Yep, that makes it clear. I think an unlogged batch of prepared statements with one statement per PK tuple would be roughly equivalent? And probably no more complex to generate in the client?
On Thu, 9 Feb 2017 at 20:22 Benjamin Roth <benjamin.r...@jaumo.com> wrote: > Maybe that makes it clear: > > DELETE FROM ks.cf WHERE (partitionkey1, partitionkey2) IN ((1, 2), (1, > 3), (2, 3), (3, 4)); > > If want to delete or select a bunch of records identified by their > multi-partitionkey tuples. > > 2017-02-09 10:18 GMT+01:00 Ben Slater <ben.sla...@instaclustr.com>: > > Are you looking this to be equivalent to (PK1=1 AND PK2=2) or are you > looking for (PK1 IN (1,2) AND PK2 IN (1,2)) or something else? > > Cheers > Ben > > On Thu, 9 Feb 2017 at 20:09 Benjamin Roth <benjamin.r...@jaumo.com> wrote: > > Hi Guys, > > CQL says this is not allowed: > > DELETE FROM ks.cf WHERE (pk1, pk2) IN ((1, 2)); > > 1. Is there a reason for it? There shouldn't be a performance penalty, it > is a PK lookup, the same thing works with a single pk column > 2. Is there a known workaround for it? > > It would be much of a help to have it for daily business, IMHO it's a > waste of resources to run multiple queries just to fetch a bunch of records > by a PK. > > Thanks in advance for any reply > > -- > Benjamin Roth > Prokurist > > Jaumo GmbH · www.jaumo.com > Wehrstraße 46 · 73035 Göppingen · Germany > Phone +49 7161 304880-6 <+49%207161%203048806> · Fax +49 7161 304880-1 > <+49%207161%203048801> > AG Ulm · HRB 731058 · Managing Director: Jens Kammerer > > -- > ———————— > Ben Slater > Chief Product Officer > Instaclustr: Cassandra + Spark - Managed | Consulting | Support > +61 437 929 798 <+61%20437%20929%20798> > > > > > -- > Benjamin Roth > Prokurist > > Jaumo GmbH · www.jaumo.com > Wehrstraße 46 · 73035 Göppingen · Germany > Phone +49 7161 304880-6 <+49%207161%203048806> · Fax +49 7161 304880-1 > <+49%207161%203048801> > AG Ulm · HRB 731058 · Managing Director: Jens Kammerer > -- ———————— Ben Slater Chief Product Officer Instaclustr: Cassandra + Spark - Managed | Consulting | Support +61 437 929 798
