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From Konstantin Boudnik <...@apache.org>
Subject Re: Data Snapshots in Ignite
Date Wed, 21 Oct 2015 23:48:13 GMT
I like it quite a bit, as well! Ticket would make the most sense as well, so
there will be a single place to collect the design docs (if needed), etc.

On Wed, Oct 21, 2015 at 04:45PM, Dmitriy Setrakyan wrote:
> I also really like the idea. One potential use case is fraud analysis in
> financial institutions. Rarely it makes sense to perform such analysis on a
> life system, but rather a snapshot of some data needs to be taken and
> analyzed offline.
> 
> I think snapshots should be saved to disk, so users could load them for
> analysis on a totally different cluster.

I think disk persistence should be optional, not mandatory.

Cos

> Raul, if you don’t mind, can you file a ticket and see if anyone in the
> community wants to pick it up?
> 
> D.
> 
> On Wed, Oct 21, 2015 at 5:51 AM, Sergi Vladykin <sergi.vladykin@gmail.com>
> wrote:
> 
> > Raul,
> >
> > Actually SQL indexes are already snapshotable. I'm not sure if it does make
> > sense to make
> > the whole cache (with full cache API support) snapshotable, but I like your
> > idea
> > about running multiple SQL statements against the same snapshot.
> >
> > Also I don't think that it is a good idea to keep snapshots for a long
> > time,
> > so I'd prefer to have typical AutoClosable API like:
> >
> > try (Snapshot s = ...) {
> >     s.query(...);
> >     s.query(...);
> >     s.query(...);
> > }
> >
> > Though I'm not sure when we will be able to get down to this.
> >
> > Sergi
> >
> > 2015-10-21 12:06 GMT+03:00 Raul Kripalani <raulk@apache.org>:
> >
> > > Hey guys,
> > >
> > > LevelDb has a functionality called Snapshots which provides a consistent
> > > read-only view of the DB at a given point in time, against which queries
> > > can be executed.
> > >
> > > To my knowledge, this functionality doesn't exist in the world of open
> > > source In-Memory Computing. Ignite could be an innovator here.
> > >
> > > Ignite Snapshots would allow queries, distributed closures, map-reduce
> > > jobs, etc. It could be useful for Spark RDDs to avoid data shift while
> > the
> > > computation is taking place (not sure if there's already some form of
> > > snapshotting, though). Same for IGFS.
> > >
> > > Example usage:
> > >
> > >     IgniteCacheSnapshot snapshot =
> > > ignite.cache("mycache").snapshots().create();
> > >
> > >     // all three queries are executed against a view of the cache at the
> > > point in time where it was snapshotted
> > >     snapshot.query("select ...");
> > >     snapshot.query("select ...");
> > >     snapshot.query("select ...");
> > >
> > > In fact, it would be awesome to be able to logically save this snapshot
> > > with a name so that later jobs, queries, etc. can run on top of it, e.g.:
> > >
> > >     IgniteCacheSnapshot snapshot =
> > > ignite.cache("mycache").snapshots().create("abc");
> > >
> > >     // ...
> > >     // in another module of a distributed system, or in another thread in
> > > parallel, use the saved snapshot
> > >     IgniteCacheSnapshot snapshot =
> > > ignite.cache("mycache").snapshots().get("abc");
> > >     ....
> > >
> > > Named snapshotting can be dangerous due to data retention, e.g. imagine
> > > keeping a snapshot for 2 weeks! So we should force the user to specify a
> > > TTL:
> > >
> > >     IgniteCacheSnapshot snapshot =
> > > ignite.cache("mycache").snapshots().create("abc", 2, TimeUnit.HOURS);
> > >
> > > Such functionality would allow for "reporting checkpoints" and "time
> > > travel", for example, where you want users to be able to query the data
> > as
> > > it stood 1 hour ago, 2 hours ago, etc.
> > >
> > > What do you think?
> > >
> > > P.S.: We do have some form of snapshotting in the Compute checkpointing
> > > functionality – but my proposal is to generalise the notion.
> > >
> > > Regards,
> > >
> > > *Raúl Kripalani*
> > > PMC & Committer @ Apache Ignite, Apache Camel | Integration, Big Data and
> > > Messaging Engineer
> > > http://about.me/raulkripalani | http://www.linkedin.com/in/raulkripalani
> > > http://blog.raulkr.net | twitter: @raulvk
> > >
> >

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