diff options
author | Reynold Xin <rxin@databricks.com> | 2016-02-26 22:35:12 -0800 |
---|---|---|
committer | Reynold Xin <rxin@databricks.com> | 2016-02-26 22:35:12 -0800 |
commit | 59e3e10be2f9a1c53979ca72c038adb4fa17ca64 (patch) | |
tree | 3d6b2246738484273d36d0ccbec66b733930a3e0 /docs/job-scheduling.md | |
parent | f77dc4e1e202942aa8393fb5d8f492863973fe17 (diff) | |
download | spark-59e3e10be2f9a1c53979ca72c038adb4fa17ca64.tar.gz spark-59e3e10be2f9a1c53979ca72c038adb4fa17ca64.tar.bz2 spark-59e3e10be2f9a1c53979ca72c038adb4fa17ca64.zip |
[SPARK-13521][BUILD] Remove reference to Tachyon in cluster & release scripts
## What changes were proposed in this pull request?
We provide a very limited set of cluster management script in Spark for Tachyon, although Tachyon itself provides a much better version of it. Given now Spark users can simply use Tachyon as a normal file system and does not require extensive configurations, we can remove this management capabilities to simplify Spark bash scripts.
Note that this also reduces coupling between a 3rd party external system and Spark's release scripts, and would eliminate possibility for failures such as Tachyon being renamed or the tar balls being relocated.
## How was this patch tested?
N/A
Author: Reynold Xin <rxin@databricks.com>
Closes #11400 from rxin/release-script.
Diffstat (limited to 'docs/job-scheduling.md')
-rw-r--r-- | docs/job-scheduling.md | 3 |
1 files changed, 1 insertions, 2 deletions
diff --git a/docs/job-scheduling.md b/docs/job-scheduling.md index 95d47794ea..00b6a18836 100644 --- a/docs/job-scheduling.md +++ b/docs/job-scheduling.md @@ -54,8 +54,7 @@ an application to gain back cores on one node when it has work to do. To use thi Note that none of the modes currently provide memory sharing across applications. If you would like to share data this way, we recommend running a single server application that can serve multiple requests by querying -the same RDDs. In future releases, in-memory storage systems such as [Tachyon](http://tachyon-project.org) will -provide another approach to share RDDs. +the same RDDs. ## Dynamic Resource Allocation |