:
{
"0" : {
"id" : "2",
"key" : "Text1"
}
}
Update 1 (newbie way)
If you want all the document not just one use this
var result = [];
db.myCollection.find({'pair.id' : "2"} , {'pair.$':1, _id : -1}).forEach(function(item)
{
result.push(item.pair);
});
// the output will be in result
Update 2
Use this query to get all sub-documents
db.myCollection.aggregate
(
{ $unwind: '$pair' },
{ $match : {'pair.id' : "2"} }
).result
it produce output as
{
"0" : {
"_id" : ObjectId("548deb511a01c68fab8d67db"),
"pair" : {
"id" : "2",
"key" : "Text1"
}
},
"1" : {
"_id" : ObjectId("548deb511a01c68fab8d67db"),
"pair" : {
"id" : [
"2",
"3"
],
"key" : "Text2"
}
}
}
Since your are query specify a field in a subdocument this is what will work. see .find() documentation.
db.myCollection.find({"Text1.id" : "2"}, {"Text1.id": true})
{ "_id" : ObjectId("548dd798e2fa652e675af11d"), "Text1" : { "id" : "2" } }
If the query is on "Text1" or "Text2" the best thing to do here as mention in the accepted answer is changing you document structure. This can be easily done using the "Bulk" API.
var bulk = db.mycollection.initializeOrderedBulkOp(),
count = 0;
db.mycollection.find().forEach(function(doc) {
var pair = [];
for(var key in doc) {
if(key !== "_id") {
var id = doc[key]["id"].split(/[, ]/);
pair.push({"key": key, "id": id});
}
}
bulk.find({"_id": doc._id}).replaceOne({ "pair": pair });
count++; if (count % 300 == 0){
// Execute per 300 operations and re-Init
bulk.execute();
bulk = db.mycollection.initializeOrderedBulkOp();
}
})
// Clean up queues
if (count % 300 != 0 )
bulk.execute();
Your document now look like this:
{
"_id" : ObjectId("55edddc6602d0b4fd53a48d8"),
"pair" : [
{
"key" : "Text1",
"id" : [
"2"
]
},
{
"key" : "Text2",
"id" : [
"2",
"3"
]
},
{
"key" : "Text3",
"id" : [
"1"
]
}
]
}
Running the following query:
db.mycollection.aggregate([
{ "$project": {
"pair": {
"$setDifference": [
{ "$map": {
"input": "$pair",
"as": "pr",
"in": {
"$cond": [
{ "$setIsSubset": [ ["2"], "$$pr.id" ]},
"$$pr",
false
]
}
}},
[false]
]
}
}}
])
returns:
{
"_id" : ObjectId("55edddc6602d0b4fd53a48d8"),
"pair" : [
{
"key" : "Text1",
"id" : [
"2"
]
},
{
"key" : "Text2",
"id" : [
"2",
"3"
]
}
]
}
I have the following sample data in MongoDB:
{
"_id" : ObjectId("54833e93ade1a1521a2a2fe8"),
"fname" : "yumi",
"mname" : "sakura",
"lname" : "kirisaki",
"consultations" : [
{
"medications" : [
"paracetamol",
"ibuprofen",
"carbocisteine"
],
"diagnosis" : [
"sore throat",
"fever",
"cough"
],
"date" : ISODate("2014-12-01T16:00:00Z")
},
{
"medications" : [
"paracetamol",
"carbocisteine",
"afrin"
],
"diagnosis" : [
"cough",
"colds",
"fever"
],
"date" : ISODate("2014-12-11T16:00:00Z")
}
]
}
{
"_id" : ObjectId("54833e93ade1a1521a2a2fe9"),
"fname" : "james",
"mname" : "legaspi",
"lname" : "reyes",
"consultations" : [
{
"medications" : [
"zanamivir",
"ibuprofen",
"paracetamol"
],
"diagnosis" : [
"influenza",
"body aches",
"headache"
],
"date" : ISODate("2014-10-22T16:00:00Z")
},
{
"medications" : [
"carbocisteine",
"albuterol",
"ibuprofen"
],
"diagnosis" : [
"asthma",
"cough",
"headache"
],
"date" : ISODate("2014-11-13T16:00:00Z")
}
]
}
I am trying to query patients with zanamivir AND ibuprofen AND cough:
db.patient.find({
$and:
[
{"consultations.medications":["zanamivir", "ibuprofen"]},
{"consultations.diagnosis":"cough"}
]
}).pretty()
So, in the short sample data, I was hoping james would be returned since he is the only one with zanamivir medication.
Nothing is happening when I enter the above query in cmd. It just goes to the next line (no syntax errors, etc.)
How must I go about the query?
You need the use the $all operator.
db.patient.find({
"consultations.medications": { "$all" : [ "zanamivir", "ibuprofen" ]},
"consultations.diagnosis": "cough"
})
Pretty simple, it's just your first part of the query.
db.patient.find({
$and:[
{"consultations.medications":["zanamivir", "ibuprofen"]},
{"consultations.diagnosis":"cough"}]})
Asking Mongodb to find consultations.medications against ["zanamivir", "ibuprofen"] is asking it to find someone whose medications are equal to ['zanamivir', 'ibuprofen'].
If you want to find people who have had zanamivir and ibuprofen medicated you need to tweak the query to this:
db.patient.find({
$and:[
{"consultations.medications":"zanamivir"},
{"consultations.medications":"ibuprofen"},
{"consultations.diagnosis":"cough"}]})
Enjoy!