Hi List,
>From the looks of it everything is possible but I still have some
questions. My application consist of events being upserted that expire
after 30 seconds and doing aggregations on those. I always filter on
user_id which is also the routing_value.
event_fields =
{"user_id","timestamp","tags","dimension1","dimension2","dimension3"}
Questions:
1. 97% of queries are upserts of events that expire after 30 seconds.
These will be bulk inserted. Since I'll always filter_by timestamp, it's no
problem that TTL only deletes every 60seconds.
2. Can I disable the translog/commit-log (something like postgresql
UNLOGGED TABLE)? So if the node crashes I don't care that I'll loose all
data because they would be expired anyway after restarting.
3. 2% of queries will be an aggregation query which will always filter
on "user_id", but may also filter on all the fields. Should I index every
field ? I think I only need to index user_id and the TTL. Because it would
be too much overhead even maintaining the indexes, because of expiring
documents.
4. How can I get a top-hits-aggregation on an array's elements field ?
Basically explode/unnest the array and top-hit-aggregate the elements. Or
is that done automatically ?
5. There is no "exact distinct aggregation", only approximate?
6. Is there an in-memory option ? With no disk activity ? I remember
reading some threads that in-memory wasn't very good since it was stored on
the java-heap ?
7. Can I select in the mapping, that TTL uses data from the 'timestamp'
field? So I don't have both 'timestamp' and 'ttl' as separate field-indexes.
8. Most of the queries will only aggregate at most 100K documents,
usually <=10K, so I think I only need to tune indexing and deleting
performance.
9. Should I disable compression? Since my most concern is about
cpu-usage, and compression/decompression will slow it down.
Thanks
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