[
https://issues.apache.org/jira/browse/FLINK-17178?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17327910#comment-17327910
]
Flink Jira Bot commented on FLINK-17178:
----------------------------------------
This major issue is unassigned and itself and all of its Sub-Tasks have not
been updated for 30 days. So, it has been labeled "stale-major". If this ticket
is indeed "major", please either assign yourself or give an update. Afterwards,
please remove the label. In 7 days the issue will be deprioritized.
> Provide "ALL" cache strategy in LookupFunction
> -----------------------------------------------
>
> Key: FLINK-17178
> URL: https://issues.apache.org/jira/browse/FLINK-17178
> Project: Flink
> Issue Type: New Feature
> Components: Connectors / Common
> Reporter: Lijie Wang
> Priority: Major
> Labels: stale-major
>
> We provide "ALL" cache strategy mentioned in FLINK-13252, motivation as
> follow:
> Maintain the entire dimension table in memory to improve performance. There
> is no IO overhead when we lookup the cached table. Reload dimension table
> periodically for update, and we can reload asynchronously with little IO
> delay.
> The cache needs to be reloaded periodically for update。
> Limitations：
> 1. It's suitable for scenario that users don't care the lateness so much,
> periodically updating can satisfy them.
> 2. The “ALL” cache needs more memory, so it's suitable for small dimension
> table.
--
This message was sent by Atlassian Jira
(v8.3.4#803005)
