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From Denis Magda <dma...@gridgain.com>
Subject Re: 答复: How can I only get the local data
Date Mon, 29 Feb 2016 13:52:19 GMT
 > but I will use the “ignite.compute().broadcast()” method to get all 
data(for example, aggregate in server node)

There is no sense to use compute.broadcast() and local query at all 
because SQL engine does this properly for you out of the box. So in such 
a case just execute query and all the nodes that store cache XX data 
will receive the request and return their portion of data.

 > Or, Is there another method to use “select * from XX where XX” to get 
the local data in partition cache method ?

Give me an example of a real SQL you're executing.

--
Denis

On 2/29/2016 2:30 PM, smilehong(洪利平) wrote:
>
> Yes, You are right,  but I will use the “ignite.compute().broadcast()” 
> method to get all data(for example, aggregate in server node),  so I 
> want to know that  set Query.setLocal to "true" can solute this 
> problem ( Get data only from local node) ?
>
> Or, Is there another method to use “select * from XX where XX” to get 
> the local data in partition cache method ?
>
> *发件人:*Denis Magda [mailto:dmagda@gridgain.com]
> *发 送时间:*2016年2月29日19:12
> *收件人:*user@ignite.apache.org
> *主题:*Re: How can I only get the local data(Internet mail)
>
> Hi,
>
> Presently there is no a reliable way to execute a SQL query over local 
> collocated data.
> Even if you set Query.setLocal to "true" there is a chance that you 
> will get incomplete result set if re-partitioning happened at some 
> point of the query execution.
>
> However, it's planned to support the feature that will execute a query 
> on a specific machine if it's know that all the data is located there.
> Igniters, have we already created a ticket for this feature?
>
> --
> Denis
>
> On 2/29/2016 10:52 AM, smilehong(洪利平) wrote:
>
>     Hi, all
>
>       when I use the “select * from XX where XX” in ignite, how can I
>     only get the local data ? because it obtain data on all nodes
>     default. And I have configure the cache modes is partitioned mode.
>
>      Thank you very much!
>


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