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authorMatei Alexandru Zaharia <matei@apache.org>2014-02-03 06:30:49 +0000
committerMatei Alexandru Zaharia <matei@apache.org>2014-02-03 06:30:49 +0000
commitffa89cfbb0887db1e53b4e774359003daae7a62c (patch)
tree5ed6f8036d7af23d321c7d9652630035b26b3fc1
parent61203830f49cf7f5ce82f70ead2a155e256c02ee (diff)
downloadspark-website-ffa89cfbb0887db1e53b4e774359003daae7a62c.tar.gz
spark-website-ffa89cfbb0887db1e53b4e774359003daae7a62c.tar.bz2
spark-website-ffa89cfbb0887db1e53b4e774359003daae7a62c.zip
fix image path
-rw-r--r--releases/_posts/2013-09-25-spark-release-0-8-0.md2
-rw-r--r--site/releases/spark-release-0-8-0.html2
2 files changed, 2 insertions, 2 deletions
diff --git a/releases/_posts/2013-09-25-spark-release-0-8-0.md b/releases/_posts/2013-09-25-spark-release-0-8-0.md
index 8cb5b4edf..6ca6ecb37 100644
--- a/releases/_posts/2013-09-25-spark-release-0-8-0.md
+++ b/releases/_posts/2013-09-25-spark-release-0-8-0.md
@@ -19,7 +19,7 @@ You can download Spark 0.8.0 as either a <a href="http://spark-project.org/downl
Spark now displays a variety of monitoring data in a web UI (by default at port 4040 on the driver node). A new job dashboard contains information about running, succeeded, and failed jobs, including percentile statistics covering task runtime, shuffled data, and garbage collection. The existing storage dashboard has been extended, and additional pages have been added to display total storage and task information per-executor. Finally, a new metrics library exposes internal Spark metrics through various API’s including JMX and Ganglia.
<p style="text-align: center;">
-<img src="{{site.url}}/images/0.8.0-ui-screenshot.png" style="width:90%;">
+<img src="{{site.url}}images/0.8.0-ui-screenshot.png" style="width:90%;">
</p>
### Machine Learning Library
diff --git a/site/releases/spark-release-0-8-0.html b/site/releases/spark-release-0-8-0.html
index bce92d1e2..1bb741885 100644
--- a/site/releases/spark-release-0-8-0.html
+++ b/site/releases/spark-release-0-8-0.html
@@ -168,7 +168,7 @@
<p>Spark now displays a variety of monitoring data in a web UI (by default at port 4040 on the driver node). A new job dashboard contains information about running, succeeded, and failed jobs, including percentile statistics covering task runtime, shuffled data, and garbage collection. The existing storage dashboard has been extended, and additional pages have been added to display total storage and task information per-executor. Finally, a new metrics library exposes internal Spark metrics through various API’s including JMX and Ganglia.</p>
<p style="text-align: center;">
-<img src="//images/0.8.0-ui-screenshot.png" style="width:90%;" />
+<img src="/images/0.8.0-ui-screenshot.png" style="width:90%;" />
</p>
<h3 id="machine-learning-library">Machine Learning Library</h3>