Is there a way to add the id property when generating jsonschema?
Using the jackson databind, I am:
ObjectMapper mapper = new ObjectMapper();
SchemaFactoryWrapper visitor = new SchemaFactoryWrapper();
JsonSchemaGenerator jsg = new JsonSchemaGenerator(mapper, visitor);
JsonSchema jsonSchema = jsg.generateSchema(Status.class);
On the following enum:
public enum Status {
ON,
OFF;
}
It generates:
{
"type" : "string",
"enum" : [ "ON", "OFF" ]
}
However, if would like it to include the id:
{
"id" : "urn:jsonschema:com:example:enums:Status"
"type" : "string",
"enum" : [ "ON", "OFF" ]
}
Is this possible?
Related
I'm upgrading a project from SpringFox to SpringDoc v1.6.12 and I struggle to make the new code work for the following method of my RestController:
#PostMapping(path = TASK_MAPPING_PATH, consumes = MediaType.APPLICATION_FORM_URLENCODED_VALUE)
public ResponseEntity<String> loadTask(
#RequestParam String applicationId,
#RequestParam String businessId,
#RequestParam boolean directLink
) {[...]}
The particularity of this method is that it should encode its parameters in the body since the Content-Type application/x-www-form-urlencoded is used.
But when I browse the url https://localhost:8443/v3/api-docs, the generated code is the following:
"/api/enrolment/task" : {
"post" : {
"operationId" : "loadTask",
"parameters" : [ {
"in" : "query",
"name" : "applicationId",
"required" : true,
"schema" : {
"type" : "string"
}
}, {
"in" : "query",
"name" : "businessId",
"required" : true,
"schema" : {
"type" : "string"
}
}, {
"in" : "query",
"name" : "directLink",
"required" : true,
"schema" : {
"type" : "boolean"
}
} ],
"responses" : {
[...]
},
"summary" : [...],
"tags" : [...]
}
},
All of the applicationId, businessId and directLink parameters are passed in the URL instead of the request body as expected.
I would have expected the following openApi definition instead:
"/api/enrolment/task" : {
"post" : {
"operationId" : "loadTask",
"requestBody" : {
"content" : {
"application/x-www-form-urlencoded" : {
"schema" : {
"type" : "object",
"properties" : {
"applicationId" : {
"type" : "string"
},
"businessId" : {
"type" : "string"
},
"directLink" : {
"type" : "boolean"
}
},
"required" : [ "applicationId", "businessId", "directLink" ]
}
}
}
},
"responses" : {
[...]
},
"summary" : [...],
"tags" : [...]
}
},
Does anyone ever had the same issue ?
Does anyone knows the solution to my problem ?
Thanks.
I am generating index for my avro data in solr. Index are only getting generated for data elements which are at root level and not which are nested.
Below is the sample schema (not including all of it)
My Avro Schema is as below.
{
"type" : "record",
"name" : "abcd",
"namespace" : "xyz",
"doc" : "Schema Definition for Low Fare Search Shopping Request/Response Data",
"fields" : [ {
"name" : "ShopID",
"type" : "string"
}, {
"name" : "RqSysTimestamp",
"type" : [ "null", "string" ],
"default" : null
}, {
"name" : "RqTimestamp",
"type" : [ "null", "string" ],
"default" : null
}, {
"name" : "RsSysTimestamp",
"type" : [ "null", "string" ],
"default" : null
}, {
"name" : "RsTimestamp",
"type" : [ "null", "string" ],
"default" : null
}, {
"name" : "Request",
"type" : {
"type" : "record",
"name" : "RequestStruct",
"fields" : [ {
"name" : "TransactionID",
"type" : [ "string", "null" ]
}, {
"name" : "AgentSine",
"type" : [ "string", "null" ]
}, {
"name" : "CabinPref",
"type" : [ {
"type" : "array",
"items" : {
"type" : "record",
"name" : "CabinStruct",
"fields" : [ {
"name" : "Cabin",
"type" : [ "string", "null" ]
}, {
"name" : "PrefLevel",
"type" : [ "string", "null" ]
} ]
}
}, "null" ]
}, {
"name" : "CountryCode",
"type" : [ "string", "null" ]
},
"name" : "PassengerStatus",
"type" : [ "string", "null" ]
}, {
}
How do i refer "TransactionID" in my morphline config file. I tried all options but it does not generate index for data elements which are nested.
