You can use the JoltTransformJSON processor for this. Here is a Chain spec that should get you what you want: [ { "operation": "shift", "spec": { "0": { "*": "header" }, "*": "data[]" } }, { "operation": "shift", "spec": { "data": { "*": { "*": { "@0": "[&2].@(4,header[&])" } } } } } ] The first operation splits the top array into "header" (containing the first element) and "data" (containing the rest). The second operation creates an array of objects, each object having the keys from the header associated with the values from each element in the "data" array. With your input above, I get the following output: [ { "host" : "DUSTSADMIN.ads.xyz.de", "host_icons" : "menu", "host_state" : "UP", "num_services_crit" : "0", "num_services_ok" : "28", "num_services_pending" : "0", "num_services_unknown" : "0", "num_services_warn" : "0" }, { "host" : "DUSTSVMDC01.ads.xyz.de", "host_icons" : "menu", "host_state" : "UP", "num_services_crit" : "0", "num_services_ok" : "34", "num_services_pending" : "0", "num_services_unknown" : "0", "num_services_warn" : "0" }, { "host" : "DUSTSVMDC02.ads.xyz.de", "host_icons" : "menu", "host_state" : "UP", "num_services_crit" : "0", "num_services_ok" : "34", "num_services_pending" : "0", "num_services_unknown" : "0", "num_services_warn" : "0" } ] ... View more

FetchElasticsearch is used to get a single document from an ES cluster. Each document in ES has a document identifier (or "_id") associated with it, and that identifier is what should be supplied to the Document Identifier property. If you don't know the document identifier for the document(s) you're looking for, then QueryElasticsearchHttp is your best bet. It allows you to use the Query String "mini-language" to search for fields with desired values (see here for more information). You can then parse the results using any number of processors, such as EvaluateJsonPath to get individual fields from the results, SplitJson if there are multiple results, etc. ... View more

As of NiFi 1.2.0 you may be able to use ConvertRecord to do this, with a JsonTreeReader and a CSVRecordSetWriter (with a Record separator of comma and a value separator of a single space). Prior to 1.2.0 (or if the above approach doesn't work), you can use ExecuteScript. Here is a sample Groovy script that will read all the "term" values from the incoming JSON object and add an attribute called "terms" containing the comma-separated list: def flowFile = session.get() if(!flowFile) return def input = session.read(flowFile) def json = new groovy.json.JsonSlurper().parse(input) def terms = json.results.collect { it.term }.join(',') input.close() flowFile = session.putAttribute(flowFile, 'terms', terms) session.transfer(flowFile, REL_SUCCESS) If instead you need to replace the content of the flow file with the comma-separated list: def flowFile = session.get() if(!flowFile) return flowFile = session.write(flowFile, { inputStream, outputStream -> def json = new groovy.json.JsonSlurper().parse(inputStream) def terms = json.results.collect { it.term }.join(',') outputStream.write(terms.bytes) } as StreamCallback) flowFile = session.putAttribute(flowFile, 'mime.type', 'text/csv') session.transfer(flowFile, REL_SUCCESS) ... View more

After ConvertJSONToSQL you should not have JSON in the flowfile content, rather it should be a SQL statement. From the screenshot, you are sending all relationships to PutSQL, when you should only send the "sql" relationship. The "original" and "failure" relationships contain the input JSON, the "sql" relationship contains the corresponding SQL statement(s). ... View more

What are your attributes named, and what are their values? AttributesToJSON will not create an array for you, but you can use JoltTransformJSON after AttributesToJSON to create an array from the attributes. Given this example input JSON: { "error_message_1": "missing_field_1", "error_message_2": "missing_field_2" } You can use the following Shift spec in the JoltTransformJSON processor: { "operation": "shift", "spec": { "error_message_*": "errors[].errorMessage" } } This gives the following output (which matches your goal above): { "errors" : [ { "errorMessage" : "missing_field_1" }, { "errorMessage" : "missing_field_2" } ] } ... View more