GitHub user paul-rogers opened a pull request:
https://github.com/apache/drill/pull/958
DRILL-5808: Reduce memory allocator strictness for "managed" operators
The "managed" external sort and the hash agg operators now actively attempt
to stay within a memory "budget."
Out goals are to:
1. Stay within the budget, and
2. Make full use of the available memory.
Unfortunately, at present, Drill has a number of limitations that work at
cross-purposes to the above goal.
* Upstream operators create record batches potentially larger than the
memory budget.
* Memory allocations are "lumpy" - power of two rounded.
* Vectors double in size automatically when needed.
The combination of the above means that memory planning must be aware of
the size of each and every vector to the byte level in order to predict size
doubling and power-of-two rounding.
But, of course, Drill is schema-on-read, meaning that Drill cannot know
ahead of time the "shape" of the data it will process. Without that
information, memory estimates are, at best, averages, but actual allocations
have a wide variance around those averages.
Add to this Drill's memory allocation scheme: each operator is given a
strict budget enforced by the memory allocator. Go above the budget by a single
byte and the query dies.
How do we resolve this conflict? On the one hand, Drill's internals are
rough-and-ready; it is impossible to predict actual memory usage. On the other
hand, the allocator requires perfect prediction else the user suffers with
failed queries.
Much work is needed in Drill internals to provide for better memory
management. (Relational databases have long ago solved the issues, so solutions
are available.) Until then, this commit introduces a work-around.
Memory-managed operators can ask for "leniency" from the allocator. In this
mode, the allocator:
* Allows actual memory use to spike up to 100% of the limit, or 100 MB,
whichever is less,
* Logs each such "excess allocation" as a warning, so we can identify and
fix issues, and
* Allows leniency only in production environments, but not during
development or test.
That is, we give users a margin for error so that their queries succeed
even if Drill's memory calculations don't come out exactly right.
This should be fine because, of course, Drill still has several operators
that observe no memory limits at all. Seems silly to have one operator using
GBs of memory, while enforcing a typical 30 MB limit on others.
Until all operators are memory managed, and Drill provides better memory
management tools, this PR allows queries to succeed even if we get things
slightly wrong internally.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/paul-rogers/drill DRILL-5808
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/drill/pull/958.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #958
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commit a9c5083b8743efa2b5c74fee77e12d8f69258601
Author: Paul Rogers <[email protected]>
Date: 2017-09-24T19:51:43Z
DRILL-5808: Reduce memory allocator strictness for "managed" operators
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