* Add first efforts at broadcast
* Tidy
* Move broadcast code to client
* Progress with broadcast impl
* Rename to address change
* Fix compile errors
* Use `while` loop
* Tidy
* Flip broadcast condition
* Switch to forgetting individual indices
* Always broadcast when the node starts
* Refactor into two functions
* Add testing
* Add another test
* Tidy, add more testing
* Tidy
* Add test, rename enum
* Rename enum again
* Tidy
* Break loop early
* Add V15 schema migration
* Bump schema version
* Progress with migration
* Update beacon_node/client/src/address_change_broadcast.rs
Co-authored-by: Michael Sproul <micsproul@gmail.com>
* Fix typo in function name
---------
Co-authored-by: Michael Sproul <micsproul@gmail.com>
Currently there is a race between receiving blocks and receiving light client optimistic updates (in unstable), which results in processing errors. This is a continuation of PR #3693 and seeks to progress on issue #3651
Add the parent_root to ReprocessQueueMessage::BlockImported so we can remove blocks from queue when a block arrives that has the same parent root. We use the parent root as opposed to the block_root because the LightClientOptimisticUpdate does not contain the block_root.
If light_client_optimistic_update.attested_header.canonical_root() != head_block.message().parent_root() then we queue the update. Otherwise we process immediately.
michaelsproul came up with this idea.
The code was heavily based off of the attestation reprocessing.
I have not properly tested this to see if it works as intended.
* Import BLS to execution changes before Capella
* Test for BLS to execution change HTTP API
* Pack BLS to execution changes in LIFO order
* Remove unused var
* Clippy
We recently ran a large-block experiment on the testnet and plan to do a further experiment on mainnet.
Although the metrics recovered from lighthouse nodes were quite useful, I think we could do with greater resolution in the block delay metrics and get some specific values for each block (currently these can be lost to large exponential histogram buckets).
This PR increases the resolution of the block delay histogram buckets, but also introduces a new metric which records the last block delay. Depending on the polling resolution of the metric server, we can lose some block delay information, however it will always give us a specific value and we will not lose exact data based on poor resolution histogram buckets.
## Issue Addressed
Currently there is a race between receiving blocks and receiving light client optimistic updates (in unstable), which results in processing errors. This is a continuation of PR #3693 and seeks to progress on issue #3651
## Proposed Changes
Add the parent_root to ReprocessQueueMessage::BlockImported so we can remove blocks from queue when a block arrives that has the same parent root. We use the parent root as opposed to the block_root because the LightClientOptimisticUpdate does not contain the block_root.
If light_client_optimistic_update.attested_header.canonical_root() != head_block.message().parent_root() then we queue the update. Otherwise we process immediately.
## Additional Info
michaelsproul came up with this idea.
The code was heavily based off of the attestation reprocessing.
I have not properly tested this to see if it works as intended.
* Import BLS to execution changes before Capella
* Test for BLS to execution change HTTP API
* Pack BLS to execution changes in LIFO order
* Remove unused var
* Clippy
We recently ran a large-block experiment on the testnet and plan to do a further experiment on mainnet.
Although the metrics recovered from lighthouse nodes were quite useful, I think we could do with greater resolution in the block delay metrics and get some specific values for each block (currently these can be lost to large exponential histogram buckets).
This PR increases the resolution of the block delay histogram buckets, but also introduces a new metric which records the last block delay. Depending on the polling resolution of the metric server, we can lose some block delay information, however it will always give us a specific value and we will not lose exact data based on poor resolution histogram buckets.
