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author | Sean Owen <sowen@cloudera.com> | 2016-10-09 12:43:24 +0100 |
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committer | Sean Owen <sowen@cloudera.com> | 2016-10-09 12:43:24 +0100 |
commit | 4fbd720ddf9dc899a7e62b3103da63f169174580 (patch) | |
tree | 8594b184271cecab411f29400f88eb904930a507 /site/releases/spark-release-1-4-0.html | |
parent | 5a6c152c8aa9dec698d13ad283ab37f043aeb6f4 (diff) | |
download | spark-website-4fbd720ddf9dc899a7e62b3103da63f169174580.tar.gz spark-website-4fbd720ddf9dc899a7e62b3103da63f169174580.tar.bz2 spark-website-4fbd720ddf9dc899a7e62b3103da63f169174580.zip |
Add new book per request; again fix minor differences in rendering from others' different/older jekyll versions?
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 9285d1829..fc02b6fbe 100644 --- a/site/releases/spark-release-1-4-0.html +++ b/site/releases/spark-release-1-4-0.html @@ -250,7 +250,7 @@ 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> @@ -276,7 +276,7 @@ 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> |