Hi Robert,

The architecture [1] suggested here is an ideal one. You deploy Ignite
separately as an in-memory store and use one of the replication techniques
to update the HDFS cluster:
* Hadoop Connector form [1].
* Implement a custom version of a CacheStore [2] interface that will push
all the changes from Ignite to Hadoop.

Does this work for you?

[1]
https://www.gridgain.com/docs/latest/integrations/datalake-accelerator/getting-started
[2]
https://apacheignite.readme.io/docs/3rd-party-store#section-custom-cachestore
-
Denis


On Fri, Oct 25, 2019 at 8:21 AM Munoz, Robert <[email protected]>
wrote:

> Hi Denis,
>
>
>
> Thank you for responding. The use case is to deploy ignite cluster on our
> Hadoop cluster nodes and make use of persistence to HDFS since the data
> disks have already been allocated for HDFS. I am new to ignite so am
> unfamiliar with its file/folder structure but the goal would be to use
> ignite as in memory cache for sql tables and to persist the data to HDFS as
> write through / read through . This should not impact the current HDFS
> configuration as we have users/applications using HDFS already.  The
> implementation should be standard sql and not hbase get/put operations. Let
> me know if this helps.
>
>
>
>
>
>
>
> Thanks,
>
>
>
> Robert Munoz
>
> 949-220-5169
>
> https://pimco.webex.com/meet/robert.munoz
>
>
>
>
>
>
>
> *From:* Denis Magda <[email protected]>
> *Sent:* Thursday, October 24, 2019 10:08 PM
> *To:* [email protected]
> *Subject:* Re: Support for hdfs caching
>
>
>
> Robert,
>
>
>
> Could you please describe your use case? There several options that might
> suit your needs.
>
>
>
> Denis
>
> On Thursday, October 24, 2019, Munoz, Robert <[email protected]>
> wrote:
>
> Hello,
>
>
>
> With the removal of Hadoop accelerator from ignite binaries, are there any
> other options for using HDFS as persistence store?
>
>
>
>
>
> Thanks,
>
>
>
> Robert Munoz
>
>
>
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> -
>
> Denis
>
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