+1 having a queue and consumers between your source of truth and ES is a
great approach. You cab decouple and independently scale ( and stop when
needed as DP said) the different components, minimising impact to your
users.
On 09/01/2014 7:35 AM, "David Pilato" <[email protected]> wrote:

> I would do 1/ to have a more near real time search.
> Also, I'd the idea that I have an object in memory and I simply push it to
> MySQL and to ES in the same time. No need to read again the object from
> MySQL to index it in another process (proposition 2)
>
> That said you could use also a Message Queue in the middle if you want to
> be able at some point to stop your ES cluster without stopping your
> application.
> This is what I did in the past.
>
> My 2 cents
>
> --
> *David Pilato* | *Technical Advocate* | *Elasticsearch.com*
> @dadoonet <https://twitter.com/dadoonet> | 
> @elasticsearchfr<https://twitter.com/elasticsearchfr>
>
>
> Le 8 janvier 2014 at 20:13:40, arthurX 
> ([email protected]<//[email protected]>)
> a écrit:
>
> Hello! I use MySQL as my primary datastore and use Elasticsearch to
> further index the documents.
> My problem is keeping the data in ES in sync with MySQL.
>
> Currently I have two methods in mind:
> 1. whenever add or update an entry in MySQL, do the action together in ES.
> 2. Do some cron jobs that periodically keep ES in sync with the data in
> MySQL.
>
> For method 2 I wonder how can I check if an entry is already indexed in
> Elasticsearch. And would it be efficient at all if I have to check every
> entry to see if it is updated?
>
> I am new to the technology and I am afraid I had missed some really
> obvious and established solutions here. Or otherwise the "normal" way this
> situation is handled?
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