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| author | Patrick Wendell <pwendell@apache.org> | 2013-09-28 23:44:45 +0000 |
|---|---|---|
| committer | Patrick Wendell <pwendell@apache.org> | 2013-09-28 23:44:45 +0000 |
| commit | 1084e2c734bbe813457b9288b99880eb3e0a0e1a (patch) | |
| tree | d7b88982918aa98dd19044f45c72ca2a6b51a2b8 /examples.md | |
| parent | 08d4f7700212b606b6e01bfb97ed25fa74e831b3 (diff) | |
| download | spark-website-1084e2c734bbe813457b9288b99880eb3e0a0e1a.tar.gz spark-website-1084e2c734bbe813457b9288b99880eb3e0a0e1a.tar.bz2 spark-website-1084e2c734bbe813457b9288b99880eb3e0a0e1a.zip | |
Make examples from GitHub more prominent
Diffstat (limited to 'examples.md')
| -rw-r--r-- | examples.md | 5 |
1 files changed, 4 insertions, 1 deletions
diff --git a/examples.md b/examples.md index 36c8415e6..783643354 100644 --- a/examples.md +++ b/examples.md @@ -8,7 +8,10 @@ navigation: --- <h2>Spark Examples</h2> -Spark is built around <em>distributed datasets</em> that support types of parallel operations: transformations, which are lazy and yield another distributed dataset (e.g., <code>map</code>, <code>filter</code>, and <code>join</code>), and actions, which force the computation of a dataset and return a result (e.g., <code>count</code>). The following examples show off some of the available operations and features. Several additional examples are distributed with Spark, both for core Spark ([Scala examples](https://github.com/apache/incubator-spark/tree/master/examples/src/main/scala/org/apache/spark/examples), [Java examples](https://github.com/apache/incubator-spark/tree/master/examples/src/main/java/org/apache/spark/examples), [Python examples](https://github.com/apache/incubator-spark/tree/master/python/examples)) and streaming Spark ([Scala examples](https://github.com/apache/incubator-spark/tree/master/examples/src/main/scala/org/apache/spark/streaming/examples), [Java examples](https://github.com/apache/incubator-spark/tree/master/examples/src/main/java/org/apache/spark/streaming/examples)). +Spark is built around <em>distributed datasets</em> that support types of parallel operations: transformations, which are lazy and yield another distributed dataset (e.g., <code>map</code>, <code>filter</code>, and <code>join</code>), and actions, which force the computation of a dataset and return a result (e.g., <code>count</code>). The following examples show off some of the available operations and features. Several additional examples are distributed with Spark: + + * Core Spark: [Scala examples](https://github.com/apache/incubator-spark/tree/master/examples/src/main/scala/org/apache/spark/examples), [Java examples](https://github.com/apache/incubator-spark/tree/master/examples/src/main/java/org/apache/spark/examples), [Python examples](https://github.com/apache/incubator-spark/tree/master/python/examples) + * Streaming Spark: [Scala examples](https://github.com/apache/incubator-spark/tree/master/examples/src/main/scala/org/apache/spark/streaming/examples), [Java examples](https://github.com/apache/incubator-spark/tree/master/examples/src/main/java/org/apache/spark/streaming/examples) <h3>Text Search</h3> |