I'm trying to merge / reduce many JSON objects and somehow I'm not getting the expected result.
I'm only interested in getting all keys, the values and the number of items inside arrays are irrelevant.
file1.json:
{
"customerId": "xx",
"emails": [
{
"address": "james#zz.com",
"customType": "",
"type": "custom"
},
{
"address": "sales#x.com",
"primary": true
},
{
"address": "info#x.com"
}
]
}
{
"id": "654",
"emails": [
{
"address": "peter#x.com",
"primary": true
}
]
}
The desired output is a JSON object with all possible keys from all input objects. The values are irrelevant, any value from any input object is OK. But all keys from input objects must be present in output object:
{
"emails": [
{
"address": "james#zz.com", <--- any existing value works
"customType": "", <--- any existing value works
"type": "custom", <--- any existing value works
"primary": true <--- any existing value works
}
],
"customerId": "xx", <--- any existing value works
"id": "654" <--- any existing value works
}
I tried reducing it, but it misses many of the keys in the array:
$ jq -s 'reduce .[] as $item ({}; . + $item)' file1.json
{
"customerId": "xx",
"emails": [
{
"address": "peter#x.com",
"primary": true
}
],
"id": "654"
}
The structure of the objects contained in file1.json is unknown, so the solution must be agnostic of any keys/values and the solution must not assume any structure or depth.
Is it possible to fix this somehow considering how jq works? Or is it possible to solve this issue using another tool?
PS: For those of you that are curious, this is useful to infer a schema that can be created in a database. Given an arbitrary number of JSON objects with an arbitrary structure, it's easy to create a single JSON squished/merged/fused structure that will "accommodate" all JSON objects.
BigQuery is able to autodetect a schema, but only 500 lines are analyzed to come up with it. This presents problems if objects have different structures past that 500 line mark.
With this approach I can squish a JSON Lines file with 1000000s of objects into one line that can be then imported into BigQuery with the autodetect schema flag and it will work every time since BigQuery only has one line to analyze and this line is the "super-schema" of all the objects. After extracting the autodetected schema I can manually fine tune it to make sure types are correct and then recreate the table specifying my tuned schema:
$ ls -1 users*.json | wc --lines
3672
$ cat users*.json > users-all.json
$ cat users-all.json | wc --lines
146482633
$ jq 'squish' users-all.json > users-all-squished.json
$ cat users-all-squished.json | wc --lines
1
$ bq load --autodetect users users-all-squished.json
$ bq show schema --format=prettyjson users > users-schema.json
$ vi users-schema.json
$ bq rm --table users
$ bq mk --table users --schema=users-schema.json
$ bq load users users-all.json
[Some options are missing or changed for readability]
Here is a solution that produces the expected result in the sample example, and seems to meet all the stated requirements. It is similar to one proposed by #pmf on this page.
jq -n --stream '
def squish: map(if type == "number" then 0 else . end);
reduce (inputs | select(length==2)) as [$p, $v] ({}; setpath($p|squish; $v))
'
Output
For the example given in the Q, the output is:
{
"customerId": "xx",
"emails": [
{
"address": "peter#x.com",
"customType": "",
"type": "custom",
"primary": true
}
],
"id": "654"
}
As #peak has pointed out, some aspects are underspecified. For instance, what should happen with .customerId and .id? Are they always the same across all files (as suggested by the sample files provided)? Do you want the items of the .emails array just thrown into one large array, or do you want to have them "merged" by some criteria (e.g. by a common value in their .address field)? Here are some stubs to start from:
Simply concatenate the .emails arrays and take all other parts from the first file:
jq 'reduce inputs as $in (.; .emails += $in.emails)' file*.json
# or simpler
jq '.emails += [inputs.emails[]]' file*.json
Demo Demo
{
"emails": [
{
"address": "cc#xx.com"
},
{
"address": "james#zz.com",
"customType": "",
"type": "custom"
},
{
"address": "james#x.com"
},
{
"address": "sales#x.com",
"primary": true
},
{
"address": "info#x.com"
},
{
"address": "james#x.com"
},
{
"address": "sales#x.com",
"primary": true
},
{
"address": "info#x.com"
}
],
"customerId": "xx",
"id": "654"
}
Merge the objects in the .emails array by a common value in their .address field, with latter values overwriting former values for other fields with colliding names, and discard all other parts from the files:
jq -n 'reduce inputs.emails[] as $e ({}; .[$e.address] += $e) | map(.)' file*.json
Demo
[
{
"address": "cc#xx.com"
},
{
"address": "james#zz.com",
"customType": "",
"type": "custom"
},
{
"address": "james#x.com"
},
{
"address": "sales#x.com",
"primary": true
},
{
"address": "info#x.com"
}
]
If you are only interested in a list of unique field names for a given address, regardless of the counts and values used, you can also go with:
jq -n '
reduce inputs.emails[] as $e ({}; .[$e.address][$e | keys_unsorted[]] = 1)
| map_values(keys)
'
Demo
{
"cc#xx.com": [
"address"
],
"james#zz.com": [
"address",
"customType",
"type"
],
"james#x.com": [
"address"
],
"sales#x.com": [
"address",
"primary"
],
"info#x.com": [
"address"
]
}
The structure of the objects contained in file1.json is unknown, so the solution must be agnostic of any keys/values and the solution must not assume any structure or depth.
