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ui: graphs don't load on 240 node cluster #72986
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cc @nkodali assigned to our team label for triage and discussion in next Mondays' backlog grooming session |
Confirming that this is in our December milestone |
(sorry repeat comment since I accidentally made it in Jira) @nvanbenschoten have you considered running Prometheus alongside these clusters instead of using DB Console for timeseries metrics? That could alleviate this directly. I do want to tackle this issue but Prometheus will likely work for you immediately. We have a demo configuration with matching dashboards from DB Console under I am still going ahead with a proposed solution but just wanted to throw out the workaround above. Some large customers will hit this limit at some point soonish so I definitely want to address it directly. I like the idea of using an existing memory limit like system-wide or |
Previously, the memory limit per-`tsdb` worker was set at a static 64MiB. This cap created issues seen in cockroachdb#24018 where this limit was hit on a 30 node cluster. To alleviate the issue, the number of workers was reduced. We've currently hit this limit again as part of load testing with larger clusters and have decided to make the per-query worker memory limit dynamic. The per-worker limit is now raised based on the amount of memory available to the SQL Pool via the `MemoryPoolSize` configuration variable. This is set to be 25% of the system memory by default. The `tsdb` memory cap per-worker is now doubled until it reaches `1/128` of the memory pool setting. For example, on a node with 128 - 256 GiB of memory, this will correspond to 512 MiB allocated per worker. TODO(davidh): Can the tests be faster? They iterate on a server create TODO(davidh): Is 1/128 a good setting? How do we validate this. TODO(davidh): Should this behavior be gated behind a feature flag? It's possible on some memory-constrained deployments a sudden spike in memory usage by tsdb could cause problems. Resolves cockroachdb#72986 Release note (ops change): customers running clusters with 240 nodes or more can effectively access tsdb metrics.
This is a good point. I was planning to run with a patched version of CRDB with a higher |
Previously, the memory limit for all `tsdb` workers was set at a static 64MiB. This cap created issues seen in cockroachdb#24018 where this limit was hit on a 30 node cluster. To alleviate the issue, the number of workers was reduced, raising the per-worker allocation. We've currently hit this limit again as part of load testing with larger clusters and have decided to make the per-query worker memory limit dynamic. The per-worker limit is now raised based on the amount of memory available to the SQL Pool via the `MemoryPoolSize` configuration variable. This is set to be 25% of the system memory by default. The `tsdb` memory cap per-worker is now doubled until it reaches `1/128` of the memory pool setting. For example, on a node with 128 - 256 GiB of memory, this will correspond to 512 MiB allocated for all running `tsdb` queries. In addition, the ts server is now connected to the same `BytesMonitor` instance as the SQL memory monitor and workers will becapped at double the query limit. Results are monitored as before but a cap is not introduced there since we didn't have one present previously. This behavior is gated behind a private cluster setting that's enabled by default. TODO(davidh): Can the tests be faster? They iterate on a server create TODO(davidh): Is 1/128 a good setting? How do we validate this. Resolves cockroachdb#72986 Release note (ops change): customers running clusters with 240 nodes or more can effectively access tsdb metrics.
Previously, the memory limit for all `tsdb` workers was set at a static 64MiB. This cap created issues seen in cockroachdb#24018 where this limit was hit on a 30 node cluster. To alleviate the issue, the number of workers was reduced, raising the per-worker allocation. We've currently hit this limit again as part of load testing with larger clusters and have decided to make the per-query worker memory limit dynamic. The per-worker limit is now raised based on the amount of memory available to the SQL Pool via the `MemoryPoolSize` configuration variable. This is set to be 25% of the system memory by default. The `tsdb` memory cap per-worker is now doubled until it reaches `1/128` of the memory pool setting. For example, on a node with 128 - 256 GiB of memory, this will correspond to 512 MiB allocated for all running `tsdb` queries. In addition, the ts server is now connected to the same `BytesMonitor` instance as the SQL memory monitor and workers will becapped at double the query limit. Results are monitored as before but a cap is not introduced there since we didn't have one present previously. This behavior is gated behind a private cluster setting that's enabled by default and sets the ratio at 1/128 of the SQL memory pool. Resolves cockroachdb#72986 Release note (ops change): customers running clusters with 240 nodes or more can effectively access tsdb metrics.
Previously, the memory limit for all `tsdb` workers was set at a static 64MiB. This cap created issues seen in cockroachdb#24018 where this limit was hit on a 30 node cluster. To alleviate the issue, the number of workers was reduced, raising the per-worker allocation. We've currently hit this limit again as part of load testing with larger clusters and have decided to make the per-query worker memory limit dynamic. The per-worker limit is now raised based on the amount of memory available to the SQL Pool via the `MemoryPoolSize` configuration variable. This is set to be 25% of the system memory by default. The `tsdb` memory cap per-worker is now doubled until it reaches `1/128` of the memory pool setting. For example, on a node with 128 - 256 GiB of memory, this will correspond to 512 MiB allocated for all running `tsdb` queries. In addition, the ts server is now connected to the same `BytesMonitor` instance as the SQL memory monitor and workers will becapped at double the query limit. Results are monitored as before but a cap is not introduced there since we didn't have one present previously. This behavior is gated behind a private cluster setting that's enabled by default and sets the ratio at 1/128 of the SQL memory pool. Resolves cockroachdb#72986 Release note (ops change): customers running clusters with 240 nodes or more can effectively access tsdb metrics.
