It is up to the SQL statement to control the rows that are fetched when the
JDBC river restarts.
Note that rivers are deprecated. One of the reason because rivers are
obsoleted is the undefined state if a node restarts. JDBC river simply
re-runs the SQL statement.
Use the JDBC plugin in standalone feeder mode for better control what data
is indexed, e.g. one initial run to index all data, and a cron job for
incremental data.
Jörg
On Sun, Apr 19, 2015 at 6:47 PM, GWired <garrettcjohn...@gmail.com> wrote:
> I have a river created using the column strategy.
>
> Whenever the system reboots or restarts it appears that the river is
> forgetting it's last place and starts all over again.
>
> These systems will do updates from time to time and rebuilding the indexes
> is taking a really long time slowing down performance of elastic search.
>
> Here's an example of one of the built river documents.
>
> PUT _river/mytypename/_meta
> {
> "type":"jdbc",
> "jdbc": {
> "url":"jdbc:sqlserver://servername.mydomain.com:1433
> ;databaseName=mydbname;integratedSecurity=true;",
> "sql":"SELECT id as _id, * FROM [mydbname].[dbo].[mytypename]",
> "strategy":"column",
> "created_at":"createddate",
> "updated_at":"lastmodifieddate",
> "schedule":"0 0-55 0-23 ? * *",
> "autocommit":true,
> "index":"jdbc",
> "type":"mytypename"
> }
> }
>
> Any ideas on how to handle this? It takes about 6 hours for it to get all
> the data and during that time ElasticSearch becomes very slow.
>
>
>
>
>
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