Let's take for example a set of 12 compute nodes with an aggregate memory of *1.2TiB*, we need to do following settings for optimal results. Add the following optimal entries for _core-site.xml_ to configure _s3a_ with **MinIO**. Most important options here are
mapreduce.fileoutputcommitter.algorithm.version=2 # Use the latest committer version
mapreduce.job.reduce.slowstart.completedmaps=0.99 # 99% map, then reduce
mapreduce.reduce.shuffle.input.buffer.percent=0.9 # Min % buffer in RAM
mapreduce.reduce.shuffle.merge.percent=0.9 # Minimum % merges in RAM
mapreduce.reduce.speculative=false # Disable speculation for reducing
mapreduce.task.io.sort.factor=999 # Threshold before writing to disk
mapreduce.task.sort.spill.percent=0.9 # Minimum % before spilling to disk
```
S3A is the connector to use S3 and other S3-compatible object stores such as MinIO. MapReduce workloads typically interact with object stores in the same way they do with HDFS. These workloads rely on HDFS atomic rename functionality to complete writing data to the datastore. Object storage operations are atomic by nature and they do not require/implement rename API. The default S3A committer emulates renames through copy and delete APIs. This interaction pattern causes significant loss of performance because of the write amplification. *Netflix*, for example, developed two new staging committers - the Directory staging committer and the Partitioned staging committer - to take full advantage of native object storage operations. These committers do not require rename operation. The two staging committers were evaluated, along with another new addition called the Magic committer for benchmarking.
It was found that the directory staging committer was the fastest among the three, S3A connector should be configured with the following parameters for optimal results:
For more information about these options please visit [https://www.cloudera.com/documentation/enterprise/5-11-x/topics/admin_hive_on_s3_tuning.html](https://www.cloudera.com/documentation/enterprise/5-11-x/topics/admin_hive_on_s3_tuning.html)