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https://issues.apache.org/jira/browse/SPARK-9588?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Shenghu Yang updated SPARK-9588:
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Description:
In spark 1.4, we can only do 'cache table <table_name>'. However, if we have
table which will get a new partition periodically, say every 10 minutes, we
have to do 'uncache' & then 'cache' the whole table, taking long time.
Things would be much faster if we can do:
(1) cache table <table_name> partition <newest_partition>
(2) uncache table <table_name> partition <oldest_partition>
This way we will alway have a sliding window type of cached data.
was:
In spark 1.4, we can only do 'cache table <table_name>'. However, if we have
table which will get a new partition periodically, say every 10 minutes, we
have to do 'uncache' & then 'cache' the whole table, taking long time.
Things would be much faster if we can do:
(1) cache table <table_name> partition <newest_partition>
(2) uncache table <table_name> partition <oldest_partition>
This way we can always having a sliding window type of cached data.
> spark sql cache: partition level cache eviction
> -----------------------------------------------
>
> Key: SPARK-9588
> URL: https://issues.apache.org/jira/browse/SPARK-9588
> Project: Spark
> Issue Type: Improvement
> Reporter: Shenghu Yang
>
> In spark 1.4, we can only do 'cache table <table_name>'. However, if we have
> table which will get a new partition periodically, say every 10 minutes, we
> have to do 'uncache' & then 'cache' the whole table, taking long time.
> Things would be much faster if we can do:
> (1) cache table <table_name> partition <newest_partition>
> (2) uncache table <table_name> partition <oldest_partition>
> This way we will alway have a sliding window type of cached data.
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