HeartSaVioR commented on a change in pull request #23743: [SPARK-26843][MESOS]
Use ConfigEntry for hardcoded configs for "mesos" resource manager
URL: https://github.com/apache/spark/pull/23743#discussion_r255358549
##########
File path:
resource-managers/mesos/src/test/scala/org/apache/spark/scheduler/cluster/mesos/MesosFineGrainedSchedulerBackendSuite.scala
##########
@@ -80,9 +81,9 @@ class MesosFineGrainedSchedulerBackendSuite
}
test("Use configured mesosExecutor.cores for ExecutorInfo") {
- val mesosExecutorCores = 3
+ val mesosExecutorCores = 3.0
Review comment:
I'm honestly not a expert on this but the documentation of
`spark.mesos.mesosExecutor.cores` clarify that it can receive floating point
number so the type still makes sense.
https://github.com/apache/spark/blob/master/docs/running-on-mesos.md
```
<tr>
<td><code>spark.mesos.mesosExecutor.cores</code></td>
<td><code>1.0</code></td>
<td>
(Fine-grained mode only) Number of cores to give each Mesos executor.
This does not
include the cores used to run the Spark tasks. In other words, even if
no Spark task
is being run, each Mesos executor will occupy the number of cores
configured here.
The value can be a floating point number.
</td>
</tr>
```
The default value is also explained as `1.0` instead of 1. I'll update the
config entry to reflect the sync.
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