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Independent SQL-On-Hadoop Benchmark of SparkSQL, Impala, and Hive

14 点作者 mb22大约 9 年前

1 comment

mb22大约 9 年前
50 days ago on the &quot;Announcing Spark 1.6 (databricks.com)&quot; thread I mentioned that we were doing a 3rd party SQL-on-Hadoop benchmark (<a href="https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=10837758" rel="nofollow">https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=10837758</a>) and a bunch of folks sent me notes asking for a heads up when the results were in.<p>Well, we are done with our analysis and have a blog post offering up up the bulk of the results - <a href="http:&#x2F;&#x2F;blog.atscale.com&#x2F;how-different-sql-on-hadoop-engines-satisfy-bi-workloads" rel="nofollow">http:&#x2F;&#x2F;blog.atscale.com&#x2F;how-different-sql-on-hadoop-engines-...</a><p>The blog has the majority of the results, and additionally there is a registration link for the full 17 page whitepaper if you are really keen on SQL-on-Hadoop. www.atscale.com&#x2F;benchmark<p>Trystan, the engineer that did the bulk of the benchmark work, would be happy to answer questions regarding the methodology, hardware, etc.<p>Due to how fast these engines are evolving, we plan on doing an update to this benchmark on a quarterly basis.