here is my API get request:
{
"data": [
{
"id": 2,
"attributes": {
"title": "something",
"game": "default",
"players": "static",
}
}
],
}
I would like to set "Players" to an array like below:
"attributes": {
"title": "23123",
"game": "1231",
"players": [
"1" : "static1",
"2" : "static2",
"3" : static3",
],
}
how can i make this array?
You need to make a component called "Player" from content-type builder and then add this component with repeatable to your main entity type.
[
{
"key": "test1",
"category": "test",
"name": "test1",
"translations":
{
"english": "eng"
}
},
{
"key": "test2",
"category": "test",
"name": "test1",
"translations":
{
"english": "eng2",
"german": "German"
}
},
{
"key": "test3",
"category": "power",
"name": "test1",
"translations":
{
"EN_lang": "jik"
}
}
]
Here, we have multiple field's are with different values and we have to match value in translations (field position will change on every call)
You have to be clear about what you want to assert. Hint, the new contains deep (available in 0.9.6.RC4) can help:
* match response contains deep { key: 'test2', translations: { english: 'eng2' } }
Else you should look at transforming the JSON into a shape where it is easier to do the assertions you want: https://github.com/intuit/karate#json-transforms
I'm trying to use UpdateRecord 1.9.0 processor to modify a JSON but it does not replace the values as I want.
this is the source message
{
"type": "A",
"ids": [{
"id": "1",
"value": "abc"
}, {
"id": "2",
"value": "def"
}, {
"id": "3",
"value": "ghi"
}
]
}
and the wanted output
{
"ids": [{
"userId": "1",
}, {
"userId": "2",
}, {
"userId": "3",
}
]
}
I have configured the processor as follows
processor config
Reader:
reader
Schema registry:
schema
writer:
writer
And it works, the output is a JSON without the field 'type' and the ids have the field 'userId' instead 'id' and 'value'.
To fill the value of userId, I defined the replace strategy and the property to replace:
strategy
But the output is wrong. The userId is always filled with the id of the last element in the array:
{
"ids": [{
"userId": "3"
}, {
"userId": "3"
}, {
"userId": "3"
}
]
}
I think the value of the expression is ok because if I try to replace only one record it works fine (/ids[0]/userId, ..id)
Nifi docs has a really similar example (example 3):
https://nifi.apache.org/docs/nifi-docs/components/org.apache.nifi/nifi-standard-nar/1.7.1/org.apache.nifi.processors.standard.UpdateRecord/additionalDetails.html
But it does not work for me.
What am I doing wrong?
thanks
Finally I have used JoltJSONTransform processor instead UpdateRecord
JoltJSONTransform
template:
[
{
"operation": "shift",
"spec": {
"ids":{
"*":{
"id": "ids[&1].userId"
}
}
}
}
]
Easier than UpdateRecord
I'm new in lodash (v3.10.1), and having a hard time understanding.
Hope someone can help.
I have an input something like this:
{
{"id":1,"name":"Matthew","company":{"id":1,"name":"abc","industry":{"id":5,"name":"Medical"}}},
{"id":2,"name":"Mark","company":{"id":1,"name":"abc","industry":{"id":5,"name":"Medical"}}},
{"id":3,"name":"Luke","company":{"id":1,"name":"abc","industry":{"id":5,"name":"Medical"}}},
{"id":4,"name":"John","company":{"id":1,"name":"abc","industry":{"id":5,"name":"Medical"}}},
{"id":5,"name":"Paul","company":{"id":1,"name":"abc","industry":{"id":5,"name":"Medical"}}}
];
I would like to output this or close to this:
{
"industries": [
{
"industry":{
"id":5,
"name":"Medical",
"companies": [
{
"company":{
"id":1,
"name":"abc",
"employees": [
{"id":1,"name":"Matthew"},
{"id":2,"name":"Mark"},
{"id":3,"name":"Luke"},
{"id":4,"name":"John"},
{"id":5,"name":"Paul"}
]
}
}
]
}
}
]
}
Here's something that gets you close to what you want. I structured the output to be an object instead of an array. You don't need the industries or industry properties in your example output. The output structure looks like this:
{
"industry name": {
"id": "id of industry",
"companies": [
{
"company name": "name of company",
"id": "id of company",
"employees": [
{
"id": "id of company",
"name": "name of employee"
}
]
}
]
}
}
I use the _.chain function to wrap the collection with a lodash wrapper object. This enables me to explicitly chain lodash functions.
