[#2544] fix(client): NPE about StatisticsCodec

[SalvadorRomo]

What changes were proposed in this pull request?

Converting List<codeCost> into a synchronize list

Why are the changes needed?

this bugs happened in concurrent environment when spark workers with the RssShuffleManager and spark.rss.client.io.compression.statisticsEnabled property enabled, logs its compression statistics when finished, but since the class was not prepared for concurrent enviroment, at the time to call List<codeCost> into the codec.statistics() methods enters in a race condition.

Fix: # 2544

Does this PR introduce any user-facing change?

No.

How was this patch tested?

this issue was diffcult to replicate into a local enviroment, but instead when the patch was applied, i make sure the application continue working as usual by:
1- deploying the application based on ./deploy/docker/read.me
2- when executing the spark-shell make sure to do it by including the spark.rss.client.io.compression.statisticsEnabled props as follow:

docker exec -it rss-spark-master-1 /opt/spark/bin/spark-shell \
   --master spark://rss-spark-master-1:7077 \
   --conf spark.serializer=org.apache.spark.serializer.KryoSerializer \
   --conf spark.shuffle.manager=org.apache.spark.shuffle.RssShuffleManager \
   --conf spark.rss.coordinator.quorum=rss-coordinator-1:19999,rss-coordinator-2:19999 \
   --conf spark.rss.storage.type=MEMORY_LOCALFILE \
   --conf spark.speculation=true \
   --conf spark.rss.client.io.compression.statisticsEnabled=true

3- run multipe spark scala jobs
4- when finishing, into each worker, look for the logs in /opt/spark/work/...
5- looks for every entry in the file that succesfully logs the statistics.

[github-actions]

Test Results

 3 082 files  ±0   3 082 suites  ±0   6h 48m 37s ⏱️ -26s
 1 191 tests ±0   1 190 ✅ +1   1 💤 ±0  0 ❌  - 1 
15 100 runs  ±0  15 085 ✅ +1  15 💤 ±0  0 ❌  - 1 

Results for commit 6e48950. ± Comparison against base commit f1323ab.

♻️ This comment has been updated with latest results.

[zuston]

Sorry for the late reply, that I'm busy for working.

This PR looks good to me. And I will validate this in our production cluster. Thanks for your contribution! @SalvadorRomo

Welcome to the uniffle community! 🎉

[zuston]

And you could format your code by the following command

mvn spotless:apply -Pspark3 -Pspark2 -Ptez -Pmr -Phadoop2.8

[zuston]

Merged @SalvadorRomo . Thanks again