Below is the sample of my morphline config file.
extractAvroPaths {
flatten : true
paths : {
ShopID : /ShopID
RqSysTimestamp : /RqSysTimestamp
RqTimestamp : /RqTimestamp
RsSysTimestamp :/RsSysTimestamp
RsTimestamp : /RsTimestamp
TransactionID : "/Request/RequestStruct/TransactionID"
AgentSine : "/Request/RequestStruct/AgentSine"
Cabin :/Cabin
PrefLevel :/PrefLevel
CountryCode :/CountryCode
FrequentFlyerStatus :/FrequentFlyerStatus
The toAvro command expects a java.util.Map as input on conversion to a nested Avro record. So this is my solution.
morphlines: [
{
id: convertJsonToAvro
importCommands: [ "org.kitesdk.**" ]
commands: [
# read the JSON blob
{ readJson: {} }
# java code
{
java {
imports : """
import com.fasterxml.jackson.databind.JsonNode;
import com.fasterxml.jackson.databind.ObjectMapper;
import org.kitesdk.morphline.base.Fields;
import java.io.IOException;
import java.util.Set;
import java.util.ArrayList;
import java.util.Iterator;
import java.util.List;
import java.util.Map;
"""
code : """
String jsonStr = record.getFirstValue(Fields.ATTACHMENT_BODY).toString();
ObjectMapper mapper = new ObjectMapper();
Map<String, Object> map = null;
try {
map = (Map<String, Object>)mapper.readValue(jsonStr, Map.class);
} catch (IOException e) {
e.printStackTrace();
}
Set<String> keySet = map.keySet();
for (String o : keySet) {
record.put(o, map.get(o));
}
return child.process(record);
"""
}
}
# convert the extracted fields to an avro object
# described by the schema in this field
{ toAvro {
schemaFile: /etc/flume/conf/a1/like_user_event_realtime.avsc
} }
#{ logInfo { format : "loginfo: {}", args : ["#{}"] } }
# serialize the object as avro
{ writeAvroToByteArray: {
format: containerlessBinary
} }
]
}
]
My data model has few fixed fields and a block of variable fields. The variable fields as a block, can repeat o to n number of times within the same record.
The object person can be used as an analogy for this. The name has just one entry in each record but he can have o to n number of addresses, and the field address has a structure too. Is there a way to loop through the address schema for any number of addresses the person has? How do I mention this in the Avro schema file?
Have you tried using a nested Avro schema. That should solve your one-person-multiple-addresses requirement. Here is a schema that would help.
{
"type": "record",
"name" : "person",
"namespace" : "com.testavro",
"fields": [
{ "name" : "personname", "type": ["null","string"] },
{ "name" : "personId", "type": ["null","string"] },
{ "name" : "Addresses", "type": {
"type": "array",
"items": [ {
"type" : "record",
"name" : "Address",
"fields" : [
{ "name" : "addressLine1", "type": ["null", "string"] },
{ "name" : "addressLine2", "type": ["null", "string"] },
{ "name" : "city", "type": ["null", "string"] },
{ "name" : "state", "type": ["null", "string"] },
{ "name" : "zipcode", "type": ["null", "string"] }
]
}]
}
}
]
}
When code is generated with the above avro schema you get the person class and the Address class. The autogenerated class for person class(only field declarations) looks like
/**
* RecordBuilder for person instances.
