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Create a structured streaming spark job that streams from a kafka topic and then calls a python flask app and stores the returned data back in a new kafka topic

This project includes writing a simple SPARK APPLICATION in SCALA. This will be launched with spark-submit option.

I prefer if we use structured streaming in KAFKA: [login to view URL]

Please make it a maven project with [login to view URL] so it can be built easily!

Objectives:

a) A kafka topic exists with the name "topicA"

____________

b) When you subscribe to that topic you get the following output for example in JSON format:

{"destination":"213","source":"111","productId":"10","submittedTs":"20003","userAgent":"v7","_firstEts":"1922","content":"This is an example c0ntent","accountId":"111-222","contentEncoding":"NORMAL","channel":"xxc"}

{"destination":"213","source":"234","productId":"10","submittedTs":"2409`","userAgent":"v7","_firstEts":"2019","content":"Another example content","accountId":"111-222","contentEncoding":"NORMAL","channel":"xxc"}

{"destination":"124","source":"55565","productId":"12","submittedTs":"44323","userAgent":"v7","_firstEts":"2022","content":"Blah blah food","accountId":"111-222","contentEncoding":"NORMAL","channel":"xxc"}

{"destination":"2232","source":"511","productId":"11","submittedTs":"54124","userAgent":"v7","_firstEts":"2302","content":"the quick brown fox jumped!","accountId":"111-222","contentEncoding":"NORMAL","channel":"xxc"}

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c) A spark job will be able to stream data from a kafka topic and then extract certain fields from topicA namely:

This should be written in a way where it is easy to add/remove more fields that want to be extracted from it.

-) accountId

-) submittedTs

-) source

-) destination

-) content

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d) and this will then be sent to a python flask server which will return back the following to the spark application:

Note: 1 new field comes back from flask server called "feature"

This should also be written in a way where it is easy to add/remove fields that come back from the flask python server.

-) accountId

-) content

-) feature

-) submittedTs

{"accountId":"111-222","content":"This is an example c0ntent","feature":"hello","submittedTs":"20003"}

{"accountId":"111-222","content":"Another example content":"hello","submittedTs":"2409"}

{"accountId":"111-222","content":"Blah blah food","feature":"hello","submittedTs":"44323"}

{"accountId":"111-222","content":"the quick brown fox jumped!","feature":"hello","submittedTs":"54124"}

____________

e) the spark application will then dump all this in a new kafka topic called topicB in a JSON format, exactly like the format is stored in topicA.

____________

f) spark application will be submitted with the following application arguments

master

kafka-bootstrap-server

input-kafka-topic

flask-server-port

kafka-group

output-kafka-topic

flask-server-endpoint

____________

So our spark-submit command will look like:

spark-submit --master <$master> --num-executors 2 --total-executor-cores 1 --executor-cores 1 --executor-memory 1g --driver-memory 1g --name my-spark-job --class [login to view URL] --queue default --deploy-mode cluster /home/ubuntu/[login to view URL] <$kafka-bootstrap-server> <$input-kafka-topic> <$flask-server-port> <$kafka-group> <$output-kafka-topic> <$flask-server-endpoint>

and with argument values filled in:

spark-submit --master yarn --num-executors 2 --total-executor-cores 1 --executor-cores 1 --executor-memory 1g --driver-memory 1g --name my-spark-job --class [login to view URL] --queue default --deploy-mode cluster /home/ubuntu/[login to view URL] [login to view URL] topicA 5001 kafka_group_1 topicB http://localhost/default/post/

I can give you the code for flask python app so you can help test it. It is attached with this ([login to view URL]) ticket. Run it with command: python [login to view URL]

- You can CURL it to test locally:

curl --header "Content-Type: application/json" --request POST --data '{"accountId":"111-222","submittedTs":"2000","source":"ABC","destination":"XYZ","content":"blablabla"}' localhost:5001/default/post/

Fähigkeiten: Skala, Spark, Apache Maven, Flask

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Über den Arbeitgeber:
( 1 Bewertung ) Hammersmith, United Kingdom

Projekt-ID: #25216609

Vergeben an:

mishraS83

working as an architect, good experience of spark , read you requirements, let's discuss more. would be happy to help

£128 GBP in 3 Tagen
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