Hi I would like to make a dump of the database, in JSON format, to KAFKA The database contains lots of data, millions and in some cases billions of “rows” I will provide the customer with an export of the data, where they can read it off of a KAFKA topic
My thinking was to have it scalable such that I will distribute the token range of all available partition-keys to a number of (N) processes (JSON-Producers) First I will have a process which will read through the available tokens and then publish them on a KAFKA “Coordinator” Topic And then I can create 1, 10, 20 or N processes that will act as Producers to the real KAFKA topic, and pick available tokens/partition-keys off of the “Coordinator” Topic One by one until all the “rows” have been processed. So the JOSN-Producer will take e.g. a range of 1000 “rows” and convert them into my own JSON format and post to KAFKA And then after that take another 1000 “rows” and then …. And then another 1000 “rows” and so on, until it is done. I base my idea on how I believe Apache Spark Connector accomplishes data locality, i.e. being aware of where tokens reside and figured that since that is possible it should be possible to create a job-list in a KAFKA topic, and have each Producer pick jobs from there, and read up data from Cassandra based on the partition key (token) and then post the JSON on the export KAFKA topic. https://dzone.com/articles/data-locality-w-cassandra-how Would you consider this a good idea ? Would there in fact be a better idea, what would that be then ? -Tobias