*/
public static class Builder extends org.apache.avro.specific.SpecificRecordBuilderBase<person>
implements org.apache.avro.data.RecordBuilder<person> {
private java.lang.String personname;
private java.lang.String personId;
private java.util.List<java.lang.Object> Addresses;
and the Address class (only field declarations) looks like
/**
* RecordBuilder for Address instances.
*/
public static class Builder extends org.apache.avro.specific.SpecificRecordBuilderBase<Address>
implements org.apache.avro.data.RecordBuilder<Address> {
private java.lang.String addressLine1;
private java.lang.String addressLine2;
private java.lang.String city;
private java.lang.String state;
private java.lang.String zipcode;
Is this what you were looking for?
I'm trying to remove from MongoDB collection an object (not document) that meets specific value condition, in this case - "Accessible" : "null" - while keeping other instances of this objects. I tried db.collection.update({}, {$unset: { "Accessible":"null"}}, false, true) but it removed all objects with "Accessible" key.Thanks in advance
My MongoDB collection before update
{
"_id" : ObjectId("52e5f09e8f3d99e1046abccc"),
"Name" : "Skyline",
"Accessible" : "Y"
}
{
"_id" : ObjectId("52e5f09e8f3d99e1046abccd"),
"Name" : "Highland",
"Accessible" : "null"
}
Desired result:
{
"_id" : ObjectId("52e5f09e8f3d99e1046abccc"),
"Name" : "Skyline",
"Accessible" : "Y"
}
{
"_id" : ObjectId("52e5f09e8f3d99e1046abccd"),
"Name" : "Highland"
}
You need to first identify the documents you wish to update and then unset that specific field:
db.collection.update(
{"Accessible" : "null"},
{$unset: { "Accessible" : ""}},
{ multi: true }
)
Further documentation on $unset operator:
http://docs.mongodb.org/manual/reference/operator/update/unset/
I am using Elasticsearch with Haystacksearch and Django and want to search the follow structure:
{
{
"title": "book1",
"category" : ["Cat_1", "Cat_2"],
"key_values" :
[
{
"key_name" : "key_1",
"value" : "sample_value_1"
},
{
"key_name" : "key_2",
"value" : "sample_value_12"
}
]
},
{
"title": "book2",
"category" : ["Cat_3", "Cat_2"],
"key_values" :
[
{
"key_name" : "key_1",
"value" : "sample_value_1"
},
{
"key_name" : "key_3",
"value" : "sample_value_6"
},
{
"key_name" : "key_4",
"value" : "sample_value_5"
}
]
}
}
Right now I have set up an index model using Haystack with a "text" that put all the data together and runs a full text search! In my opinion this is not the a well established search 'cause I am not using my data set structure and hence this is some kind odd.
As an example if for an object I have a key-value
{
"key_name": "key_1",
"value": "sample_value_1"
}
and for another object I have
{
"key_name": "key_2",
"value": "sample_value_1"
}
and we it gets a query like "Key_1 sample_value_1" comes I get a thoroughly mixed result of objects who have these words in their fields rather than using their structures.
P.S. I am totally new to ElasticSearch and better to say new to the search technologies and challenges. I have searched the web and SO button didn't find anything satisfying. Please let me know if there is something wrong with my thoughts and expectations from these search engines and if there is SO duplicate question! And also if there is a better approach to design a database for this kind of search
Read the es docs on nested mappings and do something like this:
"book_type" : {
"properties" : {
// title, cat mappings
"key_values" : {
"type" : "nested"
"properties": {
"key_name": {
"type": "string", "index": "not_analyzed"
},
"value": {
"type": "string"
}
}
}
}
}
Then query using a nested query
"nested" : {
"path" : "key_values",
"query" : {
"bool" : {
"must" : [
{
"term" : {"key_values.key_name" : "key_1"}
},
{
"match" : {"key_values.value" : "sample_value_1"}
}
]
}
}
}