Smart Partitioning with Apache Apex

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Processing big data often requires running the same computations parallelly in multiple processes or threads, called partitions, with each partition handling a subset of the data. This becomes all the more necessary when processing live data streams where maintaining SLA is paramount. Furthermore, multiple different computations make up an application and each of them may have different partitioning needs. Partitioning also needs to adapt to changing data rates, input sources and other application requirements like SLA.