74563: kv,kvcoord,sql: poison txnCoordSender after a retryable error r=lidorcarmel a=lidorcarmel Previously kv users could lose parts of a transaction without getting an error. After Send() returned a retryable error the state of txn got reset which made it usable again. If the caller ignored the error they could continue applying more operations without realizing the first part of the transaction was discarded. See more details in the issue (#22615). The simple case example is where the retryable closure of DB.Txn() returns nil instead of returning the retryable error back to the retry loop - in this case the retry loop declares success without realizing we lost the first part of the transaction (all the operations before the retryable error). This PR leaves the txn in a "poisoned" state after encountering an error, so that all future operations fail fast. The caller is therefore expected to reset the txn handle back to a usable state intentionally, by calling Txn.PrepareForRetry(). In the simple case of DB.Txn() the retry loop will reset the handle and run the retry even if the callback returned nil. Closes #22615 Release note: None 74662: tsdb: expand mem per worker based on sql pool size r=dhartunian a=dhartunian Previously, the memory limit for all `tsdb` workers was set at a static 64MiB. This cap created issues seen in #24018 where this limit was hit on a 30 node cluster. To alleviate the issue, the number of workers was reduced, raising the per-worker allocation. We've currently hit this limit again as part of load testing with larger clusters and have decided to make the per-query worker memory limit dynamic. The per-worker limit is now raised based on the amount of memory available to the SQL Pool via the `MemoryPoolSize` configuration variable. This is set to be 25% of the system memory by default. The `tsdb` memory cap per-worker is now doubled until it reaches `1/128` of the memory pool setting. For example, on a node with 128 - 256 GiB of memory, this will correspond to 512 MiB allocated for all running `tsdb` queries. In addition, the ts server is now connected to the same `BytesMonitor` instance as the SQL memory monitor and workers will becapped at double the query limit. Results are monitored as before but a cap is not introduced there since we didn't have one present previously. This behavior is gated behind a private cluster setting that's enabled by default and sets the ratio at 1/128 of the SQL memory pool. Resolves #72986 Release note (ops change): customers running clusters with 240 nodes or more can effectively access tsdb metrics. 75677: randgen: add PopulateRandTable r=mgartner a=msbutler PopulateRandTable populates the caller's table with random data. This helper function aims to make it easier for engineers to develop randomized tests that leverage randgen / sqlsmith. Informs #72345 Release note: None 76334: opt: fix missing filters after join reordering r=mgartner a=mgartner #### opt: add TES, SES, and rules to reorderjoins This commit updates the output of the `reorderjoins` opt test command to display the initial state of the `JoinOrderBuilder`. It adds additional information to the output including the TES, SES, and conflict rules for each edge. Release note: None #### opt: fix missing filters after join reordering This commit eliminates logic in the `assoc`, `leftAsscom`, and `rightAsscom` functions in the join order builder that aimed to prevent generating "orphaned" predicates, where one or more referenced relations are not in a join's input. In rare cases, this logic had the side effect of creating invalid conflict rules for edges, which could prevent valid predicates from being added to reordered join trees. It is safe to remove these conditionals because they are unnecessary. The CD-C algorithm already prevents generation of orphaned predicates by checking that the total eligibility set (TES) is a subset of a join's input vertices. In our implementation, this is handled by the `checkNonInnerJoin` and `checkInnerJoin` functions. Fixes #76522 Release note (bug fix): A bug has been fixed which caused the query optimizer to omit join filters in rare cases when reordering joins, which could result in incorrect query results. This bug was present since v20.2. Co-authored-by: Lidor Carmel <lidor@cockroachlabs.com> Co-authored-by: David Hartunian <davidh@cockroachlabs.com> Co-authored-by: Michael Butler <butler@cockroachlabs.com> Co-authored-by: Marcus Gartner <marcus@cockroachlabs.com>
Previously, the memory limit for all `tsdb` workers was set at a static 64MiB. This cap created issues seen in cockroachdb#24018 where this limit was hit on a 30 node cluster. To alleviate the issue, the number of workers was reduced, raising the per-worker allocation. We've currently hit this limit again as part of load testing with larger clusters and have decided to make the per-query worker memory limit dynamic. This PR introduces a new CLI flag `--max-tsdb-memory` to mirror the functionality of the `--max-sql-memory` flag by accepting bytes or a percentage of system memory. The default is set to be `1%` of system memory or 64 MiB, whichever is greater. This ensures that performance after this PR is equal or better for timeseries queries without eating too far into memory budgets for SQL. In addition, the ts server is now connected to the same `BytesMonitor` instance as the SQL memory monitor and workers will becapped at double the query limit. Results are monitored as before but a cap is not introduced there since we didn't have one present previously. Resolves cockroachdb#72986 Release note (cli change, ops change): A new CLI flag `--max-tsdb-memory` is now available, that can set the memory budget for timeseries queries when processing requests from the Metrics page in DB Console. Most customers should not need to tweak this setting as the default of 1% of system memory or 64 MiB, whichever is greater, is adequate for most deployments. In the case where a deployment of hundreds of nodes has low per-node memory available (below 8 GiB for instance) it may be necessary to increase this value to `2%` or higher in order to render timeseries graphs for the cluster using the DB Console. Otherwise, the default settings will be adequate for the vast majority of deployments.
This is identical to #24018, only at a larger scale. We resolved that issue by dropping down the number of query workers by a factor of 8. This increased the per timeseries query memory limit from 1MiB to 8MiB. It should come as no surprise then that we once again see this issue on 240 node clusters (given
30*8=240
).@mrtracy laid out a few options on that issue #24018 (comment). I think we should explore the first one - "Raise the overall limit (currently 64MiB)". Specifically, I think it would make sense to scale this server-wide limit by the available memory on the machine. On a machine with 100s of GiB of available memory (e.g.
n2-standard-48
machines have 192 GiB of memory), 64MiB isn't much. Or instead of a static limit, we should hook this memory budget into the--max-sql-memory
budget.cc. @piyush-singh
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