When writing to some tables with materialized views, we need to read from the base table first to perform a delete of the old view row. When doing so, the memory used for the read is tracked by the user read concurrency semaphore. When we have a large number of such reads, we may use up all of the semaphore units, causing the following reads to be queued. When we have some user reads coming at the same time, these reads can have very high latency due to the write workload on the base table. We want to avoid this, so that the write workload doesn't have a high impact on the latency of the read workload.
This is fixed in this patch by adding a separate read concurrency semaphore just for view update read-before-writes. With the new semaphore, even if there are many view update read-before-writes, they will be queued on a different semaphore than the user reads, and they won't impact their latency.
The second issue fixed by this patch is the concurrency of the view updates that is currently unlimited. Because of that view updates may take up so much memory that they we may run out of memory.
This is fixed by using the read admission on the view update concurrency semaphore.
This limits the number of concurrent view update reads to
max_count_concurrent_view_update_reads, all other incoming view update reads are
queued using just a small chunk of memory. Without this, the reads would also get
queued after exceeding view_update_reader_concurrency_semaphore_serialize_limit_multiplier, but they would take much more memory while staying in the queue.
The new semaphore has half the capacity of the regular user read concurrency semahpore and is currently used only for user writes - is't used independently of the scheduling group on which we base the read semaphore selection, but we use a different code path for streaming (not database::do_apply) and we shouldn't have view updates in system writes or during compaction.
This patch also adds a test to confirm that the view update workload doesn't impact the read latency, as well as a test which confirms that we do not run out of memory even under heavy view udpate workload.
The issue of view updates causing increased latencies most often occurs in the following scenario:
* we have a medium to high write workload to a table with a materialized view which requires reading from the base table before sending the update to delete the old rows
* we have any read workload
* one replica is slower or is handling more writes due to an imbalance of data distribution
* we write with a cl<ALL, the mentioned replica is replying to write requests slower while new ones keep being sent to it.
* each write performs a read first taking resources from the user read concurrency semaphore, so when enough writes accumulate the reads using the semaphore start getting queued
* the queue is shared by regular reads and view update reads. When there's enough view update reads in the queue, regular reads start getting increased latencies
An sct test (perf-regression-latency-mv-read-concurrency) was prepared to somewhat resemble this scenario:
* the tables were prepared satisfying the conditions above
* we use a medium write workload and a very low read workload
* the imbalance is achieved by writing to just a few (10) partitions - some replicas (and shards) can have twice or more used partitions than others. We also keep writing to a limited (though high) number of rows, to cause overwrites which require reading before sending the view update
* to minimize the test case, we use a cluster of 3 nodes and rf=2, we write with cl=ONE to have background replica writes and read with cl=ALL to wait for the slower replica to respond.
In the test above:
* without the fix, the latency of reads increases over 50s
* with the fix, the latency of reads stays below 20ms
Fixes https://github.com/scylladb/scylladb/issues/8873
Fixes https://github.com/scylladb/scylladb/issues/15805
The patch is not that small and it isn't fixing a regression, so no backports
Closesscylladb/scylladb#20887
* github.com:scylladb/scylladb:
test: add test for high view update concurrency causing bad_allocs
test: add test for high view update concurrency degrading read latency
mv: add a dedicated read concurrency semaphore for view update read before writes