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Right now I've got Logstash importing a miniature version of my MSSQL database, using the JDBC plugin. I've got each JDBC input scheduled to run every minute to update Elasticsearch. To update, I'm currently just re-importing every single table and row in my database, and adding all rows to Elasticsearch. When I begin using the full database though, this will be very inefficient as it will take more than a minute to go through the entire database. Is there another way to keep Elasticsearch in sync with my database? I've tried to use the 'sql_last_value' parameter to only import new rows into the database, but this will only work when the 'id' for my database table is a number, and each new entry in the table has a greater number than the last. Some tables in the database have an 'id' which can be completely random (ie. "43f4-f43ef-e44454r"), which cannot be used with 'sql_last_value' as they are impossible to compare. I'm also unable modify the actual database at all, which cuts out a lot of my potential solutions. I feel as if i am out of options here, so can anyone suggest anything that I can try?

Mark Rotteveel
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reno
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    Do you have a timestamp or date field that you can use? Usually `sql_last_value` works best with a `last_updated` date field. – Val Feb 27 '17 at 05:32

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