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Hi,
Thanks for the replies, I guess I was hoping for a bit better than linear
scaling, this was performing IndexedRDD.join(RDD)((id, a, b) => (a, b)). In
each join every row in the smaller table is joined to one in the lookup. I
ran the same test with standard RDD joins and there was barely any ti
Hi guys,
I'm interested in the IndexedRDD too.
How many rows in the big table that matches the small table in every run?
If the number of rows stay constant, then I think Jem wants the runtime to
stay about constant (i.e. ~ 0.6 second for all cases). However, I agree
with Andrew. The performance w
Hi Jem,
Linear time in scaling on the big table doesn't seem that surprising to
me. What were you expecting?
I assume you're doing normalRDD.join(indexedRDD). If you were to replace
the indexedRDD with a normal RDD, what times do you get?
On Tue, Jan 13, 2015 at 5:35 AM, Jem Tucker wrote:
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