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https://issues.apache.org/jira/browse/CASSANDRA-15026?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Roee Zilkha updated CASSANDRA-15026:
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Description:
Currently, Cassandra will open each and every sstable file (I assume for
pulling its metadata and create initial in-memory mapping to persisted data),
when there are large amount of keyspaces and tables, this will cause a major
overhead when restarting a node.
In our use case, many keyspaces are rarely accessed and we would prefer that
their initialization will be invoked lazily and not on startup, thereby
reducing the time it takes a node to start serving clients.
* Slack Conversation attached
was:
Currently, Cassandra will open each and every sstable file (I assume for
pulling its metadata and create initial in-memory mapping to persisted data
blocks), when there are large amount of keyspaces and tables, this will cause a
major overhead when restarting a node.
In our use case, many keyspaces are rarely accessed and we would prefer that
their initialization will be invoked lazily and not on startup, thereby
reducing the time it takes a node to start serving clients.
* Slack Conversation attached
> Lazy initialization for lower latency on startup
> ------------------------------------------------
>
> Key: CASSANDRA-15026
> URL: https://issues.apache.org/jira/browse/CASSANDRA-15026
> Project: Cassandra
> Issue Type: Improvement
> Components: Local/Startup and Shutdown
> Reporter: Roee Zilkha
> Priority: Minor
> Attachments: discussion.png
>
>
> Currently, Cassandra will open each and every sstable file (I assume for
> pulling its metadata and create initial in-memory mapping to persisted data),
> when there are large amount of keyspaces and tables, this will cause a major
> overhead when restarting a node.
>
> In our use case, many keyspaces are rarely accessed and we would prefer that
> their initialization will be invoked lazily and not on startup, thereby
> reducing the time it takes a node to start serving clients.
>
> * Slack Conversation attached
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