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https://issues.apache.org/jira/browse/SPARK-34309?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17279548#comment-17279548
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Yang Jie edited comment on SPARK-34309 at 2/5/21, 10:13 AM:
------------------------------------------------------------

[~dongjoon] I use the code in 
[GetPutBenchmark|https://github.com/ben-manes/caffeine/blob/master/caffeine/src/jmh/java/com/github/benmanes/caffeine/cache/GetPutBenchmark.java]
 to compare the performance of caffeine, guava cache, LinkedHashMap and 
ConcurrentLinkedHashMap, the result as follows:

# read write (6 threads read and 2 threads write):

 !screenshot-1.png! 

# read only (8 threads read):

 !image-2021-02-05-18-08-48-852.png! 

# write only (8 threads write):



was (Author: luciferyang):
[~dongjoon] I use the code in 
[GetPutBenchmark|https://github.com/ben-manes/caffeine/blob/master/caffeine/src/jmh/java/com/github/benmanes/caffeine/cache/GetPutBenchmark.java]
 to compare the performance of caffeine, guava cache, LinkedHashMap and 
ConcurrentLinkedHashMap, the result as follows:

# read write (6 read and 2 write):

 !screenshot-1.png! 

# read only

 !image-2021-02-05-18-08-48-852.png! 

> Use Caffeine instead of Guava Cache
> -----------------------------------
>
>                 Key: SPARK-34309
>                 URL: https://issues.apache.org/jira/browse/SPARK-34309
>             Project: Spark
>          Issue Type: Improvement
>          Components: Spark Core, SQL
>    Affects Versions: 3.2.0
>            Reporter: Yang Jie
>            Priority: Minor
>         Attachments: image-2021-02-05-18-08-48-852.png, screenshot-1.png
>
>
> Caffeine is a high performance, near optimal caching library based on Java 8, 
> it is used in a similar way to guava cache, but with better performance. The 
> comparison results are as follow are on the [caffeine benchmarks 
> |https://github.com/ben-manes/caffeine/wiki/Benchmarks]
> At the same time, caffeine has been used in some open source projects like 
> Cassandra, Hbase, Neo4j, Druid, Spring and so on.
>  



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