Fast merge #848
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Fast merge #848
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antgonza
reviewed
Sep 4, 2020
| list_list = [[r, c, v] for (r, c), v in collapsed_rcv.items()] | ||
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| return self.__class__(list_list, feature_order, sample_order) | ||
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| def merge(self, other, sample='union', observation='union', |
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Will it be worth adding a flag to merge to ignore metadata; this will be helpful if we wanted to force using the fast merge and our tables have metadata and we want to ignore.
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Oh, ya, that's a really good idea. Will do
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@wasade, thank you! Looks good! |
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Added a (much) faster way to merge tables when the axes overlap.
Table.concatis still (much) faster for the special case where one axis is assured to be disjoint. This revised merge method can operate on many tables at once, unlike the existingmergewhich took a single table.I don't have exact timing information, but the existing merge with four tables, each with roughly 600 samples and 1M features, was around 3 hours. This new method took a few minutes.