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12-11-2017
11:35 PM
Thanks for answering my original questions, but I have to revise my questions because of a coding issue. The new result is actually better. I list the original questions below for reference. Now, if running 6 unique queries concurrently take 4 seconds, is it a wrong expectation to think 50 concurrent queries (of the 6 unique queries) will return much faster than 13 seconds assuming all setup is correct, no IO issue, and it is truly concurrent? By default, the recommended concurrent queries is 4. (Why 4?) Also, is it possible to find out memory usage of each query?
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12-06-2017
10:15 PM
We have been testing LLAP concurrency for a couple months now. A little info on our test cluster below.
4 data nodes. Each node has 32 physical cores (2 vcores per) and 96GB memory. There is one LLAP queue with 50% Capacity and 50% Max Capacity.. Concurrent Queries = 50 2 Daemons & Number of executors per LLAP Daemon = 48 (1GB container) We can get results back pretty quick (under 2 seconds) below 12 concurrent queries. However, once it reaches 18 and above, we started seeing longer runtime and a lot of killed task attempts (see image). I believe it contributes to the longer rumtime. Is it enough info to figure out which configuration setup can avoid those killed tasks? HDP version 2.6 Thanks.
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Hortonworks Data Platform (HDP)