SPARK-1183. Don't use "worker" to mean executor

Author: Sandy Ryza <sandy@cloudera.com>

Closes #120 from sryza/sandy-spark-1183 and squashes the following commits:

5066a4a [Sandy Ryza] Remove "worker" in a couple comments
0bd1e46 [Sandy Ryza] Remove --am-class from usage
bfc8fe0 [Sandy Ryza] Remove am-class from doc and fix yarn-alpha
607539f [Sandy Ryza] Address review comments
74d087a [Sandy Ryza] SPARK-1183. Don't use "worker" to mean executor

1 files changed, 2 insertions, 2 deletions

diff --git a/docs/mllib-classification-regression.md b/docs/mllib-classification-regression.md
index 18a3e8e075..d5bd8042ca 100644
--- a/docs/mllib-classification-regression.md
+++ b/docs/mllib-classification-regression.md
@@ -77,8 +77,8 @@ between the two goals of small loss and small model complexity.
 
 **Distributed Datasets.**
 For all currently implemented optimization methods for classification, the data must be
-distributed between the worker machines *by examples*. Every machine holds a consecutive block of
-the `$n$` example/label pairs `$(\x_i,y_i)$`. 
+distributed between processes on the worker machines *by examples*. Machines hold consecutive
+blocks of the `$n$` example/label pairs `$(\x_i,y_i)$`. 
 In other words, the input distributed dataset
 ([RDD](scala-programming-guide.html#resilient-distributed-datasets-rdds)) must be the set of
 vectors `$\x_i\in\R^d$`.