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Posted to commits@spark.apache.org by sr...@apache.org on 2015/09/08 15:36:44 UTC
spark git commit: [DOC] Added R to the list of languages with "high-level API" support in the…
Repository: spark
Updated Branches:
refs/heads/master 5ffe752b5 -> 9d8e838d8
[DOC] Added R to the list of languages with "high-level API" support in the…
… main README.
Author: Stephen Hopper <sh...@shopper-osx.local>
Closes #8646 from enragedginger/master.
Project: http://git-wip-us.apache.org/repos/asf/spark/repo
Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/9d8e838d
Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/9d8e838d
Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/9d8e838d
Branch: refs/heads/master
Commit: 9d8e838d883ed21f9ef562e7e3ac074c7e4adb88
Parents: 5ffe752
Author: Stephen Hopper <sh...@shopper-osx.local>
Authored: Tue Sep 8 14:36:34 2015 +0100
Committer: Sean Owen <so...@cloudera.com>
Committed: Tue Sep 8 14:36:34 2015 +0100
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README.md | 4 ++--
docs/quick-start.md | 16 ++++++++--------
2 files changed, 10 insertions(+), 10 deletions(-)
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http://git-wip-us.apache.org/repos/asf/spark/blob/9d8e838d/README.md
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diff --git a/README.md b/README.md
index 380422c..76e29b4 100644
--- a/README.md
+++ b/README.md
@@ -1,7 +1,7 @@
# Apache Spark
Spark is a fast and general cluster computing system for Big Data. It provides
-high-level APIs in Scala, Java, and Python, and an optimized engine that
+high-level APIs in Scala, Java, Python, and R, and an optimized engine that
supports general computation graphs for data analysis. It also supports a
rich set of higher-level tools including Spark SQL for SQL and DataFrames,
MLlib for machine learning, GraphX for graph processing,
@@ -94,5 +94,5 @@ distribution.
## Configuration
-Please refer to the [Configuration guide](http://spark.apache.org/docs/latest/configuration.html)
+Please refer to the [Configuration Guide](http://spark.apache.org/docs/latest/configuration.html)
in the online documentation for an overview on how to configure Spark.
http://git-wip-us.apache.org/repos/asf/spark/blob/9d8e838d/docs/quick-start.md
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diff --git a/docs/quick-start.md b/docs/quick-start.md
index ce2cc9d..d481fe0 100644
--- a/docs/quick-start.md
+++ b/docs/quick-start.md
@@ -126,7 +126,7 @@ scala> val wordCounts = textFile.flatMap(line => line.split(" ")).map(word => (w
wordCounts: spark.RDD[(String, Int)] = spark.ShuffledAggregatedRDD@71f027b8
{% endhighlight %}
-Here, we combined the [`flatMap`](programming-guide.html#transformations), [`map`](programming-guide.html#transformations) and [`reduceByKey`](programming-guide.html#transformations) transformations to compute the per-word counts in the file as an RDD of (String, Int) pairs. To collect the word counts in our shell, we can use the [`collect`](programming-guide.html#actions) action:
+Here, we combined the [`flatMap`](programming-guide.html#transformations), [`map`](programming-guide.html#transformations), and [`reduceByKey`](programming-guide.html#transformations) transformations to compute the per-word counts in the file as an RDD of (String, Int) pairs. To collect the word counts in our shell, we can use the [`collect`](programming-guide.html#actions) action:
{% highlight scala %}
scala> wordCounts.collect()
@@ -163,7 +163,7 @@ One common data flow pattern is MapReduce, as popularized by Hadoop. Spark can i
>>> wordCounts = textFile.flatMap(lambda line: line.split()).map(lambda word: (word, 1)).reduceByKey(lambda a, b: a+b)
{% endhighlight %}
-Here, we combined the [`flatMap`](programming-guide.html#transformations), [`map`](programming-guide.html#transformations) and [`reduceByKey`](programming-guide.html#transformations) transformations to compute the per-word counts in the file as an RDD of (string, int) pairs. To collect the word counts in our shell, we can use the [`collect`](programming-guide.html#actions) action:
+Here, we combined the [`flatMap`](programming-guide.html#transformations), [`map`](programming-guide.html#transformations), and [`reduceByKey`](programming-guide.html#transformations) transformations to compute the per-word counts in the file as an RDD of (string, int) pairs. To collect the word counts in our shell, we can use the [`collect`](programming-guide.html#actions) action:
{% highlight python %}
>>> wordCounts.collect()
@@ -217,13 +217,13 @@ a cluster, as described in the [programming guide](programming-guide.html#initia
</div>
# Self-Contained Applications
-Now say we wanted to write a self-contained application using the Spark API. We will walk through a
-simple application in both Scala (with SBT), Java (with Maven), and Python.
+Suppose we wish to write a self-contained application using the Spark API. We will walk through a
+simple application in Scala (with sbt), Java (with Maven), and Python.
<div class="codetabs">
<div data-lang="scala" markdown="1">
-We'll create a very simple Spark application in Scala. So simple, in fact, that it's
+We'll create a very simple Spark application in Scala--so simple, in fact, that it's
named `SimpleApp.scala`:
{% highlight scala %}
@@ -259,7 +259,7 @@ object which contains information about our
application.
Our application depends on the Spark API, so we'll also include an sbt configuration file,
-`simple.sbt` which explains that Spark is a dependency. This file also adds a repository that
+`simple.sbt`, which explains that Spark is a dependency. This file also adds a repository that
Spark depends on:
{% highlight scala %}
@@ -302,7 +302,7 @@ Lines with a: 46, Lines with b: 23
</div>
<div data-lang="java" markdown="1">
-This example will use Maven to compile an application jar, but any similar build system will work.
+This example will use Maven to compile an application JAR, but any similar build system will work.
We'll create a very simple Spark application, `SimpleApp.java`:
@@ -374,7 +374,7 @@ $ find .
Now, we can package the application using Maven and execute it with `./bin/spark-submit`.
{% highlight bash %}
-# Package a jar containing your application
+# Package a JAR containing your application
$ mvn package
...
[INFO] Building jar: {..}/{..}/target/simple-project-1.0.jar
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