Hi Steve, Maybe you could implement a custom TableSource that queries the data from the rest API and converts the JSON directly into a Row data type. This would also avoid going through the DataStream API just for ingesting the data.
Best, Fabian Am Mi., 4. Sept. 2019 um 15:57 Uhr schrieb Steve Robert < contact.steverob...@gmail.com>: > Hi guys , > > It's been a while since I'm studying TABLE APIs for integration into my > system. > when i take a look on this documentation > : > https://ci.apache.org/projects/flink/flink-docs-release-1.9/dev/table/connect.html#connectors > > > I understand that it is possible to apply a JSON FORMAT on the connector > and apply a JSON-SCHEMA without any hardcoded java pojo > .jsonSchema( > "{" + > " type: 'object'," + > " properties: {" + > " lon: {" + > " type: 'number'" + > " }," + > " rideTime: {" + > " type: 'string'," + > " format: 'date-time'" + > " }" + > " }" + > "}" > ) > > > but my problematic is the following my data comes from REST-API , so I > have to process the data and transmit it via a DataStream > the problem is that between the conversation of a dataStream and a > table must pass through a Java Pojo. Datastream<YourPojo> input.... > Table table=tEnv.fromDataStream(input); > I tried a trick while making a conversation from my JSON to AVRO using > a GenericRecord but it does not seem possible . > > my user case and being able to add REST-API processing in runtime and > be able to outsource and dynamically load my Pojo / Schema without harcode > an Java-Pojo object > > > Do you have an approach to suggest me ? > > > Thank a lot >