From there, I use the _.groupBy function to group elements of the collection by their industry name. Since I'm chaining, I don't have to pass in the array again to the function. It's implicitly passed via the lodash wrapper. The second argument of the _.groupBy is the path to the value I want to group elements by. In this case, it's the path to the industry name: company.industry.name. _.groupBy returns an object with each employee grouped by their industry (industries are keys for this object).
I then do use _.transform to transform each industry object. _.transform is essentially _.reduce except that the results returned from the _.transform function is always an object.
The function passed to the _.transform function gets executed against each key/value pair in the object. In the function, I use _.groupBy again to group employees by company. Based off the results of _.groupBy, I map the values to the final structure I want for each employee object.
I then call the _.value function because I want to unwrap the output collection from the lodash wrapper object.
I hope this made sense. If it doesn't, I highly recommend reading Lo-Dash Essentials. After reading the book, I finally got why lodash is so useful.
"use strict";
var _ = require('lodash');
var emps = [
{ "id": 1, "name": "Matthew", "company": { "id": 1, "name": "abc", "industry": { "id": 5, "name": "Medical" } } },
{ "id": 2, "name": "Mark", "company": { "id": 1, "name": "abc", "industry": { "id": 5, "name": "Medical" } } },
{ "id": 3, "name": "Luke", "company": { "id": 1, "name": "abc", "industry": { "id": 5, "name": "Medical" } } },
{ "id": 4, "name": "John", "company": { "id": 1, "name": "abc", "industry": { "id": 5, "name": "Medical" } } },
{ "id": 5, "name": "Paul", "company": { "id": 1, "name": "abc", "industry": { "id": 5, "name": "Medical" } } }
];
var result = _.chain(emps)
.groupBy("company.industry.name")
.transform(function(result, employees, industry) {
result[industry] = {};
result[industry].id = _.get(employees[0], "company.industry.id");
result[ industry ][ 'companies' ] = _.map(_.groupBy(employees, "company.name"), function( employees, company ) {
return {
company: company,
id: _.get(employees[ 0 ], 'company.id'),
employees: _.map(employees, _.partialRight(_.pick, [ 'id', 'name' ]))
};
});
return result;
})
.value();
Results from your example are as follows:
{
"Medical": {
"id": 5,
"companies": [
{
"company": "abc",
"id": 1,
"employees": [
{
"id": 1,
"name": "Matthew"
},
{
"id": 2,
"name": "Mark"
},
{
"id": 3,
"name": "Luke"
},
{
"id": 4,
"name": "John"
},
{
"id": 5,
"name": "Paul"
}
]
}
]
}
}
If you ever wanted the exact same structure as in the questions, I solved it using the jsonata library:
(
/* lets flatten it out for ease of accessing the properties*/
$step1 := $ ~> | $ |
{
"employee_id": id,
"employee_name": name,
"company_id": company.id,
"company_name": company.name,
"industry_id": company.industry.id,
"industry_name": company.industry.name
},
["company", "id", "name"] |;
/* now the magic begins*/
$step2 := {
"industries":
[($step1{
"industry" & $string(industry_id): ${
"id": $distinct(industry_id)#$I,
"name": $distinct(industry_name),
"companies": [({
"company" & $string(company_id): {
"id": $distinct(company_id),
"name": $distinct(company_name),
"employees": [$.{
"id": $distinct(employee_id),
"name": $distinct(employee_name)
}]
}
} ~> $each(function($v){ {"company": $v} }))]
}
} ~> $each(function($v){ {"industry": $v} }))]
};
)