You can use the --stream flag to break down the structure into an array of paths and values, discard the values part and make the paths unique:
jq --stream -nc '[inputs[0]] | unique[]' file*.json
["customerId"]
["emails"]
["emails",0,"address"]
["emails",0,"customType"]
["emails",0,"primary"]
["emails",0,"type"]
["emails",1,"address"]
["emails",2]
["emails",2,"address"]
["emails",2,"primary"]
["emails",3]
["emails",3,"address"]
["id"]
Trying to build a representation of this, similar to any of the input files, comes with a lot of caveats. For instance, how would you represent in a single structure if one file had .emails as an array of objects, and another had .emails as just an atomic value, say, a string. You would not be able to represent this plurality without introducing new, possibly ambiguous structures (e.g. putting all possibilities into an array).
Therefore, having a list of paths could be a fair compromise. Judging by your desired output, you want to focus more on the object structure, so you could further reduce complexity by discarding the array indices. Depending on your use case, you could replace them with a single value to retain the information of the presence of an array, or discard them entirely:
jq --stream -nc '[inputs[0] | map(numbers = 0)] | unique[]' file*.json
["customerId"]
["emails"]
["emails",0]
["emails",0,"address"]
["emails",0,"customType"]
["emails",0,"primary"]
["emails",0,"type"]
["id"]
jq --stream -nc '[inputs[0] | map(strings)] | unique[]' file*.json
["customerId"]
["emails"]
["emails","address"]
["emails","customType"]
["emails","primary"]
["emails","type"]
["id"]
The following program meets these two key requirements:
"all keys from input objects must be present in output object";
"the solution must be agnostic of any keys/values and the solution must not assume any structure or depth."
The approach is the same as one suggested by #pmf, and for the example given in the Q, produces results that are very similar to the one that is shown:
jq -n --stream '
def squish: map(select(type == "string"));
reduce (inputs | select(length==2)) as [$p, $v] ({};
setpath($p|squish; $v))
'
With the given input, this produces:
{
"customerId": "xx",
"emails": {
"address": "peter#x.com",
"customType": "",
"type": "custom",
"primary": true
},
"id": "654"
}
I've got some JSON like the following (I've filtered the output here):
[
{
"Tags": [
{
"Key": "Name",
"Value": "example1"
},
{
"Key": "Irrelevant",
"Value": "irrelevant"
}
],
"c7n:MatchedFilters": [
"tag: example_tag_rule"
],
"another_key": "another_value_I_dont_want"
},
{
"Tags": [
{
"Key": "Name",
"Value": "example2"
}
],
"c7n:MatchedFilters": [
"tag:example_tag_rule",
"tag: example_tag_rule2"
]
}
]
I'd like to create a csv file with the value within the Name key and all of the "c7n:MatchedFilters" in the array. I've made a few attempts but still can't get quite the output I expect. There's some example code and the output below:
#Prints the key that I'm after.
cat new.jq | jq '.[] | [.Tags[], {"c7n:MatchedFilters"}] | .[] | select(.Key=="Name")|.Value'
"example1"
"example2"
#Prints all the filters in an array I'm after.
cat new.jq | jq -r '.[] | [.Tags[], {"c7n:MatchedFilters"}] | .[] | select(."c7n:MatchedFilters") | .[]'
[
"tag: example_tag_rule"
]
[
"tag:example_tag_rule",
"tag: example_tag_rule2"
]
#Prints *all* the tags (including ones I don't want) and all the filters in the array I'm after.
cat new.jq | jq '.[] | [.Tags[], {"c7n:MatchedFilters"}] | select((.[].Key=="Name") and (.[]."c7n:MatchedFilters"))'
[
{
"Key": "Name",
"Value": "example1"
},
{
"Key": "Irrelevant",
"Value": "irrelevant"
},
{
"c7n:MatchedFilters": [
"tag: example_tag_rule"
]
}
]
[
{
"Key": "Name",
"Value": "example2"
},
{
"c7n:MatchedFilters": [
"tag:example_tag_rule",
"tag: example_tag_rule2"
]
}
]
I hope this makes sense, let me know if I've missed anything.
Your attempts are not working because you start out with [.Tags[], {"c7n:MatchedFilters"}] to construct one array containing all the tags and an object containing the filters. You are then struggling to find a way to process this entire array at once because it jumbles together these unrelated things without any distinction. You will find it much easier if you don't combine them in the first place!
