F# - Compare 2 JsonValue' - json

I have 2 Json values that are similar, but there are some differences.
Json1:
{
"id": "1",
"people" : [
{
"Id" : 1421,
"Name" : "Jackson",
"Age" : 21,
"Status" : "Available"
},
{
"Id" : 5916,
"Name" : "Steven",
"Age" : 22,
"Status" : "Available"
}
],
"totalRecords" : 2
}
Json2:
{
"id": "1",
"people" : [
{
"Id" : 1421,
"Name" : "Jackson",
"Age" : 21,
"Status" : "Available"
},
{
"Id" : 5916,
"Name" : "Steven",
"Age" : 22,
"Status" : "Unavailable"
},
{
"Id" : 1337,
"Name" : "Alice",
"Age" : 19,
"Status" : "Available"
}
],
"totalRecords" : 3
}
I'd like to know if there's a way to compare the two Jsonvalues. At the moment I de-serialize the data into a type and then use the Id's and the status' to see if anythings changed. I then pick out the parts that are different (In the example it'd be Steven and Alice) and add them to a sequence for later.
I'd like to reverse a few of the steps. I'd like too compare the json, find the differences, deserialize them and then add them to the sequence, or add them to the sequence then de-serialize the whole sequence. Either way, same result.
Any ideas?

Related

Jmeter: Extracting JSON response with special/spaces characters

Hello can someone help me extract the value of user parameter which is "testuser1"
I tried to use this JSON Path expression $..data I was able to extract the entire response but unable to extract user parameter. Thanks in advance
{
"data": "{ "took" : 13, "timed_out" : false, "_shards" : { "total" : 5, "successful" : 5, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : 1, "max_score" : 1.0, "hits" : [ { "_index" : "bushidodb_history_network_eval_ea9656ef-0a9b-474b-8026-2f83e2eb9df1_2021-april-10", "_type" : "network", "_id" : "6e2e58be-0ccf-3fb4-8239-1d4f2af322e21618059082000", "_score" : 1.0, "_source" : { "misMatches" : [ "protocol", "state", "command" ], "instance" : "e3032804-4b6d-3735-ac22-c827950395b4|0.0.0.0|10.179.155.155|53|UDP", "protocol" : "UDP", "localAddress" : "0.0.0.0", "localPort" : "12345", "foreignAddress" : "10.179.155.155", "foreignPort" : "53", "command" : "ping yahoo.com ", "user" : "testuser1", "pid" : "10060", "state" : "OUTGOINGFQ", "rate" : 216.0, "originalLocalAddress" : "192.168.100.229", "exe" : "/bin/ping", "md5" : "f9ad63ce8592af407a7be43b7d5de075", "dir" : "", "agentId" : "abcd-dcd123", "year" : "2021", "month" : "APRIL", "day" : "10", "hour" : "12", "time" : "1618059082000", "isMerged" : false, "timestamp" : "Apr 10, 2021 12:51:22 PM", "metricKey" : "6e2e58be-0ccf-3fb4-8239-1d4f2af322e2", "isCompliant" : false }, "sort" : [ 1618059082000 ] } ] }, "aggregations" : { "count_over_time" : { "buckets" : [ { "key_as_string" : "2021-04-10T08:00:00.000-0400", "key" : 1618056000000, "doc_count" : 1 } ] } }}",
"success": true,
"message": {
"code": "S",
"message": "Get Eval results Count Success"
}
}
Actual Response:
Images
What you posted doesn't look like a valid JSON to me.
If in reality you're getting what's in your image, to wit:
{
"data": "{ \"took\" : 13, \"timed_out\" : false, \"_shards\" : { \"total\" : 5, \"successful\" : 5, \"skipped\" : 0, \"failed\" : 0 }, \"hits\" : { \"total\" : 1, \"max_score\" : 1.0, \"hits\" : [ { \"_index\" : \"bushidodb_history_network_eval_ea9656ef-0a9b-474b-8026-2f83e2eb9df1_2021-april-10\", \"_type\" : \"network\", \"_id\" : \"6e2e58be-0ccf-3fb4-8239-1d4f2af322e21618059082000\", \"_score\" : 1.0, \"_source\" : { \"misMatches\" : [ \"protocol\", \"state\", \"command\" ], \"instance\" : \"e3032804-4b6d-3735-ac22-c827950395b4|0.0.0.0|10.179.155.155|53|UDP\", \"protocol\" : \"UDP\", \"localAddress\" : \"0.0.0.0\", \"localPort\" : \"12345\", \"foreignAddress\" : \"10.179.155.155\", \"foreignPort\" : \"53\", \"command\" : \"pingyahoo.com\", \"user\" : \"testuser1\", \"pid\" : \"10060\", \"state\" : \"OUTGOINGFQ\", \"rate\" : 216.0, \"originalLocalAddress\" : \"192.168.100.229\", \"exe\" : \"/bin/ping\", \"md5\" : \"f9ad63ce8592af407a7be43b7d5de075\", \"dir\" : \"\", \"agentId\" : \"abcd-dcd123\", \"year\" : \"2021\", \"month\" : \"APRIL\", \"day\" : \"10\", \"hour\" : \"12\", \"time\" : \"1618059082000\", \"isMerged\" : false, \"timestamp\" : \"Apr10, 202112: 51: 22PM\", \"metricKey\" : \"6e2e58be-0ccf-3fb4-8239-1d4f2af322e2\", \"isCompliant\" : false }, \"sort\" : [ 1618059082000 ] } ] }, \"aggregations\" : { \"count_over_time\" : { \"buckets\" : [ { \"key_as_string\" : \"2021-04-10T08: 00: 00.000-0400\", \"key\" : 1618056000000, \"doc_count\" : 1 } ] } }}",
"success": true,
"message": {
"code": "S",
"message": "Get Eval results Count Success"
}
}
the easiest way is just using 2 JSON Extractors:
Extract data attribute value into a JMeter Variable from the response
Extract user attribute value into a JMeter variable from ${data} JMeter Variable:
Demo:
If the response looks like exactly you posted you won't be able to use JSON Extractors and will have to treat it as normal text so your choice is limited to Regular Expression Extractor, example regular expression:
"user"\s*:\s*"(\w+)"
Add Regular Expression extractor with the corresponding request and extract it. Use the below expression.
Expression: "user" : "(.*?)"
Ref: https://jmeter.apache.org/usermanual/regular_expressions.html
Regular Expression Extractor Sample

