fd6877c654
This series fixes one cause of oversized allocations - and therefore potentially stalls and increased tail latencies - in Alternator.
The first patch in the series is the main fix - the later patches are cleanups requested by reviewers but also involved other pre-existing code, so I did those cleanups as separate patches.
Alternator's Scan or Query operation return a page of results. When the number of items is not limited by a "Limit" parameter, the default is to return a 1 MB page. If items are short, a large number of them can fit in that 1MB. The test test_query.py::test_query_large_page_small_rows has 30,000 items returned in a single page.
In the response JSON, all these items are returned in a single array "Items". Before this patch, we build the full response as a RapidJSON object before sending it. The problem is that unfortunately, RapidJSON stores arrays as contiguous allocations. This results in large contiguous allocations in workloads that scan many small items, and large contiguous allocations can also cause stalls and high tail latencies. For example, before this patch, running
test/alternator/run --runveryslow \
test_query.py::test_query_large_page_small_rows
reports in the log:
oversized allocation: 573440 bytes.
After this patch, this warning no longer appears.
The patch solves the problem by collecting the scanned items not in a RapidJSON array, but rather in a chunked_vector<rjson::value>, i.e, a chunked (non-contiguous) array of items (each a JSON value). After collecting this array separately from the response object, we need to print its content without actually inserting it into the object - we add a new function print_with_extra_array() to do that.
The new separate-chunked-vector technique is used when a large number (currently, >256) of items were scanned. When there is a smaller number of items in a page (this is typical when each item is longer), we just insert those items in the object and print it as before.
Beyond the original slow test that demonstrated the oversized allocation (which is now gone), this patch also includes a new test which exercises the new code with a scan of 700 (>256) items in a page - but this new test is fast enough to be permanently in our test suite and not a manual "veryslow" test as the other test.
Fixes #23535
The stalls caused by large allocations was seen by actual users, so it makes sense to backport this patch. On the other hand, the patch while not big is fairly intrusive (modifies the nomal Scan and Query path and also the later patches do some cleanup of additional code) so there is some small risk involved in the backport.
Closes scylladb/scylladb#24480
* github.com:scylladb/scylladb:
alternator: clean up by co-routinizing
alternator: avoid spamming the log when failing to write response
alternator: clean up and simplify request_return_type
alternator: avoid oversized allocation in Query/Scan
Scylla in-source tests.
For details on how to run the tests, see docs/dev/testing.md
Shared C++ utils, libraries are in lib/, for Python - pylib/
alternator - Python tests which connect to a single server and use the DynamoDB API unit, boost, raft - unit tests in C++ cqlpy - Python tests which connect to a single server and use CQL topology* - tests that set up clusters and add/remove nodes cql - approval tests that use CQL and pre-recorded output rest_api - tests for Scylla REST API Port 9000 scylla-gdb - tests for scylla-gdb.py helper script nodetool - tests for C++ implementation of nodetool
If you can use an existing folder, consider adding your test to it. New folders should be used for new large categories/subsystems, or when the test environment is significantly different from some existing suite, e.g. you plan to start scylladb with different configuration, and you intend to add many tests and would like them to reuse an existing Scylla cluster (clusters can be reused for tests within the same folder).
To add a new folder, create a new directory, and then
copy & edit its suite.ini.