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| author | Matei Alexandru Zaharia <matei@apache.org> | 2016-02-19 23:14:46 +0000 |
|---|---|---|
| committer | Matei Alexandru Zaharia <matei@apache.org> | 2016-02-19 23:14:46 +0000 |
| commit | 903fb3011c61e9b17eb661429a6e0fdf3baddb78 (patch) | |
| tree | 5a30ae13831613087d45e2e3f256d47a62630d13 /site/releases/spark-release-1-4-0.html | |
| parent | 86876315ebae65afaf7f6853f4b61b4b1d7f380c (diff) | |
| download | spark-website-903fb3011c61e9b17eb661429a6e0fdf3baddb78.tar.gz spark-website-903fb3011c61e9b17eb661429a6e0fdf3baddb78.tar.bz2 spark-website-903fb3011c61e9b17eb661429a6e0fdf3baddb78.zip | |
Reference full software name on download page
Diffstat (limited to 'site/releases/spark-release-1-4-0.html')
| -rw-r--r-- | site/releases/spark-release-1-4-0.html | 4 |
1 files changed, 2 insertions, 2 deletions
diff --git a/site/releases/spark-release-1-4-0.html b/site/releases/spark-release-1-4-0.html index 28bbd184f..a9aa577ad 100644 --- a/site/releases/spark-release-1-4-0.html +++ b/site/releases/spark-release-1-4-0.html @@ -237,7 +237,7 @@ Python coverage. MLlib also adds several new algorithms.</p> </ul> <h3 id="spark-streaming">Spark Streaming</h3> -<p>Spark streaming adds visual instrumentation graphs and significantly improved debugging information in the UI. It also enhances support for both Kafka and Kinesis.</p> +<p>Spark streaming adds visual instrumentation graphs and significantly improved debugging information in the UI. It also enhances support for both Kafka and Kinesis. </p> <ul> <li><a href="https://issues.apache.org/jira/browse/SPARK-7602">SPARK-7602</a>: Visualization and monitoring in the streaming UI including batch drill down (<a href="https://issues.apache.org/jira/browse/SPARK-6796">SPARK-6796</a>, <a href="https://issues.apache.org/jira/browse/SPARK-6862">SPARK-6862</a>)</li> @@ -263,7 +263,7 @@ Python coverage. MLlib also adds several new algorithms.</p> <h4 id="test-partners">Test Partners</h4> -<p>Thanks to The following organizations, who helped benchmark or integration test release candidates: <br /> Intel, Palantir, Cloudera, Mesosphere, Huawei, Shopify, Netflix, Yahoo, UC Berkeley and Databricks.</p> +<p>Thanks to The following organizations, who helped benchmark or integration test release candidates: <br /> Intel, Palantir, Cloudera, Mesosphere, Huawei, Shopify, Netflix, Yahoo, UC Berkeley and Databricks. </p> <h4 id="contributors">Contributors</h4> <ul> |