How to push new key and value in JSON array in mongodb?

How can I push new key and value in JSON array?
I tried I used push keyword in update query but I got a different output. I used:
db.users.updateOne({"name":"viki"},{$push{"address.district":"thambaram"}})
I have this document:
{ "_id" : ObjectId("58934f10c7592b1494fd9a4d"), "name" : "viki", "age" : 100, "subject" : [ "c", "node.js", "java" ], "address" : { "city" : "chennai", "state" : "tamilnadu", "pincode" : "123" } }
I want to add "district":"thambaram" in address json array
I need like:
{ "_id" : ObjectId("58934f10c7592b1494fd9a4d"), "name" : "viki", "age" : 100, "subject" : [ "c", "node.js", "java" ], "address" : { "city" : "chennai", "state" : "tamilnadu", "pincode" : "123","district":"thambaram"} }
Use $set
db.users.updateOne({"name":"viki"},{$set:{"address.district":"thambaram"}})
This should work.
The $push operator appends a specified value to an array. In your case you should use $set

How to flatten sub-documents in mongo db

My collection has document like this
{
"_id" : ObjectId("587c8d0364b6e32706f7edef"),
"first_name" : "John",
"last_name" : "Doe",
"password" : "aasdjsabb12213b21bbcghc1h2",
"shift" : "A",
"dept" : "Management"
"Requests" : [
{
"weekId" : 1,
"MO" : 1,
"TU" : 2,
"W" : 3,
"TH" : 9,
"FR" : 10,
"SA" : 6,
"SU" : 1
}
]
}
I want to export the result of my query to csv and need fields flattened out like this
{
"_id" : ObjectId("587c8d0364b6e32706f7edef"),
"first_name" : "John",
"last_name" : "Doe",
"password" : "aasdjsabb12213b21bbcghc1h2",
"shift" : "A",
"dept" : "Management"
"weekId" : 1,
"MO" : 1,
"TU" : 2,
"W" : 3,
"TH" : 9,
"FR" : 10,
"SA" : 6,
"SU" : 1
}
I am trying to use aggregate function but to no avail. Can anyone suggest me how to do this?
This is my working code but I don't think this is the right way
db.req.aggregate([{$unwind:'$Requests'},{$project: {first_name:1,last_name:1,dept:1,"WeekId":"$Requests.weekdId","Mon":"$Requests.MO","Tue":"$Requests.TU","Wed":"$Requests.W","Thu":"$Requests.TH","Fri":"$Requests.FR","Sat":"$Requests.SA","Sun":"$Requests.SU"}},{$out:"results"}]);
You can do this with an aggregate query, but its not very pretty:
db.test.aggregate([
{$unwind:"$Requests"},
{$project:
{_id:1,
first_name:1,
last_name:1,
password:1,
shift:1,
dept:1,
weekId:"$Requests.weekId",
MO:"$Requests.MO",
TU:"$Requests.TU",
W:"$Requests.W",
TH:"$Requests.TH",
FR:"$Requests.FR",
SA:"$Requests.SA",
SU:"$Requests.SU"}}])
.pretty()
So basically unwind the Requests array, then project out the document you want to produce. Hope this makes sense.

