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Diffstat (limited to 'docs/job-scheduling.md')
| -rw-r--r-- | docs/job-scheduling.md | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/docs/job-scheduling.md b/docs/job-scheduling.md index d304c5497b..dbcb9ae343 100644 --- a/docs/job-scheduling.md +++ b/docs/job-scheduling.md @@ -91,7 +91,7 @@ The fair scheduler also supports grouping jobs into _pools_, and setting differe (e.g. weight) for each pool. This can be useful to create a "high-priority" pool for more important jobs, for example, or to group the jobs of each user together and give _users_ equal shares regardless of how many concurrent jobs they have instead of giving _jobs_ equal shares. This approach is modeled after the -[Hadoop Fair Scheduler](http://hadoop.apache.org/docs/stable/fair_scheduler.html). +[Hadoop Fair Scheduler](http://hadoop.apache.org/docs/current/hadoop-yarn/hadoop-yarn-site/FairScheduler.html). Without any intervention, newly submitted jobs go into a _default pool_, but jobs' pools can be set by adding the `spark.scheduler.pool` "local property" to the SparkContext in the thread that's submitting them. |