You can see it in action on the live demo site: https://try.jsonata.org/VvW4uTRz_
I have a user document which contains many tags
Here is the mapping:
{
"user" : {
"properties" : {
"tags" : {
"type" : "nested",
"properties" : {
"id" : {
"type" : "string",
"index" : "not_analyzed",
"store" : "yes"
},
"current" : {
"type" : "boolean"
},
"type" : {
"type" : "string"
},
"value" : {
"type" : "multi_field",
"fields" : {
"value" : {
"type" : "string",
"analyzer" : "name_analyzer"
},
"value_untouched" : {
"type" : "string",
"index" : "not_analyzed",
"include_in_all" : false
}
}
}
}
}
}
}
}
Here are the sample user documents:
User 1
{
"created_at": 1317484762000,
"updated_at": 1367040856000,
"tags": [
{
"type": "college",
"value": "Dhirubhai Ambani Institute of Information and Communication Technology",
"id": "a6f51ef8b34eb8f24d1c5be5e4ff509e2a361829"
},
{
"type": "company",
"value": "alma connect",
"id": "58ad4afcc8415216ea451339aaecf311ed40e132"
},
{
"type": "company",
"value": "Google",
"id": "93bc8199c5fe7adfd181d59e7182c73fec74eab5",
"current": true
},
{
"type": "discipline",
"value": "B.Tech.",
"id": "a7706af7f1477cbb1ac0ceb0e8531de8da4ef1eb",
"institute_id": "4fb424a5addf32296f00013a"
},
]
}
User 2:
{
"created_at": 1318513355000,
"updated_at": 1364888695000,
"tags": [
{
"type": "college",
"value": "Dhirubhai Ambani Institute of Information and Communication Technology",
"id": "a6f51ef8b34eb8f24d1c5be5e4ff509e2a361829"
},
{
"type": "college",
"value": "Bharatiya Vidya Bhavan's Public School, Jubilee hills, Hyderabad",
"id": "d20730345465a974dc61f2132eb72b04e2f5330c"
},
{
"type": "company",
"value": "Alma Connect",
"id": "93bc8199c5fe7adfd181d59e7182c73fec74eab5"
},
{
"type": "sector",
"value": "Website and Software Development",
"id": "dc387d78fc99ab43e6ae2b83562c85cf3503a8a4"
}
]
}
User 3:
{
"created_at": 1318513355001,
"updated_at": 1364888695010,
"tags": [
{
"type": "college",
"value": "Dhirubhai Ambani Institute of Information and Communication Technology",
"id": "a6f51ef8b34eb8f24d1c5be5e4ff509e2a361821"
},
{
"type": "sector",
"value": "Website and Software Development",
"id": "dc387d78fc99ab43e6ae2b83562c85cf3503a8a1"
}
]
}
Using the above ES documents for search, I want to construct a query where I need to fetch users who have company tags in nested tag documents or the users who do not have any company tags. What will be my search query?
For example in above case, if search for google tag, then the returned documents should be 'user 1' and 'user 3' (as user 1 has company tag google and user 3 has no company tag). User 2 is not returned as it has a company tag other than google too.
Not trivial at all, mainly due to the not have a type:company tag clause. Here's what I came up with:
{
"or" : {
"filters" : [ {
"nested" : {
"filter" : {
"and" : {
"filters" : [ {
"term" : {
"tags.value" : "google"
}
}, {
"term" : {
"tags.type" : "company"
}
} ]
}
},
"path" : "tags"
}
}, {
"not" : {
"filter" : {
"nested" : {
"filter" : {
"term" : {
"tags.type" : "company"
}
},
"path" : "tags"
}
}
}
} ]
}
}
It contains an or filter with two nested clauses: the first one finds the documents that have tags.type:company and tags.value:google, while the second one finds all the documents that don't have any tags.type:company.
This needs to be optimized though since and/or/not filters don't take advantage of caching for filters that work with bitsets, like the term filter does. It would be best to take some more time to find a way to use a bool filter and obtain the same result. Have a lookt this article to know more.