Hi Vladimir,Not really, we do not want to store historical data in cache or may
be cache it for few hours and then evict it.But if recent data is missing in
cache then yes we want to cache it.So it would require some custom caching
logic to decide which data to cache.So seems like storing historical data in
persistent storage seems reasonable.The only thing is I have to use ignite
cache as side cache rather than a write through cache to HDFS, because i dont
think it would be nice idea to store individual key value pair in cache.May be
can think about HBase bt not directly to HDFS.
Regards,Vij
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On Thu, 14 Apr, 2016 at 7:26 pm, Vladimir Ozerov<[email protected]> wrote:
Hi Vij,
Storing hot recent data in cache, and historical data in persistent store
sounds like a perfectly reasonable idea.
If you decide to store historical data in HDFS, then you should be able to
construct HDFS path from the key because store interface accepts keys to
store/load data. If this is possible, then I do not see any obvious problems
with this approach.
On the other hand, do you want this historical data to be cached on access?
Vladimir.
On Thu, Apr 14, 2016 at 3:17 PM, vijayendra bhati <[email protected]>
wrote:
Thanks Vladimir !!
The drawback with using HDFS as persistent store behind Ignite cache is how we
will take care of appending single key value pair to HDFS file.Ideally we
should use some NoSQL store or RDBMS as persistent back up behind Ignite cache
and then run some scheduled batch to transfer the data to HDFS as it happens in
normal Lambda Architecture.
Now question comes why we want to use Ignite Cache ? Answer is it gives SQL
interface that means we can query on any attribute on the fly.Other we could
have used any other NoSQL. But NoSQL data model is entirely based upon query
pattern so to bring the flexibility at the time of query we think Ignite cache
would be better.
For our use case we want to put the latest 2 week data in Ignite cache to meet
the latency requirements and then for any back date get the data from backend
persistent storage, for which we are thinking about HDFS.Thats why we were
thinking if we can make Ignite cache write through cache with HDFS as backed up
persistent storage it would serve the purpose.
Please let me know whats your view on this.
Many thanks,Vij
On Wednesday, April 13, 2016 8:58 PM, Vladimir Ozerov
<[email protected]> wrote:
Vij,
No, it doesn't. IGFS serves the very different purpose - it is
Hadoop-compatible file system. It means that, for example, you can load data to
IGFS and then query it using Hive. But native Ignite SQL is not applicable here.
Vladimir.
On Wed, Apr 13, 2016 at 3:55 PM, vijayendra bhati <[email protected]>
wrote:
Thanks Vladimir,
I have not gone through complete documentation but if you could let me know
does IGFS provide SQL support like Ignite cache does ?
Regards,Vij
On Wednesday, April 13, 2016 5:54 PM, Vladimir Ozerov
<[email protected]> wrote:
Hi Vijayendra,
IGFS is designed to be a distributed file system which could cache data from
Hadoop file systems. It cannot be used as cache store by design.Ignite doesn't
have store implementation for HDFS, so you should implement your own if needed.
Particularly, you should implement org.apache.ignite.cache.store.CacheStore
interface.
Vladimir.
On Wed, Apr 13, 2016 at 2:38 PM, vijayendra bhati <[email protected]>
wrote:
Hi,
Can some body please provide me any pointers regarding how I can use Ignite
Data Grid/ In Memory caching with write through/write behind mode and writing
to HDFS ?
I know Ignite provides IGFS but its different from what I am looking for.
The other way could be I can use IGFS as my In Memory store but is it the right
approach ?
Regards,Vijayendra Bhati
