THIS IS A TEST INSTANCE. ALL YOUR CHANGES WILL BE LOST!!!!
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- The daemons are optional. Hive can work without them and also is able to bypass them even if they are deployed and operational. Feature parity with regard to language features is maintained.
- External orchestration and execution engines. LLAP is not an execution engine (like MapReduce or Tez). Overall execution is scheduled and monitored by an existing Hive execution engine (such as Tez) transparently over both LLAP nodes, as well as regular containers. Obviously, LLAP level of support depends on each individual execution engine (starting with Tez). MapReduce support is not planned, but other engines may be added later. Other frameworks like Pig also have the choice of using LLAP daemons.
- Partial execution. The result of the work performed by an LLAP daemon can either form part of the result of a Hive query, or be passed on to external Hive tasks, depending on the query.
Resource Management. YARN remains responsible for the management and allocation of resources. The YARN container delegation model is used to allow the transfer of allocated resources to LLAP. To avoid the limitations of JVM memory settings, cached data is kept off-heap, as well as large buffers for processing (e.g., group by, joins). This way, the daemon can use a small amount of memory, and additional resources (i.e., CPU and memory) will be assigned based on workload.Anchor Resource management Resource management
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Hive Contributor Meetup Presentation