Redshift has this concept in the form of Short Query Acceleration. CREATE NONCLUSTERED INDEX IDXNCPhysicdateLastModified ON Physic(dateLastModified) Please advise. it has been running since 17 hours now but not yet completed, here is the script i am using to create one. As soon as your primary Mailcow server comes back online, the backup Mailcow will deliver the queued messages to each recipient’s inbox. This would allow the idea that small/medium queries finish quickly and large queries that already were going to take a while get queued which would provide a better user experience. i am creating non clustered index on on of the date columns that has 98393892 row. Instead of relying on the sender’s mail server to re-attempt delivery, setting up a backup MX server with Mailcow means that incoming messages will be received, even when your primary Mailcow server is down.
![backup exec 16 end queued forever backup exec 16 end queued forever](https://usermanual.wiki/Pdf/RedHatEnterpriseLinux7SystemAdministratorsGuideenUS.291851052-User-Guide-Page-1.png)
BigQuery has the concept of batch queries where they execute at a later point in time but are not as aggressively scheduled, they just don't apply towards your submission query limit then.Ģ) Athena analyze queries to classify a query as small/medium vs large queries so that small/medium queries can be prioritized differently in the queue. The underlying real time Presto clusters could be scaled more aggressively (and then reflected in the pricing model possibly). To be able to select the next task to run, the scheduler itself must execute at the end of each time slice1. I've logged some feature requests around making queue behavior more consistent but do not have visibility on their priority:ġ) Allow client to specify real time vs batch query - the pricing model or tenant quotas could be different for real time vs batch. 130325 16:20:55 server id 1 endlogpos 107 Start: binlog v 4, server v 5.5.30-log created 130325 16:20:55 at startup. A nice thing about the architecture though is compute (Athena/Presto) and storage (S3) is decoupled so you can bring up and down EMR clusters short term as needed, use spot instances etc. batch/scheduled workloads that are more flexible on responsiveness - or just if your users are internal analysts that don't mind that a query that may take 5-10 seconds engine time can periodically end up getting queued for a minute.Īlternatively, supplement Athena with EMR Presto where you have more control over resources and can just send your non time-sensitive workloads to Athena - of course this involves additional costs (EC2 + EMR costs) which isn't ideal if you're doing things fairly sparingly or at a small scale.
![backup exec 16 end queued forever backup exec 16 end queued forever](https://www.mdpi.com/sensors/sensors-21-06253/article_deploy/html/images/sensors-21-06253-g009-550.jpg)
In the current state I only recommend Athena for non-user facing requests e.g. From the documentation, Athena mentions this briefly and that it will try to scale out resources as needed to try to clear the queue/complete your queries as fast as possible but I've seen this as well (query in the queue for 1+ minutes, trying to track the frequency of this a bit but we also use EMR Presto to not all queries are being sent to Athena or they're cancelled if EMR Presto completes the query quickly). Athena is "serverless" but also a multi-tenant service so there's times when the overall load on the service makes it so that your query ends up being queued. Yeah, unfortunately this is fairly random/something you cannot control currently.