You don't need a CS degree to work in this field (I don't have one either!) but there are fundamental concepts you need to understand in order to make informed decisions when designing distributed systems.
- a language for specifying data transformations, and
- an engine to compile programs written in that language into mapreduce jobs to execute on a hadoop cluster
it was designed to easily map some common functional and SQL idioms (e.g. filter, group by w/ aggregation functions) to parallel execution for processing huge amounts of data.
Impala is another big data project that is an engine for planning and executing SQL on data stored in a hadoop cluster.
Zookeeper is... black magic??
Same - was it the comment saying nobody chooses Kafka anymore? I was surprised by it.
These people seem to be invested (quite literally) in Pulsar disrupting Kafka's position in the pub/sub & event streaming space. This isn't to say Pulsar can't someday be superior, though. Time will tell. But Kafka has such a massive lead and it fits the needs for most people who need to do data integration that I don't see the need for everyone to uproot their solutions in favor of Pulsar.
But almost everyone has heard of GNU/Linux or Apple OSX.
Event driven concurrent framework for Python https://github.com/quantmind/pulsar