How to format the TSV file in Druid

I am trying to load in a TSV in druid using this ingestion speck:
MOST UPDATED SPEC BELOW:
{
"type" : "index",
"spec" : {
"ioConfig" : {
"type" : "index",
"inputSpec" : {
"type": "local",
"baseDir": "quickstart",
"filter": "test_data.json"
}
},
"dataSchema" : {
"dataSource" : "local",
"granularitySpec" : {
"type" : "uniform",
"segmentGranularity" : "hour",
"queryGranularity" : "none",
"intervals" : ["2016-07-18/2016-07-22"]
},
"parser" : {
"type" : "string",
"parseSpec" : {
"format" : "json",
"dimensionsSpec" : {
"dimensions" : ["name", "email", "age"]
},
"timestampSpec" : {
"format" : "yyyy-MM-dd HH:mm:ss",
"column" : "date"
}
}
},
"metricsSpec" : [
{
"name" : "count",
"type" : "count"
},
{
"type" : "doubleSum",
"name" : "age",
"fieldName" : "age"
}
]
}
}
}
If my schema looks like this:
Schema: name email age
And actual dataset looks like this:
name email age Bob Jones 23 Billy Jones 45
Is this how the columns should be formatted^^ in the above dataset for a TSV? Like name email age should be first (the columns) and then the actual data. I am confused how Druid will know how to map the columns to the actual dataset in TSV format.
TSV stands for tab separated format, so it looks the same as csv but you will use tabs instead of commas e.g.
Name<TAB>Age<TAB>Address
Paul<TAB>23<TAB>1115 W Franklin
Bessy the Cow<TAB>5<TAB>Big Farm Way
Zeke<TAB>45<TAB>W Main St
you will use frist line as header to define your column names - so you can use "name", "age" or "email" in dimensions in your spec file
as for the gmt and utc, they are basically the same
There is no time difference between Greenwich Mean Time and
Coordinated Universal Time
first one is time zone, the other one is a time standard
btw don`t forget to include a column with some time value in your tsv file!!
so e.g. if you will have tsv file that looks like:
"name" "position" "office" "age" "start_date" "salary"
"Airi Satou" "Accountant" "Tokyo" "33" "2016-07-16T19:20:30+01:00" "162700"
"Angelica Ramos" "Chief Executive Officer (CEO)" "London" "47" "2016-07-16T19:20:30+01:00" "1200000"
your spec file should look like this:
{
"spec" : {
"ioConfig" : {
"inputSpec" : {
"type": "local",
"baseDir": "path_to_folder",
"filter": "name_of_the_file(s)"
}
},
"dataSchema" : {
"dataSource" : "local",
"granularitySpec" : {
"type" : "uniform",
"segmentGranularity" : "hour",
"queryGranularity" : "none",
"intervals" : ["2016-07-01/2016-07-28"]
},
"parser" : {
"type" : "string",
"parseSpec" : {
"format" : "tsv",
"dimensionsSpec" : {
"dimensions" : [
"position",
"age",
"office"
]
},
"timestampSpec" : {
"format" : "auto",
"column" : "start_date"
}
}
},
"metricsSpec" : [
{
"name" : "count",
"type" : "count"
},
{
"name" : "sum_sallary",
"type" : "longSum",
"fieldName" : "salary"
}
]
}
}
}

How to update a nested array value in mongodb?

I want update a array value that is nested within an array value: i.e. set
status = enabled
where alerts.id = 2
{
"_id" : ObjectId("5496a8ed49847b6cd7c7b350"),
"name" : "joe",
"locations" : [
{
"name": "my location",
"alerts" : [
{
"id" : 1,
"status" : null
},
{
"id" : 2,
"status" : null
}
]
}
]
}
I would have used the position $ character, but cannot use it twice in a statement - multi positional operators are not supported yet: https://jira.mongodb.org/browse/SERVER-831
How do I issue a statement to only update the status field of an alert matching an id of 2?
UPDATE
If I change the schema as follows:
{
"_id" : ObjectId("5496ab2149847b6cd7c7b352"),
"name" : "joe",
"locations" : {
"my location" : {
"alerts" : [
{
"id" : 1,
"status" : "enabled"
},
{
"id" : 2,
"status" : "enabled"
}
]
},
"my other location" : {
"alerts" : [
{
"id" : 3,
"status" : null
},
{
"id" : 4,
"status" : null
}
]
}
}
}
I can then use:
update({"locations.my location.alerts.id":1},{$set: {"locations.my location.alerts.$.status": "enabled"}});
Problem is I cannot create indexes on the alert id :-(
it may be better of modelled as such, specially if an index on location and,or alerts.id is needed.
{
"_id" : ObjectId("5496a8ed49847b6cd7c7b350"),
"name" : "joe",
"location" : "myLocation",
"alerts" : [{
"id" : 1,
"status" : null
},
{
"id" : 2,
"status" : null
}
]
}
{
"_id" : ObjectId("5496a8ed49847b6cd7c7b350"),
"name" : "joe",
"location" : "otherLocation",
"alerts" : [{
"id" : 1,
"status" : null
},
{
"id" : 2,
"status" : null
}
]
}
I think you are having a wrong tool for the job. What you have in your example is relational data and it's much easier to handle with relational database. So I would suggest to use SQL-database instead of mongo.
But if you really want to do it with mongo, then I guess the only option is to fetch the document and modify it and put it back.