DaskとSparkの比較 / “If your problems vary beyond typical ETL + SQL and you want to add flexible parallelism to existing solutions then dask may be a good fit, especially if you are already using Python and associated libraries like NumPy and Pandas.”

dask
spark

msykt のブックマーク 2018/05/03 19:33

<blockquote class="hatena-bookmark-comment"><a class="comment-info" href="https://b.hatena.ne.jp/entry/363477316/comment/msykt" data-user-id="msykt" data-entry-url="https://b.hatena.ne.jp/entry/s/dask.pydata.org/en/latest/spark.html" data-original-href="https://dask.pydata.org/en/latest/spark.html" data-entry-favicon="https://cdn-ak2.favicon.st-hatena.com/64?url=https%3A%2F%2Fdask.pydata.org%2Fen%2Flatest%2Fspark.html" data-user-icon="/users/msykt/profile.png">Comparison to Spark — Dask documentation</a><ul class="comment-tag" style="list-style: none; margin: 0px;"><li style="float: left">[<a href="https://b.hatena.ne.jp/q/dask">dask</a>]</li><li style="float: left">[<a href="https://b.hatena.ne.jp/q/spark">spark</a>]</li></ul><br><p style="clear: left">DaskとSparkの比較 / “If your problems vary beyond typical ETL + SQL and you want to add flexible parallelism to existing solutions then dask may be a good fit, especially if you are already using Python and associated libraries like NumPy and Pandas.”</p><a class="datetime" href="https://b.hatena.ne.jp/msykt/20180503#bookmark-363477316"><span class="datetime-body">2018/05/03 19:33</span></a></blockquote><script src="https://b.st-hatena.com/js/comment-widget.js" charset="utf-8" async></script>

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