You want to find the single tag with a Key of "Name". Here's one way to find that:
first(
.Tags[]|
select(.Key=="Name")
).Value as $name
By using a variable binding we can save it for later and worry about constructing the array separately.
You say (in the comments) that you just want to concatenate the filters with spaces. You can do that easily enough:
(
."c7n:MatchedFilters"|
join(" ")
) as $filters
You can combine all this together like follows. Note that each variable binding leaves the input stream unchanged, so it's easy to compose everything.
jq --raw-output '
.[]|
first(
.Tags[]|
select(.Key=="Name")
).Value as $name|
(
."c7n:MatchedFilters"|
join(" ")
) as $filters|
[$name, $filters]|
#csv
Hopefully that's easy enough to read and separates out each concept. We break up the array into a stream of objects. For each object, we find the name and bind it to $name, we concatenate the filters and bind them to $filters, then we construct an array containing both, then we convert the array to a CSV string.
We don't need to use variables. We could just have a big array constructor wrapped around the expression to find the name and the expression to find the filters. But I hope you can see the variables make things a bit flatter and easier to understand.
I have some JSON like this:
{
"x": [
{
"name": "Hello",
"id": "211"
},
{
"name": "Goodbye",
"id": "221"
},
{
"name": "Christmas",
"id": "171"
}
],
"y": "value"
}
Using jq, given a name value (e.g. Christmas) how can I get it's associated id (i.e. 171).
I've got as far as being able to check for presence of the name in one of the array's objects, but I can't work out how to filter it down
jq -r 'select(.x[].name == "Christmas")'
jq approach:
jq -r '.x[] | select(.name == "Christmas").id' file
171
The function select(boolean_expression) produces its input unchanged if boolean_expression returns true for that input, and produces no output otherwise.
It can also been done like:
jq '.x[] | select(.name == "Christmas").id'
Also you can try this at link online jq play
Using jq I tried to update this json document:
{
"git_defaults": {
"branch": "master",
"email": "jenkins#host",
"user": "Jenkins"
},
"git_namespaces": [
{
"name": "NamespaceX",
"modules": [
"moduleA",
"moduleB",
"moduleC",
"moduleD"
]
},
{
"name": "NamespaceY",
"modules": [
"moduleE"
]
}
]
}
with adding moduleF to NamespaceY. I need to write the file back again to the original source file.
I came close (but no cigar) with:
jq '. | .git_namespaces[] | select(.name=="namespaceY").modules |= (.+ ["moduleF"])' config.json
and
jq '. | select(.git_namespaces[].name=="namespaceY").modules |= (.+ ["moduleF"])' config.json
The following filter should perform the update you want:
(.git_namespaces[] | select(.name=="NamespaceY").modules) += ["moduleF"]
Note that the initial '.|' in your attempt is not needed; that "NamespaceY" is capitalized in config.json; that the parens as shown are the keys to success; and that += can be used here.
One way to write back to the original file would perhaps be to use 'sponge'; other possibilities are discussed on the jq FAQ https://github.com/stedolan/jq/wiki/FAQ
I have a hierarchically deep JSON object created by a scientific instrument, so the file is somewhat large (1.3MB) and not readily readable by people. I would like to get a list of keys, up to a certain depth, for the JSON object. For example, given an input object like this
{
"acquisition_parameters": {
"laser": {
"wavelength": {
"value": 632,
"units": "nm"
}
},
"date": "02/03/2525",
"camera": {}
},
"software": {
"repo": "github.com/username/repo",
"commit": "a7642f",
"branch": "develop"
},
"data": [{},{},{}]
}
I would like an output like such.
{
"acquisition_parameters": [
"laser",
"date",
"camera"
],
"software": [
"repo",
"commit",
"branch"
]
}
This is mainly for the purpose of being able to enumerate what is in a JSON object. After processing the JSON objects from the instrument begin to diverge: for example, some may have a field like .frame.cross_section.stats.fwhm, while others may have .sample.species, so it would be convenient to be able to interrogate the JSON object on the command line.
The following should do exactly what you want
jq '[(keys - ["data"])[] as $key | { ($key): .[$key] | keys }] | add'
This will give the following output, using the input you described above:
{
"acquisition_parameters": [
"camera",
"date",
"laser"
],
"software": [
"branch",
"commit",
"repo"
]
}
Given your purpose you might have an easier time using the paths builtin to list all the paths in the input and then truncate at the desired depth:
$ echo '{"a":{"b":{"c":{"d":true}}}}' | jq -c '[paths|.[0:2]]|unique'
[["a"],["a","b"]]
Here is another variation uing reduce and setpath which assumes you have a specific set of top-level keys you want to examine:
. as $v
| reduce ("acquisition_parameters", "software") as $k (
{}; setpath([$k]; $v[$k] | keys)
)