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| author | Matei Alexandru Zaharia <matei@apache.org> | 2014-07-18 20:55:11 +0000 |
|---|---|---|
| committer | Matei Alexandru Zaharia <matei@apache.org> | 2014-07-18 20:55:11 +0000 |
| commit | 7427588a2716434f4c6478dc6513c097896a2bf0 (patch) | |
| tree | d5e5c8bf56b8b6ccd9badd706cac622e638d7eff | |
| parent | d6593a8afc64c77416ed6cbe6540b4b755f4d0e9 (diff) | |
| download | spark-website-7427588a2716434f4c6478dc6513c097896a2bf0.tar.gz spark-website-7427588a2716434f4c6478dc6513c097896a2bf0.tar.bz2 spark-website-7427588a2716434f4c6478dc6513c097896a2bf0.zip | |
tweak
| -rw-r--r-- | faq.md | 2 | ||||
| -rw-r--r-- | site/faq.html | 2 |
2 files changed, 2 insertions, 2 deletions
@@ -23,7 +23,7 @@ streaming, interactive queries, and machine learning. <p class="answer">Spark supports Scala, Java and Python.</p> <p class="question">How large a cluster can Spark scale to?</p> -<p class="answer">We are aware of multiple deployments on over 1000 nodes.</p> +<p class="answer">We have seen multiple deployments on over 1000 nodes.</p> <p class="question">What happens when a cached dataset does not fit in memory?</p> <p class="answer">Spark can either spill it to disk or recompute the partitions that don't fit in RAM each time they are requested. By default, it uses recomputation, but you can set a dataset's <a href="{{site.url}}docs/latest/scala-programming-guide.html#rdd-persistence">storage level</a> to <code>MEMORY_AND_DISK</code> to avoid this. </p> diff --git a/site/faq.html b/site/faq.html index 749260635..e5c76be08 100644 --- a/site/faq.html +++ b/site/faq.html @@ -174,7 +174,7 @@ streaming, interactive queries, and machine learning. <p class="answer">Spark supports Scala, Java and Python.</p> <p class="question">How large a cluster can Spark scale to?</p> -<p class="answer">We are aware of multiple deployments on over 1000 nodes.</p> +<p class="answer">We have seen multiple deployments on over 1000 nodes.</p> <p class="question">What happens when a cached dataset does not fit in memory?</p> <p class="answer">Spark can either spill it to disk or recompute the partitions that don't fit in RAM each time they are requested. By default, it uses recomputation, but you can set a dataset's <a href="/docs/latest/scala-programming-guide.html#rdd-persistence">storage level</a> to <code>MEMORY_AND_DISK</code> to avoid this. </p> |