usman-m

Curious how you guys use contexts?

Almost. Currently continuous views that contain an ORDER BY or LIMIT clause are not supported.

They work better for non-sliding window queries. Triggers on sliding window queries are much more resource intensive, both for CPU and memory. Essentially, the trigger process has to keep track of tuples for each step in the window and combine them whenever any tuple is updated to get the new value.

Great stuff! For now it seems like this leaves out the job of finding crowd workers. Could it be possible to do something like designing microtasks in MTurk and "stitching" the workflow together using Orchestra?

Our native implementations of all probabilistic data structures use MurmurHash3, so this isn't a problem. The dumbloom implementation is in no way a good Bloom filter, as the name suggests :)

Oops, it was meant to be:

  SELECT <user_id> FROM (SELECT DISTINCT user_id FROM user_actions);

You're absolutely right that both those queries will give the same result. I guess I was trying to motivate the basic problem of finding whether some user exists in a set of users, and `SELECT DISTINCT` is the SQL way of representing a set.

Fixed the post, thanks!

ahachete, I'm not sure if I totally understand your question.

Continuous views are consumers for streams. You can think of them as high throughput real-time materialized views. The source of data for the stream can be practically anything. Logical decoding on the other hand is a producer of streaming data--it's basically a human readable replication log. So you could potentially stream the logically decoded log into PipelineDB and build some continuous views in front of it.