diff options
Diffstat (limited to 'docs')
| -rw-r--r-- | docs/_config.yml | 6 | ||||
| -rw-r--r-- | docs/building-with-maven.md | 4 | ||||
| -rw-r--r-- | docs/index.md | 2 | ||||
| -rw-r--r-- | docs/quick-start.md | 4 | ||||
| -rw-r--r-- | docs/streaming-programming-guide.md | 4 |
5 files changed, 10 insertions, 10 deletions
diff --git a/docs/_config.yml b/docs/_config.yml index f99d5bb376..5c135a0242 100644 --- a/docs/_config.yml +++ b/docs/_config.yml @@ -3,8 +3,8 @@ markdown: kramdown # These allow the documentation to be updated with nerw releases # of Spark, Scala, and Mesos. -SPARK_VERSION: 0.7.1-SNAPSHOT -SPARK_VERSION_SHORT: 0.7.1 -SCALA_VERSION: 2.9.2 +SPARK_VERSION: 0.8.0-SNAPSHOT +SPARK_VERSION_SHORT: 0.8.0 +SCALA_VERSION: 2.9.3 MESOS_VERSION: 0.9.0-incubating SPARK_ISSUE_TRACKER_URL: https://spark-project.atlassian.net diff --git a/docs/building-with-maven.md b/docs/building-with-maven.md index c2eeafd07a..04cd79d039 100644 --- a/docs/building-with-maven.md +++ b/docs/building-with-maven.md @@ -42,10 +42,10 @@ To run a specific test suite: You might run into the following errors if you're using a vanilla installation of Maven: - [INFO] Compiling 203 Scala sources and 9 Java sources to /Users/andyk/Development/spark/core/target/scala-2.9.2/classes... + [INFO] Compiling 203 Scala sources and 9 Java sources to /Users/me/Development/spark/core/target/scala-{{site.SCALA_VERSION}}/classes... [ERROR] PermGen space -> [Help 1] - [INFO] Compiling 203 Scala sources and 9 Java sources to /Users/andyk/Development/spark/core/target/scala-2.9.2/classes... + [INFO] Compiling 203 Scala sources and 9 Java sources to /Users/me/Development/spark/core/target/scala-{{site.SCALA_VERSION}}/classes... [ERROR] Java heap space -> [Help 1] To fix these, you can do the following: diff --git a/docs/index.md b/docs/index.md index 51d505e1fa..0c4add45dc 100644 --- a/docs/index.md +++ b/docs/index.md @@ -18,7 +18,7 @@ or you will need to set the `SCALA_HOME` environment variable to point to where you've installed Scala. Scala must also be accessible through one of these methods on slave nodes on your cluster. -Spark uses [Simple Build Tool](https://github.com/harrah/xsbt/wiki), which is bundled with it. To compile the code, go into the top-level Spark directory and run +Spark uses [Simple Build Tool](http://www.scala-sbt.org), which is bundled with it. To compile the code, go into the top-level Spark directory and run sbt/sbt package diff --git a/docs/quick-start.md b/docs/quick-start.md index 5c80d2ed3a..2d961b29cb 100644 --- a/docs/quick-start.md +++ b/docs/quick-start.md @@ -53,8 +53,8 @@ scala> textFile.filter(line => line.contains("Spark")).count() // How many lines res3: Long = 15 {% endhighlight %} -## Transformations -RDD transformations can be used for more complex computations. Let's say we want to find the line with the most words: +## More On RDD Operations +RDD actions and transformations can be used for more complex computations. Let's say we want to find the line with the most words: {% highlight scala %} scala> textFile.map(line => line.split(" ").size).reduce((a, b) => if (a > b) a else b) diff --git a/docs/streaming-programming-guide.md b/docs/streaming-programming-guide.md index b30699cf3d..f5788dc467 100644 --- a/docs/streaming-programming-guide.md +++ b/docs/streaming-programming-guide.md @@ -83,7 +83,7 @@ DStreams support many of the transformations available on normal Spark RDD's: <tr> <td> <b>groupByKey</b>([<i>numTasks</i>]) </td> <td> When called on a DStream of (K, V) pairs, returns a new DStream of (K, Seq[V]) pairs by grouping together all the values of each key in the RDDs of the source DStream. <br /> - <b>Note:</b> By default, this uses Spark's default number of parallel tasks (2 for local machine, 8 for a cluser) to do the grouping. You can pass an optional <code>numTasks</code> argument to set a different number of tasks. + <b>Note:</b> By default, this uses Spark's default number of parallel tasks (2 for local machine, 8 for a cluster) to do the grouping. You can pass an optional <code>numTasks</code> argument to set a different number of tasks. </td> </tr> <tr> @@ -132,7 +132,7 @@ Spark Streaming features windowed computations, which allow you to apply transfo <td> <b>groupByKeyAndWindow</b>(<i>windowDuration</i>, <i>slideDuration</i>, [<i>numTasks</i>]) </td> <td> When called on a DStream of (K, V) pairs, returns a new DStream of (K, Seq[V]) pairs by grouping together values of each key over batches in a sliding window. <br /> -<b>Note:</b> By default, this uses Spark's default number of parallel tasks (2 for local machine, 8 for a cluser) to do the grouping. You can pass an optional <code>numTasks</code> argument to set a different number of tasks.</td> +<b>Note:</b> By default, this uses Spark's default number of parallel tasks (2 for local machine, 8 for a cluster) to do the grouping. You can pass an optional <code>numTasks</code> argument to set a different number of tasks.</td> </tr> <tr> <td> <b>reduceByKeyAndWindow</b>(<i>func</i>, <i>windowDuration</i>, <i>slideDuration</i>, [<i>numTasks</i>]) </td> |