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How to break a JSON response into smaller JSON part of a particular batch size


How to break a JSON response into smaller JSON part of a particular batch size

By : Scott Johnson
Date : November 22 2020, 10:31 AM
I wish did fix the issue. I have a small issue ... I am exposing a REST service which fetch a list of data in JSON format.. The following is my flow :- , Based on the JSON from your question, the code
code :
<json:json-to-object-transformer returnClass="java.util.Map"/>
<foreach batchSize="5" collection="#[payload['retrieveAllData']]">
  <json:object-to-json-transformer/>
   <logger message="ResponseLogdadasd :- #[message.payload]" level="INFO" doc:name="ResponseLogger"/>
</foreach>


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Spray JSON - parse only part of the JSON response

Spray JSON - parse only part of the JSON response


By : user2712294
Date : March 29 2020, 07:55 AM
hop of those help? Error message says that spray-json was expecting String but got sth else, it seems you need to define "lastTStamp" in Op class as Long, like this:
code :
case class Op(samples:Samples, lastTStamp:Long, isPersistent:Boolean)
How to break a JSON file into a smaller json wrapped in an array using jq?

How to break a JSON file into a smaller json wrapped in an array using jq?


By : Sophie
Date : March 29 2020, 07:55 AM
may help you . , jq IO is rather primitive, so I'd suggest starting with:
code :
def chunks(n):
  def c: .[0:n], (if length > n then .[n:]|c else empty end);
  c;

chunks(5)
jq -c -f chunk.jq foo.json
awk '{n++; print > "out" n ".json"}'
for f in out*.json ; do jq . $f | sponge $f ; done
jq -c --argjson n 5 'recurse(.[$n:]; length > 0) | .[0:$n]' foo.json
How to extract a specific part from JSON response with changing fields names in JSON structure (as in this example) with

How to extract a specific part from JSON response with changing fields names in JSON structure (as in this example) with


By : Joe Kim
Date : March 29 2020, 07:55 AM
I hope this helps you . If you have a dynamic key/value pair, you can use a Map-like structure to map your objects, for example:
code :
public class Page {
    private int pageId;
    private int ns;
    private String title;
    private String extract;

    // Getters, setters, ...
}

public class Query {
    private Map<String, Page> pages;

    // Getters, setters, ...
}
query.getPages()
    .values().stream()
    .findAny()
    .orElseThrow(() -> new RuntimeException("There is no page"));
How to break big Json response into multiple Json in dataweave 2?

How to break big Json response into multiple Json in dataweave 2?


By : user36077
Date : March 29 2020, 07:55 AM
I wish this helpful for you It is hard to tell based on your sample json as its not formatted json.
NOTE The expected input/output changed from my original answer so this is an update
code :
  <foreach doc:name="For Each"  collection="#[flatten(payload.parent.child.a)]" batchSize="2">
            <ee:transform doc:name="Transform Message" doc:id="7b1cccb7-fcbb-41b3-a08f-bac5600df2f2" >
                <ee:message >
                    <ee:set-payload ><![CDATA[%dw 2.0
output application/json
---
{
    parent :
    {
        child:[
           a: payload
        ]
    }
}]]></ee:set-payload>
                </ee:message>
            </ee:transform>
            <logger level="ERROR" message="Split items here: #[payload]" />
        </foreach>
  Split items here: {
      "parent": {
    "child": [
      {
        "a": [
          {

          },
          {

          }
        ]
      }
    ]
  }
}

Split items here: {
  "parent": {
"child": [
  {
    "a": [
      {

      },
      {

      }
    ]
  }
]
Padded batches does not handle the last batch of the data with smaller size than batch size

Padded batches does not handle the last batch of the data with smaller size than batch size


By : mikedensem
Date : March 29 2020, 07:55 AM
wish of those help you have constrained your placeholder to take exactly "batch_size" number of rows. To take any rows you can create placeholder like this
code :
self.img = tf.placeholder(
            name='img',
            dtype=tf.float32,
            shape=[None, self.img_size, self.img_size, 3]
        )
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